On TCP-based Session Initiation Protocol (SIP) Server Overload Control

Abstract: The Session Initiation Protocol (SIP) server overload management has attracted interest since SIP is being widely deployed in the Next Generation Networks (NGN) as a core signaling protocol. Yet all existing SIP overload control work is focused on SIP-over-UDP, despite the fact that TCP is increasingly seen as the more viable choice of SIP transport. This paper answers the following questions: is the existing TCP flow control capable of handling the SIP overload problem? If not, why and how can we make it work? We provide a comprehensive explanation of the default SIP-over-TCP overload behavior through server instrumentation. We also propose and implement novel but simple overload control algorithms without any kernel or protocol level modification. Experimental evaluation shows that with our mechanism the overload performance improves from its original zero throughput to nearly full capacity. Our work leads to the important general insight that the traditional notion of TCP flow control alone is incapable of managing overload for time-critical session-based applications, which would be applicable not only to SIP, but also to a wide range of other common applications such as database servers.


Oblivious Buy-at-Bulk in Planar Graphs

Abstract: In the oblivious buy-at-bulk network design problem in a graph, the task is to compute a fixed set of paths for every pair of source-destinations in the graph, such that any set of demands can be routed along these paths. The demands could be aggregated at intermediate edges where the fusion-cost is specified by a canonical (non-negative concave) function $f$. We give a novel algorithm for planar graphs which is oblivious with respect to the demands, and is also oblivious with respect to the fusion function $f$. The algorithm is deterministic and computes the fixed set of paths in polynomial time, and guarantees a $O(\log n)$ approximation ratio for any set of demands and any canonical fusion function $f$, where $n$ is the number of nodes. The algorithm is asymptotically optimal, since it is known that this problem cannot be approximated with better than $\Omega(\log n)$ ratio. To our knowledge, this is the first tight analysis for planar graphs, and improves the approximation ratio by a factor of $\log n$ with respect to previously known results.


Oblivious Algorithms for the Maximum Directed Cut Problem

Abstract: This paper introduces a special family of randomized algorithms for Max DICUT that we call oblivious algorithms. Let the bias of a vertex be the ratio between the total weight of its outgoing edges and the total weight of all its edges. An oblivious algorithm selects at random in which side of the cut to place a vertex v, with probability that only depends on the bias of v, independently of other vertices. The reader may observe that the algorithm that ignores the bias and chooses each side with probability 1/2 has an approximation ratio of 1/4, whereas no oblivious algorithm can have an approximation ratio better than 1/2 (with an even directed cycle serving as a negative example). We attempt to characterize the best approximation ratio achievable by oblivious algorithms, and present results that are nearly tight. The paper also discusses natural extensions of the notion of oblivious algorithms, and extensions to the more general problem of Max 2-AND.


Visual-hint Boundary to Segment Algorithm for Image Segmentation

Abstract: Image segmentation has been a very active research topic in image analysis area. Currently, most of the image segmentation algorithms are designed based on the idea that images are partitioned into a set of regions preserving homogeneous intra-regions and inhomogeneous inter-regions. However, human visual intuition does not always follow this pattern. A new image segmentation method named Visual-Hint Boundary to Segment (VHBS) is introduced, which is more consistent with human perceptions. VHBS abides by two visual hint rules based on human perceptions: (i) the global scale boundaries tend to be the real boundaries of the objects; (ii) two adjacent regions with quite different colors or textures tend to result in the real boundaries between them. It has been demonstrated by experiments that, compared with traditional image segmentation method, VHBS has better performance and also preserves higher computational efficiency.


Convolutional Matching Pursuit and Dictionary Training

Abstract: Matching pursuit and K-SVD is demonstrated in the translation invariant setting


A New Approach in Packet Scheduling in the Vanet

Abstract: Vehicular Ad hoc Networks (VANET) are expected to have great potential to improve both traffic safety and comfort in the future. When many vehicles want to access data through roadside unit, data scheduling become an important issue. In this paper, we identify some challenges in roadside based data access. To address these challenges we first review some existing scheduling schemes. We then propose a priority scheduling and finally show that using this idea can increase QOS compare to previous algorithms.


Nations At War I: Why do we keep building weapons?

Abstract: This paper is the first in series of four papers that present an analytical approach to war using game theory. We try to explore why is it that "true peace" can't be achieved and all or any efforts we make towards that goal will have huge road-blocks. A fairly simplistic and non technical overview of our approach is given in this paper using prisoner's dilemma.


Statistical Modelling of ft to Process Parameters in 30 nm Gate Length Finfets

Abstract: This paper investigates the effect of process variations on unity gain frequency (ft) in 30 nm gate length FinFET by performing extensive TCAD simulations. Six different geometrical parameters, channel doping, source/drain doping and gate electrode work function are studied for their sensitivity on ft. It is found that ft is more sensitive to gate length, underlap, gate-oxide thickness, channel and Source/Drain doping and less sensitive to source/drain width and length, and work function variations. Statistical modelling has been performed for ft through design of experiment with respect to sensitive parameters. The model has been validated through a comparison between random set of experimental data simulations and predicted values obtained from the model.


First results of the SOAP project. Open access publishing in 2010

Abstract: The SOAP (Study of Open Access Publishing) project has compiled data on the present offer for open access publishing in online peer-reviewed journals. Starting from the Directory of Open Access Journals, several sources of data are considered, including inspection of journal web site and direct inquiries within the publishing industry. Several results are derived and discussed, together with their correlations: the number of open access journals and articles; their subject area; the starting date of open access journals; the size and business models of open access publishers; the licensing models; the presence of an impact factor; the uptake of hybrid open access.


Inaccessibility-Inside Theorem for Point in Polygon

Abstract: The manuscript presents a theoretical proof in conglomeration with new definitions on Inaccessibility and Inside for a point S related to a simple or self intersecting polygon P. The proposed analytical solution depicts a novel way of solving the point in polygon problem by employing the properties of epigraphs and hypographs, explicitly. Contrary to the ambiguous solutions given by the cross over for the simple and self intersecting polygons and the solution of a point being multiply inside a self intersecting polygon given by the winding number rule, the current solution gives unambiguous and singular result for both kinds of polygons. Finally, the current theoretical solution proves to be mathematically correct for simple and self intersecting polygons.


The Impact of Data Replicatino on Job Scheduling Performance in Hierarchical data Grid

Abstract: In data-intensive applications data transfer is a primary cause of job execution delay. Data access time depends on bandwidth. The major bottleneck to supporting fast data access in Grids is the high latencies of Wide Area Networks and Internet. Effective scheduling can reduce the amount of data transferred across the internet by dispatching a job to where the needed data are present. Another solution is to use a data replication mechanism. Objective of dynamic replica strategies is reducing file access time which leads to reducing job runtime. In this paper we develop a job scheduling policy and a dynamic data replication strategy, called HRS (Hierarchical Replication Strategy), to improve the data access efficiencies. We study our approach and evaluate it through simulation. The results show that our algorithm has improved 12% over the current strategies.


Back To The Future: On Predicting User Uptime

Abstract: Correlation in user connectivity patterns is generally considered a problem for system designers, since it results in peaks of demand and also in the scarcity of resources for peer-to-peer applications. The other side of the coin is that these connectivity patterns are often predictable and that, to some extent, they can be dealt with proactively. In this work, we build predictors aiming to determine the probability that any given user will be online at any given time in the future. We evaluate the quality of these predictors on various large traces from instant messaging and file sharing applications. We also illustrate how availability prediction can be applied to enhance the behavior of peer-to-peer applications: we show through simulation how data availability is substantially increased in a distributed hash table simply by adjusting data placement policies according to peer availability prediction and without requiring any additional storage from any peer.


Performance of wireless network coding: motivating small encoding numbers

Abstract: This paper focuses on a particular transmission scheme called local network coding, which has been reported to provide significant performance gains in practical wireless networks. The performance of this scheme strongly depends on the network topology and thus on the locations of the wireless nodes. Also, it has been shown previously that finding the encoding strategy, which achieves maximum performance, requires complex calculations to be undertaken by the wireless node in real-time. Both deterministic and random point pattern are explored and using the Boolean connectivity model we provide upper bounds for the maximum coding number, i.e., the number of packets that can be combined such that the corresponding receivers are able to decode. For the models studied, this upper bound is of order of $\sqrt{N}$, where $N$ denotes the (mean) number of neighbors. Moreover, achievable coding numbers are provided for grid-like networks. We also calculate the multiplicative constants that determine the gain in case of a small network. Building on the above results, we provide an analytic expression for the upper bound of the efficiency of local network coding. The conveyed message is that it is favorable to reduce computational complexity by relying only on small encoding numbers since the resulting expected throughput loss is negligible.


A note on hierarchies and bureaucracies

Abstract: In this note, we argue that there is a bug in [Tirole, J., "Hierarchies and bureaucracies: On the role of collusion in organizations," {\em Journal of Law, Economics and Organization}, vol.2, 181-214, 1986].


A Fault Analytic Method against HB+

Abstract: The search for lightweight authentication protocols suitable for low-cost RFID tags constitutes an active and challenging research area. In this context, a family of protocols based on the LPN problem has been proposed: the so-called HB-family. Despite the rich literature regarding the cryptanalysis of these protocols, there are no published results about the impact of fault analysis over them. The purpose of this paper is to fill this gap by presenting a fault analytic method against a prominent member of the HB-family: HB+ protocol. We demonstrate that the fault analysis model can lead to a flexible and effective attack against HB-like protocols, posing a serious threat over them.


Methods for Accelerating Conway's Doomsday Algorithm (part 2)

Abstract: We propose a modification of a key component in the Doomsday Algorithm for calculating the day of the week of any calendar date. In particular, we propose to replace the calculation of the required term: \lfloor \frac{x}{12} \rfloor + x \bmod 12 + \lfloor \frac{x \bmod 12}{4} \rfloor with -[ \frac{x+11(x \bmod 2)}{2} + 11 (\frac{x+11(x \bmod 2)}{2}\bmod 2)] \bmod 7 for a 2-digit input year x; Although our expression looks daunting and complicated, we will explain why it is actually easy to calculate mentally.


Genetic Algorithm for Mulicriteria Optimization of a Multi-Pickup and Delivery Problem with Time Windows

Abstract: In This paper we present a genetic algorithm for mulicriteria optimization of a multipickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. This paper purposes a brief literature review of the PDPTW, present an approach based on genetic algorithms and Pareto dominance method to give a set of satisfying solutions to the m-PDPTW minimizing total travel cost, total tardiness time and the vehicles number.


Engineering Time-dependent One-To-All Computation

Abstract: Very recently a new algorithm to the nonnegative single-source shortest path problem on road networks has been discovered. It is very cache-efficient, but only on static road networks. We show how to augment it to the time-dependent scenario. The advantage if the new approach is that it settles nodes, even for a profile query, by scanning all downward edges. We improve the scanning of the downward edges with techniques developed for time-dependent many-to-many computations.


Shortest path problem in rectangular complexes of global nonpositive curvature

Abstract: CAT(0) metric spaces constitute a far-reaching common generalization of Euclidean and hyperbolic spaces and simple polygons: any two points x and y of a CAT(0) metric space are connected by a unique shortest path {\gamma}(x,y). In this paper, we present an efficient algorithm for answering two-point distance queries in CAT(0) rectangular complexes and two of theirs subclasses, ramified rectilinear polygons (CAT(0) rectangular complexes in which the links of all vertices are bipartite graphs) and squaregraphs (CAT(0) rectangular complexes arising from plane quadrangulations in which all inner vertices have degrees \geq4). Namely, we show that for a CAT(0) rectangular complex K with n vertices, one can construct a data structure D of size $O(n^2)$ so that, given any two points x,y in K, the shortest path {\gamma}(x,y) between x and y can be computed in O(d(p,q)) time, where p and q are vertices of two faces of K containing the points x and y, respectively, such that {\gamma}(x,y) is contained in K(I(p,q)) and d(p,q) is the distance between p and q in the underlying graph of K. If K is a ramified rectilinear polygon, then one can construct a data structure D of optimal size O(n) and answer two-point shortest path queries in O(d(p,q)log{\Delta}) time, where {\Delta} is the maximal degree of a vertex of G(K). Finally, if K is a squaregraph, then one can construct a data structure D of size O(nlogn) and answer two-point shortest path queries in O(d(p,q)) time.


A Platform-independent Programming Environment for Robot Control

Abstract: The development of robot control programs is a complex task. Many robots are different in their electrical and mechanical structure which is also reflected in the software. Specific robot software environments support the program development, but are mainly text-based and usually applied by experts in the field with profound knowledge of the target robot. This paper presents a graphical programming environment which aims to ease the development of robot control programs. In contrast to existing graphical robot programming environments, our approach focuses on the composition of parallel action sequences. The developed environment allows to schedule independent robot actions on parallel execution lines and provides mechanism to avoid side-effects of parallel actions. The developed environment is platform-independent and based on the model-driven paradigm. The feasibility of our approach is shown by the application of the sequencer to a simulated service robot and a robot for educational purpose.


Improved Methods For Generating Quasi-Gray Codes

Abstract: Consider a sequence of bit strings of length d, such that each string differs from the next in a constant number of bits. We call this sequence a quasi-Gray code. We examine the problem of efficiently generating such codes, by considering the number of bits read and written at each generating step, the average number of bits read while generating the entire code, and the number of strings generated in the code. Our results give a trade-off between these constraints, and present algorithms that do less work on average than previous results, and that increase the number of bit strings generated.


Preserving Privacy in Sequential Data Release against Background Knowledge Attacks

Abstract: A large amount of transaction data containing associations between individuals and sensitive information flows everyday into data stores. Examples include web queries, credit card transactions, medical exam records, transit database records. The serial release of these data to partner institutions or data analysis centers is a common situation. In this paper we show that, in most domains, correlations among sensitive values associated to the same individuals in different releases can be easily mined, and used to violate users' privacy by adversaries observing multiple data releases. We provide a formal model for privacy attacks based on this sequential background knowledge, as well as on background knowledge on the probability distribution of sensitive values over different individuals. We show how sequential background knowledge can be actually obtained by an adversary, and used to identify with high confidence the sensitive values associated with an individual. A defense algorithm based on Jensen-Shannon divergence is proposed, and extensive experiments show the superiority of the proposed technique with respect to other applicable solutions. To the best of our knowledge, this is the first work that systematically investigates the role of sequential background knowledge in serial release of transaction data.


Reconstruction of Aggregation Tree in spite of Faulty Nodes in Wireless Sensor Networks

Abstract: Recent advances in wireless sensor networks (WSNs) have led to many new promissing applications. However data communication between nodes consumes a large portion of the total energy of WSNs. Consequently efficient data aggregation technique can help greatly to reduce power consumption. Data aggregation has emerged as a basic approach in WSNs in order to reduce the number of transmissions of sensor nodes over {\it aggregation tree} and hence minimizing the overall power consumption in the network. If a sensor node fails during data aggregation then the aggregation tree is disconnected. Hence the WSNs rely on in-network aggregation for efficiency but a single faulty node can severely influence the outcome by contributing an arbitrary partial aggregate value. In this paper we have presented a distributed algorithm that reconstruct the aggregation tree from the initial aggregation tree excluding the faulty sensor node. This is a synchronous model that is completed in several rounds. Our proposed scheme can handle multiple number of faulty nodes as well.


Un Algorithme g\'en\'etique pour le probl\`eme de ramassage et de livraison avec fen\^etres de temps \`a plusieurs v\'ehicules

Abstract: The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for optimization of a multi pickup and delivery problem with time windows (m-PDPTW). We purposes a brief literature review of the PDPTW, present an approach based on genetic algorithms to give a satisfying solution to the m-PDPTW minimizing the total travel cost.


Approche Multicrit\`ere pour le Probl\`eme de Ramassage et de Livraison avec Fen\^etres de Temps \`a Plusieurs V\'ehicules

Abstract: Nowadays, the transport goods problem occupies an important place in the economic life of modern societies. The pickup and delivery problem with time windows (PDPTW) is one of the problems which a large part of the research was interested. In this paper, we present a a brief literature review of the VRP and the PDPTW, propose our multicriteria approach based on genetic algorithms which allows minimize the compromise between the vehicles number, the total tardiness time and the total travel cost. And this, by treating the case where a customer can have multiple suppliers and one supplier can have multiple customers


Astronomy in the Cloud: Using MapReduce for Image Coaddition

Abstract: In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection and classification, and moving object tracking. Since such studies benefit from the highest quality data, methods such as image coaddition (stacking) will be a critical preprocessing step prior to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources or transient objects, these data streams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, e.g., Amazon's EC2. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results comparing their performance.


Cut-Matching Games on Directed Graphs

Abstract: We give O(log^2 n)-approximation algorithm based on the cut-matching framework of [10, 13, 14] for computing the sparsest cut on directed graphs. Our algorithm uses only O(log^2 n) single commodity max-flow computations and thus breaks the multicommodity-flow barrier for computing the sparsest cut on directed graphs


An Explicit Framework for Interaction Nets

Abstract: Interaction nets are a graphical formalism inspired by Linear Logic proof-nets often used for studying higher order rewriting e.g. \Beta-reduction. Traditional presentations of interaction nets are based on graph theory and rely on elementary properties of graph theory. We give here a more explicit presentation based on notions borrowed from Girard's Geometry of Interaction: interaction nets are presented as partial permutations and a composition of nets, the gluing, is derived from the execution formula. We then define contexts and reduction as the context closure of rules. We prove strong confluence of the reduction within our framework and show how interaction nets can be viewed as the quotient of some generalized proof-nets.


Faster Polynomial Multiplication via Discrete Fourier Transforms

Abstract: We study the complexity of polynomial multiplication over arbitrary fields. We present a unified approach that generalizes all known asymptotically fastest algorithms for this problem. In particular, the well-known algorithm for multiplication of polynomials over fields supporting DFTs of large smooth orders, Sch\"onhage-Strassen's algorithm over arbitrary fields of characteristic different from 2, Sch\"onhage's algorithm over fields of characteristic 2, and Cantor-Kaltofen's algorithm over arbitrary algebras---all appear to be instances of this approach. We also obtain faster algorithms for polynomial multiplication over certain fields which do not support DFTs of large smooth orders. We prove that the Sch\"onhage-Strassen's upper bound cannot be improved further over the field of rational numbers if we consider only algorithms based on consecutive applications of DFT, as all known fastest algorithms are. We also explore the ways to transfer the recent F\"urer's algorithm for integer multiplication to the problem of polynomial multiplication over arbitrary fields of positive characteristic. This work is inspired by the recent improvement for the closely related problem of complexity of integer multiplication by F\"urer and its consequent modular arithmetic treatment due to De, Kurur, Saha, and Saptharishi. We explore the barriers in transferring the techniques for solutions of one problem to a solution of the other.


Deterministic and Energy-Optimal Wireless Synchronization

Abstract: We consider the problem of clock synchronization in a wireless setting where processors must power-down their radios in order to save energy. Energy efficiency is a central goal in wireless networks, especially if energy resources are severely limited. In the current setting, the problem is to synchronize clocks of $m$ processors that wake up in arbitrary time points, such that the maximum difference between wake up times is bounded by a positive integer $n$, where time intervals are appropriately discretized. Currently, the best-known results for synchronization for single-hop networks of $m$ processors is a randomized algorithm due to \cite{BKO09} of O(\sqrt {n /m} \cdot poly-log(n)) awake times per processor and a lower bound of Omega(\sqrt{n/m}) of the number of awake times needed per processor \cite{BKO09}. The main open question left in their work is to close the poly-log gap between the upper and the lower bound and to de-randomize their probabilistic construction and eliminate error probability. This is exactly what we do in this paper. That is, we show a {deterministic} algorithm with radio use of Theta(\sqrt {n /m}) that never fails. We stress that our upper bound exactly matches the lower bound proven in \cite{BKO09}, up to a small multiplicative constant. Therefore, our algorithm is {optimal} in terms of energy efficiency and completely resolves a long sequence of works in this area. In order to achieve these results we devise a novel {adaptive} technique that determines the times when devices power their radios on and off. In addition, we prove several lower bounds on the energy efficiency of algorithms for {multi-hop networks}. Specifically, we show that any algorithm for multi-hop networks must have radio use of Omega(\sqrt n) per processor.


A Path Order for Rewrite Systems that Compute Exponential Time Functions (Technical Report)

Abstract: In this paper we present a new path order for rewrite systems, the exponential path order EPOSTAR. Suppose a term rewrite system is compatible with EPOSTAR, then the runtime complexity of this rewrite system is bounded from above by an exponential function. Furthermore, the class of function computed by a rewrite system compatible with EPOSTAR equals the class of functions computable in exponential time on a Turing maschine.


Temporal Logics on Words with Multiple Data Values

Abstract: The paper proposes and studies temporal logics for attributed words, that is, data words with a (finite) set of (attribute,value)-pairs at each position. It considers a basic logic which is a semantical fragment of the logic $LTL^\downarrow_1$ of Demri and Lazic with operators for navigation into the future and the past. By reduction to the emptiness problem for data automata it is shown that this basic logic is decidable. Whereas the basic logic only allows navigation to positions where a fixed data value occurs, extensions are studied that also allow navigation to positions with different data values. Besides some undecidable results it is shown that the extension by a certain UNTIL-operator with an inequality target condition remains decidable.


XML Query Processing and Query Languges: A Survey

Abstract: Today's database is associated with interoperability between different domains and applications. This consequently results in the importance of data portability in database. XML format fits the requirements and it has been increasingly used for serving applications across different domains and purposes. However, querying XML document effectively and efficiently is still a challenging issue. This paper discusses query processing issues on XML and reviews proposed solutions for querying XML databases by various authors.


LR(1) Parser Generation System: LR(1) Error Recovery, Oracles, and Generic Tokens

Abstract: The LR(1) Parser Generation System generates full LR(1) parsers that are comparable in speed and size to those generated by LALR(1) parser generators, such as yacc [5]. LR contains a number of novel feature. This paper discusses three of them in detail: an LR(1) grammar specified automatic error recovery algorithm, oracles, and generic tokens.


Searching in Dynamic Tree-Like Partial Orders

Abstract: We give the first data structure for the problem of maintaining a dynamic set of n elements drawn from a partially ordered universe described by a tree. We define the Line-Leaf Tree, a linear-sized data structure that supports the operations: insert; delete; test membership; and predecessor. The performance of our data structure is within an O(log w)-factor of optimal. Here w <= n is the width of the partial-order---a natural obstacle in searching a partial order.


Hitting forbidden minors: Approximation and Kernelization

Abstract: We study a general class of problems called F-deletion problems. In an F-deletion problem, we are asked whether a subset of at most $k$ vertices can be deleted from a graph $G$ such that the resulting graph does not contain as a minor any graph from the family F of forbidden minors. We obtain a number of algorithmic results on the F-deletion problem when F contains a planar graph. We give (1) a linear vertex kernel on graphs excluding $t$-claw $K_{1,t}$, the star with $t$ leves, as an induced subgraph, where $t$ is a fixed integer. (2) an approximation algorithm achieving an approximation ratio of $O(\log^{3/2} OPT)$, where $OPT$ is the size of an optimal solution on general undirected graphs. Finally, we obtain polynomial kernels for the case when F contains graph $\theta_c$ as a minor for a fixed integer $c$. The graph $\theta_c$ consists of two vertices connected by $c$ parallel edges. Even though this may appear to be a very restricted class of problems it already encompasses well-studied problems such as {\sc Vertex Cover}, {\sc Feedback Vertex Set} and Diamond Hitting Set. The generic kernelization algorithm is based on a non-trivial application of protrusion techniques, previously used only for problems on topological graph classes.


Optimizing Monotone Functions Can Be Difficult

Abstract: Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotone. Contrary to what one would expect, not all of these functions are easy to optimize. The choice of the constant $c$ in the mutation probability $p(n) = c/n$ can make a decisive difference. We show that if $c < 1$, then the (1+1) evolutionary algorithm finds the optimum of every such function in $\Theta(n \log n)$ iterations. For $c=1$, we can still prove an upper bound of $O(n^{3/2})$. However, for $c > 33$, we present a strictly monotone function such that the (1+1) evolutionary algorithm with overwhelming probability does not find the optimum within $2^{\Omega(n)}$ iterations. This is the first time that we observe that a constant factor change of the mutation probability changes the run-time by more than constant factors.


A Hybrid Parallelization of AIM for Multi-Core Clusters: Implementation Details and Benchmark Results on Ranger

Abstract: This paper presents implementation details and empirical results for a hybrid message passing and shared memory paralleliziation of the adaptive integral method (AIM). AIM is implemented on a (near) petaflop supercomputing cluster of quad-core processors and its accuracy, complexity, and scalability are investigated by solving benchmark scattering problems. The timing and speedup results on up to 1024 processors show that the hybrid MPI/OpenMP parallelization of AIM exhibits better strong scalability (fixed problem size speedup) than pure MPI parallelization of it when multiple cores are used on each processor.


A Simple Deterministic Reduction for the Gap Minimum Distance of Code Problem

Abstract: We present a simple deterministic gap-preserving reduction from SAT to the Minimum Distance of Code Problem over $\F_2$. We also show how to extend the reduction to work over any finite field. Previously a randomized reduction was known due to Dumer, Micciancio, and Sudan, which was recently derandomized by Cheng and Wan. These reductions rely on highly non-trivial coding theoretic constructions whereas our reduction is elementary. As an additional feature, our reduction gives a constant factor hardness even for asymptotically good codes, i.e., having constant rate and relative distance. Previously it was not known how to achieve deterministic reductions for such codes.


Profile Based Sub-Image Search in Image Databases

Abstract: Sub-image search with high accuracy in natural images still remains a challenging problem. This paper proposes a new feature vector called profile for a keypoint in a bag of visual words model of an image. The profile of a keypoint captures the spatial geometry of all the other keypoints in an image with respect to itself, and is very effective in discriminating true matches from false matches. Sub-image search using profiles is a single-phase process requiring no geometric validation, yields high precision on natural images, and works well on small visual codebook. The proposed search technique differs from traditional methods that first generate a set of candidates disregarding spatial information and then verify them geometrically. Conventional methods also use large codebooks. We achieve a precision of 81% on a combined data set of synthetic and real natural images using a codebook size of 500 for top-10 queries; that is 31% higher than the conventional candidate generation approach.


Real-Time Multi-path Tracking of Probabilistic Available Bandwidth

Abstract: Applications such as traffic engineering and network provisioning can greatly benefit from knowing, in real time, what is the largest input rate at which it is possible to transmit on a given path without causing congestion. We consider a probabilistic formulation for available bandwidth where the user specifies the probability of achieving an output rate almost as large as the input rate. We are interested in estimating and tracking the network-wide probabilistic available bandwidth (PAB) on multiple paths simultaneously with minimal overhead on the network. We propose a novel framework based on chirps, Bayesian inference, belief propagation and active sampling to estimate the PAB. We also consider the time evolution of the PAB by forming a dynamic model and designing a tracking algorithm based on particle filters. We implement our method in a lightweight and practical tool that has been deployed on the PlanetLab network to do online experiments. We show through these experiments and simulations that our approach outperforms block-based algorithms in terms of input rate cost and probability of successful transmission.


Time Series Classification by Class-Specific Mahalanobis Distance Measures

Abstract: To classify time series by nearest neighbors, we need to specify or learn one or several distance measures. We consider variations of the Mahalanobis distance measures which rely on the inverse covariance matrix of the data. Unfortunately --- for time series data --- the covariance matrix has often low rank. To alleviate this problem we can either use a pseudoinverse, covariance shrinking or limit the matrix to its diagonal. We review these alternatives and benchmark them against competitive methods such as the related Large Margin Nearest Neighbor Classification (LMNN) and the Dynamic Time Warping (DTW) distance. As we expected, we find that the DTW is superior, but the Mahalanobis distance measures are one to two orders of magnitude faster. To get best results with Mahalanobis distance measures, we recommend learning one distance measure per class using either covariance shrinking or the diagonal approach.


Multi Layer Approach to Defend DDoS Attacks Caused by Spam

Abstract: Corporate mail services are designed to perform better than public mail services. Fast mail delivery, large size file transfer as an attachments, high level spam and virus protection, commercial advertisement free environment are some of the advantages worth to mention. But these mail services are frequent target of hackers and spammers. Distributed Denial of service attacks are becoming more common and sophisticated. The researchers have proposed various solutions to the DDOS attacks. Can we stop these kinds of attacks with available technology? These days the DDoS attack through spam has increased and disturbed the mail services of various organizations. Spam penetrates through all the filters to establish DDoS attacks, which causes serious problems to users and the data. In this paper we propose a multilayer approach to defend DDoS attack caused by spam mails. This approach is a combination of fine tuning of source filters, content filters, strictly implementing mail policies, educating user, network monitoring and logical solutions to the ongoing attack. We have conducted several experiments in corporate mail services; the results show that this approach is highly effective to prevent DDoS attack caused by spam. The defense mechanism reduced 60% of the incoming spam traffic and repelled many DDoS attacks caused by spam


Automatic Verification of Parametric Specifications with Complex Topologies

Abstract: The focus of this paper is on reducing the complexity in verification by exploiting modularity at various levels: in specification, in verification, and structurally. For specifications, we use the modular language CSP-OZ-DC, which allows us to decouple verification tasks concerning data from those concerning durations. At the verification level, we exploit modularity in theorem proving for rich data structures and use this for invariant checking. At the structural level, we analyze possibilities for modular verification of systems consisting of various components which interact.We illustrate these ideas by automatically verifying safety properties of a case study from the European Train Control System standard, which extends previous examples by comprising a complex track topology with lists of track segments and trains with different routes.


Certifying cost annotations in compilers

Abstract: We discuss the problem of building a compiler which can lift in a provably correct way pieces of information on the execution cost of the object code to cost annotations on the source code. To this end, we need a clear and flexible picture of: (i) the meaning of cost annotations, (ii) the method to prove them sound and precise, and (iii) the way such proofs can be composed. We propose a so-called labelling approach to these three questions. As a first step, we examine its application to a toy compiler. This formal study suggests that the labelling approach has good compositionality and scalability properties. In order to provide further evidence for this claim, we report our successful experience in implementing and testing the labelling approach on top of a prototype compiler written in OCAML for (a large fragment of) the C language.


Mapping XML Data to Relational Data: A DOM-Based Approach

Abstract: XML has emerged as the standard for representing and exchanging data on the World Wide Web. It is critical to have efficient mechanisms to store and query XML data to exploit the full power of this new technology. Several researchers have proposed to use relational databases to store and query XML data. While several algorithms of schema mapping and query mapping have been proposed, the problem of mapping XML data to relational data, i.e., mapping an XML INSERT statement to a sequence of SQL INSERT statements, has not been addressed thoroughly in the literature. In this paper, we propose an efficient linear algorithm for mapping XML data to relational data. This algorithm is based on our previous proposed inlining algorithm for mapping DTDs to relational schemas and can be easily adapted to other inlining algorithms.


Algorithms for nonnegative matrix factorization with the beta-divergence

Abstract: This paper describes algorithms for nonnegative matrix factorization (NMF) with the beta-divergence (beta-NMF). The beta-divergence is a family of cost functions parametrized by a single shape parameter beta that takes the Euclidean distance, the Kullback-Leibler divergence and the Itakura-Saito divergence as special cases (beta = 2,1,0, respectively). The proposed algorithms are based on a surrogate auxiliary function (a local majorization of the criterion function). We first describe a majorization-minimization (MM) algorithm that leads to multiplicative updates, which differ from standard heuristic multiplicative updates by a beta-dependent power exponent. The monotonicity of the heuristic algorithm can however be proven for beta in (0,1) using the proposed auxiliary function. Then we introduce the concept of majorization-equalization (ME) algorithm which produces updates that move along constant level sets of the auxiliary function and lead to larger steps than MM. Simulations on synthetic and real data illustrate the faster convergence of the ME approach. The paper also describes how the proposed algorithms can be adapted to two common variants of NMF : penalized NMF (i.e., when a penalty function of the factors is added to the criterion function) and convex-NMF (when the dictionary is assumed to belong to a known subspace).


Improved complexity bounds for real root isolation using Continued Fractions

Abstract: We consider the problem of isolating the real roots of a square-free polynomial with integer coefficients using (variants of) the continued fraction algorithm (CF). We introduce a novel way to compute a lower bound on the positive real roots of univariate polynomials. This allows us to derive a worst case bound of $\sOB(d^6 + d^4\tau^2 + d^3\tau^2)$ for isolating the real roots of a polynomial with integer coefficients using the classic variant of CF, where $d$ is the degree of the polynomial and $\tau$ the maximum bitsize of its coefficients. This improves the previous bound by Sharma \cite{sharma-tcs-2008} by a factor of $d^3$ and matches the bound derived by Mehlhorn and Ray \cite{mr-jsc-2009} for another variant of CF; it also matches the worst case bound of the subdivision-based solvers. We present a new variant of CF, we call it iCF, that isolates the real roots of a polynomial with integer coefficients in $\sOB(d^5+d^4\tau)$, thus improving the current known bound for the problem by a factor of $d$. If the polynomial has only real roots, then our bound becomes $\sOB(d^4+d^3\tau+ d^2\tau^2)$, thus matching the bound of the numerical algorithms by Reif \cite{r-focs-1993} and by Ben-Or and Tiwari \cite{bt-joc-1990}. Actually the latter bound holds in a more general setting, that is under the rather mild assumption that $\Omega(d/\lg^c{d})$, where $c\geq 0$ is a constant, roots contribute to the sign variations of the coefficient list of the polynomial. This is the only bound on exact algorithms that matches the one of the numerical algorithms by Pan \cite{Pan02jsc} and Sch\"onhage \cite{Sch82}. To our knowledge the presented bounds are the best known for the problem of real root isolation for algorithms based on exact computations.


Modified Bully Algorithm using Election Commission

Abstract: Electing leader is a vital issue not only in distributed computing but also in communication network [1, 2, 3, 4, 5], centralized mutual exclusion algorithm [6, 7], centralized control IPC, etc. A leader is required to make synchronization between different processes. And different election algorithms are used to elect a coordinator among the available processes in the system such a way that there will be only one coordinator at any time. Bully election algorithm is one of the classical and well-known approaches in coordinator election process. This paper will present a modified version of bully election algorithm using a new concept called election commission. This approach will not only reduce redundant elections but also minimize total number of elections and hence it will minimize message passing, network traffic, and complexity of the existing system.


Implications of Inter-Rater Agreement on a Student Information Retrieval Evaluation

Abstract: This paper is about an information retrieval evaluation on three different retrieval-supporting services. All three services were designed to compensate typical problems that arise in metadata-driven Digital Libraries, which are not adequately handled by a simple tf-idf based retrieval. The services are: (1) a co-word analysis based query expansion mechanism and re-ranking via (2) Bradfordizing and (3) author centrality. The services are evaluated with relevance assessments conducted by 73 information science students. Since the students are neither information professionals nor domain experts the question of inter-rater agreement is taken into consideration. Two important implications emerge: (1) the inter-rater agreement rates were mainly fair to moderate and (2) after a data-cleaning step which erased the assessments with poor agreement rates the evaluation data shows that the three retrieval services returned disjoint but still relevant result sets.


A probabilistic top-down parser for minimalist grammars

Abstract: This paper describes a probabilistic top-down parser for minimalist grammars. Top-down parsers have the great advantage of having a certain predictive power during the parsing, which takes place in a left-to-right reading of the sentence. Such parsers have already been well-implemented and studied in the case of Context-Free Grammars, which are already top-down, but these are difficult to adapt to Minimalist Grammars, which generate sentences bottom-up. I propose here a way of rewriting Minimalist Grammars as Linear Context-Free Rewriting Systems, allowing to easily create a top-down parser. This rewriting allows also to put a probabilistic field on these grammars, which can be used to accelerate the parser. Finally, I propose a method of refining the probabilistic field by using algorithms used in data compression.


Backward Reachability of Array-based Systems by SMT solving: Termination and Invariant Synthesis

Abstract: The safety of infinite state systems can be checked by a backward reachability procedure. For certain classes of systems, it is possible to prove the termination of the procedure and hence conclude the decidability of the safety problem. Although backward reachability is property-directed, it can unnecessarily explore (large) portions of the state space of a system which are not required to verify the safety property under consideration. To avoid this, invariants can be used to dramatically prune the search space. Indeed, the problem is to guess such appropriate invariants. In this paper, we present a fully declarative and symbolic approach to the mechanization of backward reachability of infinite state systems manipulating arrays by Satisfiability Modulo Theories solving. Theories are used to specify the topology and the data manipulated by the system. We identify sufficient conditions on the theories to ensure the termination of backward reachability and we show the completeness of a method for invariant synthesis (obtained as the dual of backward reachability), again, under suitable hypotheses on the theories. We also present a pragmatic approach to interleave invariant synthesis and backward reachability so that a fix-point for the set of backward reachable states is more easily obtained. Finally, we discuss heuristics that allow us to derive an implementation of the techniques in the model checker MCMT, showing remarkable speed-ups on a significant set of safety problems extracted from a variety of sources.


Inner Product Spaces for MinSum Coordination Mechanisms

Abstract: We study policies aiming to minimize the weighted sum of completion times of jobs in the context of coordination mechanisms for selfish scheduling problems. Our goal is to design local policies that achieve a good price of anarchy in the resulting equilibria for unrelated machine scheduling. To obtain the approximation bounds, we introduce a new technique that while conceptually simple, seems to be quite powerful. With this method we are able to prove the following results. First, we consider Smith's Rule, which orders the jobs on a machine in ascending processing time to weight ratio, and show that it achieves an approximation ratio of 4. We also demonstrate that this is the best possible for deterministic non-preemptive strongly local policies. Since Smith's Rule is always optimal for a given assignment, this may seem unsurprising, but we then show that better approximation ratios can be obtained if either preemption or randomization is allowed. We prove that ProportionalSharing, a preemptive strongly local policy, achieves an approximation ratio of 2.618 for the weighted sum of completion times, and an approximation ratio of 2.5 in the unweighted case. Again, we observe that these bounds are tight. Next, we consider Rand, a natural non-preemptive but randomized policy. We show that it achieves an approximation ratio of at most 2.13; moreover, if the sum of the weighted completion times is negligible compared to the cost of the optimal solution, this improves to \pi /2. Finally, we show that both ProportionalSharing and Rand induce potential games, and thus always have a pure Nash equilibrium (unlike Smith's Rule). This also allows us to design the first \emph{combinatorial} constant-factor approximation algorithm minimizing weighted completion time for unrelated machine scheduling that achieves a factor of 2+ \epsilon for any \epsilon > 0.


Multi-Objective Genetic Programming Projection Pursuit for Exploratory Data Modeling

Abstract: For classification problems, feature extraction is a crucial process which aims to find a suitable data representation that increases the performance of the machine learning algorithm. According to the curse of dimensionality theorem, the number of samples needed for a classification task increases exponentially as the number of dimensions (variables, features) increases. On the other hand, it is costly to collect, store and process data. Moreover, irrelevant and redundant features might hinder classifier performance. In exploratory analysis settings, high dimensionality prevents the users from exploring the data visually. Feature extraction is a two-step process: feature construction and feature selection. Feature construction creates new features based on the original features and feature selection is the process of selecting the best features as in filter, wrapper and embedded methods. In this work, we focus on feature construction methods that aim to decrease data dimensionality for visualization tasks. Various linear (such as principal components analysis (PCA), multiple discriminants analysis (MDA), exploratory projection pursuit) and non-linear (such as multidimensional scaling (MDS), manifold learning, kernel PCA/LDA, evolutionary constructive induction) techniques have been proposed for dimensionality reduction. Our algorithm is an adaptive feature extraction method which consists of evolutionary constructive induction for feature construction and a hybrid filter/wrapper method for feature selection.


Weighted Indices for Evaluating the Quality of Research with Multiple Authorship

Abstract: Devising an index to measure the quality of research is a challenging task. In this paper, we propose a set of indices to evaluate the quality of research produced by an author. Our indices utilize a policy that assigns the weights to multiple authors of a paper. We have considered two weight assignment policies: positionally weighted and equally weighted. We propose two classes of weighted indices: weighted h-indices and weighted citation h-cuts. Further, we compare our weighted h-indices with the original h-index for a selected set of authors. As opposed to h-index, our weighted h-indices take into account the weighted contributions of individual authors in multi-authored papers, and may serve as an improvement over h-index. The other class of weighted indices that we call weighted citation h-cuts take into account the number of citations that are in excess of those required to compute the index, and may serve as a supplement to h-index or its variants.


New Frontiers of Network Security: The Threat Within

Abstract: Nearly 70% of information security threats originate from inside an organization. Opportunities for insider threats have been increasing at an alarming rate with the latest trends of mobility (portable devices like Laptop, smart phones etc.), ubiquitous connectivity (wireless or through 3G connectivity) and this trend increases as more and more web-based applications are made available over the Internet. Insider threats are generally caused by current or ex-employees, contractors or partners, who have authorized access to the organization's network and servers. Theft of confidential information is often for either material gain or for willful damage. Easy availability of hacking tools on the Internet, USB devices and wireless connectivity provide for easy break-ins. The net result is losses worth millions of dollars in terms of IP theft, leakage of customer / individual information, etc. This paper presents an understanding of Insider threats, attackers and their motives and suggests mitigation techniques at the organization level


Submodular problems - approximations and algorithms

Abstract: We show that any submodular minimization (SM) problem defined on a linear constraint set with constraints having up to two variables per inequality, are 2-approximable in polynomial time. If the constraints are monotone (the two variables appear with opposite sign coefficients) then the problems of submodular minimization or supermodular maximization are polynomial time solvable. The key idea is to link these problems to a submodular s,t-cut problem defined here. This framework includes the problems: SM-vertex cover; SM-2SAT; SM-min satisfiability; SM-edge deletion for clique, SM-node deletion for biclique and others. We also introduce here the submodular closure problem and and show that it is solvable in polynomial time and equivalent to the submodular cut problem. All the results are extendible to multi-sets where each element of a set may appear with a multiplicity greater than 1. For all these NP-hard problems 2-approximations are the best possible in the sense that a better approximation factor cannot be achieved in polynomial time unless NP=P. The mechanism creates a relaxed "monotone" problem, solved as a submodular closure problem, the solution to which is mapped to a half integral super-optimal solution to the original problem. That half-integral solution has the persistency property meaning that integer valued variables retain their value in an optimal solution. This permits to delete the integer valued variables, and restrict the search of an optimal solution to the smaller set of remaining variables.


Transdichotomous Results in Computational Geometry, II: Offline Search

Abstract: We reexamine fundamental problems from computational geometry in the word RAM model, where input coordinates are integers that fit in a machine word. We develop a new algorithm for offline point location, a two-dimensional analog of sorting where one needs to order points with respect to segments. This result implies, for example, that the convex hull of n points in three dimensions can be constructed in (randomized) time n 2^O(sqrt{lglg n}). Similar bounds hold for numerous other geometric problems, such as planar Voronoi diagrams, planar off-line nearest neighbor search, line segment intersection, and triangulation of non-simple polygons. In FOCS'06, we developed a data structure for online point location, which implied a bound of O(n lg n/lglg n) for three-dimensional convex hulls and the other problems. Our current bounds are dramatically better, and a convincing improvement over the classic O(nlg n) algorithms. As in the field of integer sorting, the main challenge is to find ways to manipulate information, while avoiding the online problem (in that case, predecessor search).


A Critical Path Approach to Analyzing Parallelism of Algorithmic Variants. Application to Cholesky Inversion

Abstract: Algorithms come with multiple variants which are obtained by changing the mathematical approach from which the algorithm is derived. These variants offer a wide spectrum of performance when implemented on a multicore platform and we seek to understand these differences in performances from a theoretical point of view. To that aim, we derive and present the critical path lengths of each algorithmic variant for our application problem which enables us to determine a lower bound on the time to solution. This metric provides an intuitive grasp of the performance of a variant and we present numerical experiments to validate the tightness of our lower bounds on practical applications. Our case study is the Cholesky inversion and its use in computing the inverse of a symmetric positive definite matrix.


Abstract: We consider the problem of isolating the real roots of a square-free polynomial with integer coefficients using (variants of) the continued fraction algorithm (CF). We introduce a novel way to compute a lower bound on the positive real roots of univariate polynomials. This allows us to derive a worst case bound of $\sOB(d^6 + d^4\tau^2 + d^3\tau^2)$ for isolating the real roots of a polynomial with integer coefficients using the classic variant \cite{Akritas:implementation} of CF, where $d$ is the degree of the polynomial and $\tau$ the maximum bitsize of its coefficients. This improves the previous bound of Sharma \cite{sharma-tcs-2008} by a factor of $d^3$ and matches the bound derived by Mehlhorn and Ray \cite{mr-jsc-2009} for another variant of CF; it also matches the worst case bound of the subdivision-based solvers.


Hierarchical Multiclass Decompositions with Application to Authorship Determination

Abstract: This paper is mainly concerned with the question of how to decompose multiclass classification problems into binary subproblems. We extend known Jensen-Shannon bounds on the Bayes risk of binary problems to hierarchical multiclass problems and use these bounds to develop a heuristic procedure for constructing hierarchical multiclass decomposition for multinomials. We test our method and compare it to the well known "all-pairs" decomposition. Our tests are performed using a new authorship determination benchmark test of machine learning authors. The new method consistently outperforms the all-pairs decomposition when the number of classes is small and breaks even on larger multiclass problems. Using both methods, the classification accuracy we achieve, using an SVM over a feature set consisting of both high frequency single tokens and high frequency token-pairs, appears to be exceptionally high compared to known results in authorship determination.


Parameter Selection in Periodic Nonuniform Sampling of Multiband Signals

Abstract: Periodic nonuniform sampling has been considered in literature as an effective approach to reduce the sampling rate far below the Nyquist rate for sparse spectrum multiband signals. In the presence of non-ideality the sampling parameters play an important role on the quality of reconstructed signal. Also the average sampling ratio is directly dependent on the sampling parameters that they should be chosen for a minimum rate and complexity. In this paper we consider the effect of sampling parameters on the reconstruction error and the sampling ratio and suggest feasible approaches for achieving an optimal sampling and reconstruction.


Combiner suivi de l'activite? et partage d'exp\'eriences en apprentissage par projet pour les acteurs tuteurs et apprenants

Abstract: Our work aims to study tools offered to students and tutors involved in face-to-face or blended project- based learning activities. Project-based learning is often applied in the case of complex learning (i.e. which aims at making learners acquire various linked skills or develop their behaviours). In comparison to traditional learning, this type of learning relies on co-development, collective responsibility and co-operation. Learners are the principal actors of their learning. These trainings rest on rich and complex organizations, particularly for tutors, and it is difficult to apply innovative educational strategies. Our aim, in a bottom-up approach, is (1) to observe, according to Knowledge Management methods, a course characterized by these three criteria. The observed course concerns project management learning. Its observation allows us (2) to highlight and to analyze the problems encountered by the actors (students, tutors, designers) and (3) to propose tools to solve or improve them. We particularly study the relevance and the limits of the existing monitoring and experience sharing tools. We finally propose a result in the form of the tool MEShaT (Monitoring and Experience Sharing Tool) and end on the perspectives offered by these researches.


Ontological Matchmaking in Recommender Systems

Abstract: The electronic marketplace offers great potential for the recommendation of supplies. In the so called recommender systems, it is crucial to apply matchmaking strategies that faithfully satisfy the predicates specified in the demand, and take into account as much as possible the user preferences. We focus on real-life ontology-driven matchmaking scenarios and identify a number of challenges, being inspired by such scenarios. A key challenge is that of presenting the results to the users in an understandable and clear-cut fashion in order to facilitate the analysis of the results. Indeed, such scenarios evoke the opportunity to rank and group the results according to specific criteria. A further challenge consists of presenting the results to the user in an asynchronous fashion, i.e. the 'push' mode, along with the 'pull' mode, in which the user explicitly issues a query, and displays the results. Moreover, an important issue to consider in real-life cases is the possibility of submitting a query to multiple providers, and collecting the various results. We have designed and implemented an ontology-based matchmaking system that suitably addresses the above challenges. We have conducted a comprehensive experimental study, in order to investigate the usability of the system, the performance and the effectiveness of the matchmaking strategies with real ontological datasets.


Optimizing real world applications with GCC Link Time Optimization

Abstract: GCC has a new infrastructure to support a link time optimization (LTO). The infrastructure is designed to allow linking of large applications using a special mode (WHOPR) which support parallelization of the compilation process. In this paper we present overview of the design and implementation of WHOPR and present test results of its behavior when optimizing large applications. We give numbers on compile time, memory usage and code quality comparisons to the classical file by file based optimization model. In particular we focus on Firefox web browser. We show main problems seen only when compiling a large application, such as startup time and code size growth.


Abstraction for Epistemic Model Checking of Dining Cryptographers-based Protocols

Abstract: The paper describes an abstraction for protocols that are based on multiple rounds of Chaum's Dining Cryptographers protocol. It is proved that the abstraction preserves a rich class of specifications in the logic of knowledge, including specifications describing what an agent knows about other agents' knowledge. This result can be used to optimize model checking of Dining Cryptographers-based protocols, and applied within a methodology for knowledge-based program implementation and verification. Some case studies of such an application are given, for a protocol that uses the Dining Cryptographers protocol as a primitive in an anonymous broadcast system. Performance results are given for model checking knowledge-based specifications in the concrete and abstract models of this protocol, and some new conclusions about the protocol are derived.


Proceedings International Workshop on Component and Service Interoperability

Abstract: This volume contains the proceedings of WCSI 2010, the International Workshop on Component and Service Interoperability. WCSI 2010 was held in Malaga (Spain) on June 29th, 2010 as a satellite event of the TOOLS 2010 Federated Conferences. The papers published in this volume tackle different issues that are currently central to our community, namely definition of expressive interface languages, formal models and approaches to software composition and adaptation, interface-based compatibility and substitutability, and verification techniques for distributed software.


Using Context Dependent Semantic Similarity to Browse Information Resources: an Application for the Industrial Design

Abstract: This paper deals with the semantic interpretation of information resources (e.g., images, videos, 3D models). We present a case study of an approach based on semantic and context dependent similarity applied to the industrial design. Different application contexts are considered and modelled to browse a repository of 3D digital objects according to different perspectives. The paper briefly summarises the basic concepts behind the semantic similarity approach and illustrates its application and results.


Predicting Coding Effort in Projects Containing XML Code

Abstract: This paper studies the problem of predicting the coding effort for a subsequent year of development by analysing metrics extracted from project repositories, with an emphasis on projects containing XML code. The study considers thirteen open source projects and applies machine learning algorithms to generate models to predict one-year coding effort, measured in terms of lines of code added, modified and deleted. Both organisational and code metrics associated to revisions are taken into account. The results show that coding effort is highly determined by the expertise of developers while source code metrics have little effect on improving the accuracy of estimations of coding effort. The study also shows that models trained on one project are unreliable at estimating effort in other projects.


On Finding Frequent Patterns in Event Sequences

Abstract: Given a directed acyclic graph with labeled vertices, we consider the problem of finding the most common label sequences ("traces") among all paths in the graph (of some maximum length m). Since the number of paths can be huge, we propose novel algorithms whose time complexity depends only on the size of the graph, and on the frequency epsilon of the most frequent traces. In addition, we apply techniques from streaming algorithms to achieve space usage that depends only on epsilon, and not on the number of distinct traces. The abstract problem considered models a variety of tasks concerning finding frequent patterns in event sequences. Our motivation comes from working with a data set of 2 million RFID readings from baggage trolleys at Copenhagen Airport. The question of finding frequent passenger movement patterns is mapped to the above problem. We report on experimental findings for this data set.


Lattice Problems and Their Reductions(Russian)

Abstract: This article presets a review of lattice problems. Paper contains the main eighteen problems with their reductions and referents to his cryptography application. As an example of reduction, we detail analyze connection between SVP and CVP. Moreover, we give an Ajtai theorem and demonstrate its role in lattice based cryptography.


On Finding Similar Items in a Stream of Transactions

Abstract: While there has been a lot of work on finding frequent itemsets in transaction data streams, none of these solve the problem of finding similar pairs according to standard similarity measures. This paper is a first attempt at dealing with this, arguably more important, problem. We start out with a negative result that also explains the lack of theoretical upper bounds on the space usage of data mining algorithms for finding frequent itemsets: Any algorithm that (even only approximately and with a chance of error) finds the most frequent k-itemset must use space Omega(min{mb,n^k,(mb/phi)^k}) bits, where mb is the number of items in the stream so far, n is the number of distinct items and phi is a support threshold. To achieve any non-trivial space upper bound we must thus abandon a worst-case assumption on the data stream. We work under the model that the transactions come in random order, and show that surprisingly, not only is small-space similarity mining possible for the most common similarity measures, but the mining accuracy improves with the length of the stream for any fixed support threshold.


Learning Taxonomy for Text Segmentation by Formal Concept Analysis

Abstract: In this paper the problems of deriving a taxonomy from a text and concept-oriented text segmentation are approached. Formal Concept Analysis (FCA) method is applied to solve both of these linguistic problems. The proposed segmentation method offers a conceptual view for text segmentation, using a context-driven clustering of sentences. The Concept-oriented Clustering Segmentation algorithm (COCS) is based on k-means linear clustering of the sentences. Experimental results obtained using COCS algorithm are presented.


Splitting schemes for hyperbolic heat conduction equation

Abstract: Rapid processes of heat transfer are not described by the standard heat conduction equation. To take into account a finite velocity of heat transfer, we use the hyperbolic model of heat conduction, which is connected with the relaxation of heat fluxes. In this case, the mathematical model is based on a hyperbolic equation of second order or a system of equations for the temperature and heat fluxes. In this paper we construct for the hyperbolic heat conduction equation the additive schemes of splitting with respect to directions. Unconditional stability of locally one-dimensional splitting schemes is established. New splitting schemes are proposed and studied for a system of equations written in terms of the temperature and heat fluxes.


The surprizing complexity of generalized reachability games

Abstract: Games on graphs provide a natural and powerful model for reactive systems. In this paper, we consider generalized reachability objectives, defined as conjunctions of reachability objectives. We first prove that deciding the winner in such games is $\PSPACE$-complete, although it is fixed-parameter tractable with the number of reachability objectives as parameter. Moreover, we consider the memory requirements for both players and give matching upper and lower bounds on the size of winning strategies. In order to allow more efficient algorithms, we consider subclasses of generalized reachability games. We show that bounding the size of the reachability sets gives two natural subclasses where deciding the winner can be done efficiently.


Transmitting Video-on-Demand Effectively

Abstract: Now-a-days internet has become a vast source of entertainment & new services are available in quick succession which provides entertainment to the users. One of this service i.e. Video-on-Demand is most hyped service in this context. Transferring the video over the network with less error is the main objective of the service providers. In this paper we present an algorithm for routing the video to the user in an effective manner along with a method that ensures less error rate than others.


Enabling Data Discovery through Virtual Internet Repositories

Abstract: Mercury is a federated metadata harvesting, search and retrieval tool based on both open source and software developed at Oak Ridge National Laboratory. It was originally developed for NASA, and the Mercury development consortium now includes funding from NASA, USGS, and DOE. A major new version of Mercury was developed during 2007. This new version provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, support for RSS delivery of search results, among other features. Mercury provides a single portal to information contained in disparate data management systems. It collects metadata and key data from contributing project servers distributed around the world and builds a centralized index. The Mercury search interfaces then allow the users to perform simple, fielded, spatial and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data.


Collaborative Trust: A Novel Paradigm of Trusted Mobile Computing

Abstract: With increasing complexity of modern-day mobile devices, security of these devices in presence of myriad attacks by an intelligent adversary is becoming a major issue. The vast majority of cell phones still remain unsecured from many existing and emerging security threats. To address the security threats in mobile devices we are exploring a technology, which we refer as "Collaborative Trust". It is a technology that uses a system of devices cooperating with each other (working in a fixed or ad-hoc network) to achieve the individual security of each device. The idea is that each device is insecure by itself, since in many cases it is incapable of checking its safety by itself (e.g. when it is compromised it may lose its ability to monitor its own trustworthiness), but together, they can ensure each other's security in a collaborative manner.


Flat Zipper-Unfolding Pairs for Platonic Solids

Abstract: We show that four of the five Platonic solids' surfaces may be cut open with a Hamiltonian path along edges and unfolded to a polygonal net each of which can "zipper-refold" to a flat doubly covered parallelogram, forming a rather compact representation of the surface. Thus these regular polyhedra have particular flat "zipper pairs." No such zipper pair exists for a dodecahedron, whose Hamiltonian unfoldings are "zip-rigid." This report is primarily an inventory of the possibilities, and raises more questions than it answers.


Distributed Deterministic Edge Coloring using Bounded Neighborhood Independence

Abstract: We study the {edge-coloring} problem in the message-passing model of distributed computing. This is one of the most fundamental and well-studied problems in this area. Currently, the best-known deterministic algorithms for (2Delta -1)-edge-coloring requires O(Delta) + log-star n time \cite{PR01}, where Delta is the maximum degree of the input graph. Also, recent results of \cite{BE10} for vertex-coloring imply that one can get an O(Delta)-edge-coloring in O(Delta^{epsilon} \cdot \log n) time, and an O(Delta^{1 + epsilon})-edge-coloring in O(log Delta log n) time, for an arbitrarily small constant epsilon > 0. In this paper we devise a drastically faster deterministic edge-coloring algorithm. Specifically, our algorithm computes an O(Delta)-edge-coloring in O(Delta^{epsilon}) + log-star n time, and an O(Delta^{1 + epsilon})-edge-coloring in O(log Delta) + log-star n time. This result improves the previous state-of-the-art {exponentially} in a wide range of Delta, specifically, for 2^{Omega(\log-star n)} \leq Delta \leq polylog(n). In addition, for small values of Delta our deterministic algorithm outperforms all the existing {randomized} algorithms for this problem. On our way to these results we study the {vertex-coloring} problem on the family of graphs with bounded {neighborhood independence}. This is a large family, which strictly includes line graphs of r-hypergraphs for any r = O(1), and graphs of bounded growth. We devise a very fast deterministic algorithm for vertex-coloring graphs with bounded neighborhood independence. This algorithm directly gives rise to our edge-coloring algorithms, which apply to {general} graphs. Our main technical contribution is a subroutine that computes an O(Delta/p)-defective p-vertex coloring of graphs with bounded neighborhood independence in O(p^2) + \log-star n time, for a parameter p, 1 \leq p \leq Delta.


Constructing Two Edge-Disjoint Hamiltonian Cycles in Locally Twisted Cubes

Abstract: The $n$-dimensional hypercube network $Q_n$ is one of the most popular interconnection networks since it has simple structure and is easy to implement. The $n$-dimensional locally twisted cube, denoted by $LTQ_n$, an important variation of the hypercube, has the same number of nodes and the same number of connections per node as $Q_n$. One advantage of $LTQ_n$ is that the diameter is only about half of the diameter of $Q_n$. Recently, some interesting properties of $LTQ_n$ were investigated. In this paper, we construct two edge-disjoint Hamiltonian cycles in the locally twisted cube $LTQ_n$, for any integer $n\geqslant 4$. The presence of two edge-disjoint Hamiltonian cycles provides an advantage when implementing algorithms that require a ring structure by allowing message traffic to be spread evenly across the locally twisted cube.


Three-coloring triangle-free graphs on surfaces I. Extending a coloring to a disk with one triangle

Abstract: Let G be a plane graph with exactly one triangle T and all other cycles of length at least 5, and let C be a facial cycle of G of length at most six. We prove that a 3-coloring of C does not extend to a 3-coloring of G if and only if C has length exactly six and there is a color x such that either G has an edge joining two vertices of C colored x, or T is disjoint from C and every vertex of T is adjacent to a vertex of C colored x. This is a lemma to be used in a future paper of this series.


The use of machine learning with signal- and NLP processing of source code to fingerprint, detect, and classify vulnerabilities and weaknesses with MARFCAT

Abstract: We present a machine learning approach to static code analysis and fingerprinting for weaknesses related to security, software engineering, and others using the open-source MARF framework and the MARFCAT application based on it for the NIST's SATE2010 static analysis tool exposition workshop found at http://samate.nist.gov/SATE2010Workshop.html


Regular Expressions, au point

Abstract: We introduce a new technique for constructing a finite state deterministic automaton from a regular expression, based on the idea of marking a suitable set of positions inside the expression, intuitively representing the possible points reached after the processing of an initial prefix of the input string. Pointed regular expressions join the elegance and the symbolic appealingness of Brzozowski's derivatives, with the effectiveness of McNaughton and Yamada's labelling technique, essentially combining the best of the two approaches.


An Asymmetric Fingerprinting Scheme based on Tardos Codes

Abstract: Tardos codes are currently the state-of-the-art in the design of practical collusion-resistant fingerprinting codes. Tardos codes rely on a secret vector drawn from a publicly known probability distribution in order to generate each Buyer's fingerprint. For security purposes, this secret vector must not be revealed to the Buyers. To prevent an untrustworthy Provider forging a copy of a Work with an innocent Buyer's fingerprint, previous asymmetric fingerprinting algorithms enforce the idea of the Buyers generating their own fingerprint. Applying this concept to Tardos codes is challenging since the fingerprint must be based on this vector secret. This paper provides the first solution for an asymmetric fingerprinting protocol dedicated to Tardos codes. The motivations come from a new attack, in which an untrustworthy Provider by modifying his secret vector frames an innocent Buyer.


Privacy-Compatibility For General Utility Metrics

Abstract: In this note, we present a complete characterization of the utility metrics that allow for non-trivial differential privacy guarantees.


Function and form of gestures in a collaborative design meeting

Abstract: This paper examines the relationship between gestures' function and form in design collaboration. It adopts a cognitive design research viewpoint. The analysis is restricted to gesticulations and emblems. The data analysed come from an empirical study conducted on an architectural design meeting. Based on a previous analysis of the data, guided by our model of design as the construction of representations, we distinguish representational and organisational functions. The results of the present analysis are that, even if form-function association tendencies exist, gestures with a particular function may take various forms, and particular gestural movements as regards form can fulfil different functions. Reconsidering these results and other research on gesture, we formulate the assumption that, if formal characteristics do not allow differentiating functional gestures in collaboration, context-dependent, semantic characteristics may be more appropriate. We also envision the possibility that closer inspection of the data reveal tendencies of another nature.


A Strategy-Proof and Non-monetary Admission Control Mechanism for Wireless Access Networks

Abstract: We study admission control mechanisms for wireless access networks where (i) each user has a minimum service requirement, (ii) the capacity of the access network is limited, and (iii) the access point is not allowed to use monetary mechanisms to guarantee that users do not lie when disclosing their minimum service requirements. To guarantee truthfulness, we use auction theory to design a mechanism where users compete to be admitted into the network. We propose admission control mechanisms under which the access point intelligently allocates resources based on the announced minimum service requirements to ensure that users have no incentive to lie and the capacity constraint is fulfilled. We also prove the properties that any feasible mechanism should have.


"Reminder: please update your details": Phishing Trends

Abstract: Spam messes up users inbox, consumes resources and spread attacks like DDoS, MiM, Phishing etc., Phishing is a byproduct of email and causes financial loss to users and loss of reputation to financial institutions. In this paper we study the characteristics of phishing and technology used by phishers. In order to counter anti phishing technology, phishers change their mode of operation; therefore continuous evaluation of phishing helps us to combat phishers effectively. We have collected seven hundred thousand spam from a corporate server for a period of 13 months from February 2008 to February 2009. From the collected date, we identified different kinds of phishing scams and mode of their operation. Our observation shows that phishers are dynamic and depend more on social engineering techniques rather than software vulnerabilities. We believe that this study would be useful to develop more efficient anti phishing methodologies.


Duty-Cycle-Aware Minimum-Energy Multicasting in Wireless Sensor Networks

Abstract: In duty-cycled wireless sensor networks, the nodes switch between active and dormant states, and each node may determine its active/dormant schedule independently. This complicates the Minimum-Energy Multicasting (MEM) problem, which has been primarily studied in always-active wireless ad-hoc networks. In this paper, we study the duty-cycle-aware MEM problem in wireless sensor networks, and we present a formulation of the Minimum-Energy Multicast Tree Construction and Scheduling (MEMTCS) problem. We prove that the MEMTCS problem is NP-hard, and it is unlikely to have an approximation algorithm with a performance ratio of $(1-o(1))\ln\Delta$, where $\Delta$ is the maximum node degree in a network. We propose a polynomial-time approximation algorithm for the MEMTCS problem with a performance ratio of $\mathcal{O}(H(\Delta+1))$, where $H(\cdot)$ is the harmonic number. We also provide a distributed implementation of our algorithm. Finally, we perform extensive simulations and the results demonstrate that our algorithm significantly outperform other known algorithms in terms of both the total energy cost and the transmission redundancy.


Contract Aware Components, 10 years after

Abstract: The notion of contract aware components has been published roughly ten years ago and is now becoming mainstream in several fields where the usage of software components is seen as critical. The goal of this paper is to survey domains such as Embedded Systems or Service Oriented Architecture where the notion of contract aware components has been influential. For each of these domains we briefly describe what has been done with this idea and we discuss the remaining challenges.


Partition Refinement of Component Interaction Automata: Why Structure Matters More Than Size

Abstract: Automata-based modeling languages, like Component Interaction Automata, offer an attractive means to capture and analyze the behavioral aspects of interacting components. At the center of these modeling languages we find finite state machines that allow for a fine-grained description how and when specific service requests may interact with other components or the environment. Unfortunately, automata-based approaches suffer from exponential state explosion, a major obstacle to the successful application of these formalisms in modeling real-world scenarios. In order to cope with the complexity of individual specifications we can apply partition refinement, an abstraction technique to alleviate the state explosion problem. But this technique too exhibits exponential time and space complexity and, worse, does not offer any guarantees for success. To better understand as to why partition refinement succeeds in some cases while it fails in others, we conducted an empirical study on the performance of a partition refinement algorithm for Component Interaction Automata specifications. As a result we have identified suitable predictors for the expected effectiveness of partition refinement. It is the structure, not the size, of a specification that weighs heavier on the outcome of partition refinement. In particular, Component Interaction Automata specifications for real-world systems are capable of producing scale-free networks containing structural artifacts that can assist the partition refinement algorithm not only converge earlier, but also yield a significant state space reduction on occasion.


Behavioural Models for Group Communications

Abstract: Group communication is becoming a more and more popular infrastructure for efficient distributed applications. It consists in representing locally a group of remote objects as a single object accessed in a single step; communications are then broadcasted to all members. This paper provides models for automatic verification of group-based applications, typically for detecting deadlocks or checking message ordering. We show how to encode group communication, together with different forms of synchronisation for group results. The proposed models are parametric such that, for example, different group sizes or group members could be experimented with the minimum modification of the original model.


Components Interoperability through Mediating Connector Patterns

Abstract: A key objective for ubiquitous environments is to enable system interoperability between system's components that are highly heterogeneous. In particular, the challenge is to embed in the system architecture the necessary support to cope with behavioral diversity in order to allow components to coordinate and communicate. The continuously evolving environment further asks for an automated and on-the-fly approach. In this paper we present the design building blocks for the dynamic and on-the-fly interoperability between heterogeneous components. Specifically, we describe an Architectural Pattern called Mediating Connector, that is the key enabler for communication. In addition, we present a set of Basic Mediator Patterns, that describe the basic mismatches which can occur when components try to interact, and their corresponding solutions.


Tau Be or not Tau Be? - A Perspective on Service Compatibility and Substitutability

Abstract: One of the main open research issues in Service Oriented Computing is to propose automated techniques to analyse service interfaces. A first problem, called compatibility, aims at determining whether a set of services (two in this paper) can be composed together and interact with each other as expected. Another related problem is to check the substitutability of one service with another. These problems are especially difficult when behavioural descriptions (i.e., message calls and their ordering) are taken into account in service interfaces. Interfaces should capture as faithfully as possible the service behaviour to make their automated analysis possible while not exhibiting implementation details. In this position paper, we choose Labelled Transition Systems to specify the behavioural part of service interfaces. In particular, we show that internal behaviours (tau transitions) are necessary in these transition systems in order to detect subtle errors that may occur when composing a set of services together. We also show that tau transitions should be handled differently in the compatibility and substitutability problem: the former problem requires to check if the compatibility is preserved every time a tau transition is traversed in one interface, whereas the latter requires a precise analysis of tau branchings in order to make the substitution preserve the properties (e.g., a compatibility notion) which were ensured before replacement.


Multilevel Contracts for Trusted Components

Abstract: This article contributes to the design and the verification of trusted components and services. The contracts are declined at several levels to cover then different facets, such as component consistency, compatibility or correctness. The article introduces multilevel contracts and a design+verification process for handling and analysing these contracts in component models. The approach is implemented with the COSTO platform that supports the Kmelia component model. A case study illustrates the overall approach.


A Reusable Component for Communication and Data Synchronization in Mobile Distributed Interactive Applications

Abstract: In Distributed Interactive Applications (DIA) such as multiplayer games, where many participants are involved in a same game session and communicate through a network, they may have an inconsistent view of the virtual world because of the communication delays across the network. This issue becomes even more challenging when communicating through a cellular network while executing the DIA client on a mobile terminal. Consistency maintenance algorithms may be used to obtain a uniform view of the virtual world. These algorithms are very complex and hard to program and therefore, the implementation and the future evolution of the application logic code become difficult. To solve this problem, we propose an approach where the consistency concerns are handled separately by a distributed component called a Synchronization Medium, which is responsible for the communication management as well as the consistency maintenance. We present the detailed architecture of the Synchronization Medium and the generic interfaces it offers to DIAs. We evaluate our approach both qualitatively and quantitatively. We first demonstrate that the Synchronization Medium is a reusable component through the development of two game applications, a car racing game and a space war game. A performance evaluation then shows that the overhead introduced by the Synchronization Medium remains acceptable.


Improved Complexity Bound of Vertex Cover for Low degree Graph

Abstract: In this paper, we use a new method to decrease the parameterized complexity bound for finding the minimum vertex cover of connected max-degree-3 undirected graphs. The key operation of this method is reduction of the size of a particular subset of edges which we introduce in this paper and is called as "real-cycle" subset. Using "real-cycle" reductions alone we compute a complexity bound $O(1.15855^k)$ where $k$ is size of the optimal vertex cover. Combined with other techniques, the complexity bound can be further improved to be $O(1.1504^k)$. This is currently the best complexity bound.


Steering Fragments of Instruction Sequences

Abstract: A steering fragment of an instruction sequence consists of a sequence of steering instructions. These are decision points involving the check of a propositional statement in sequential logic. The question is addressed why composed propositional statements occur in steering fragments given the fact that a straightforward transformation allows their elimination. A survey is provided of constraints that may be implicitly assumed when composed propositional statements occur in a meaningful instruction sequence.


Service Level Agreement (SLA) in Utility Computing Systems

Abstract: In recent years, extensive research has been conducted in the area of Service Level Agreement (SLA) for utility computing systems. An SLA is a formal contract used to guarantee that consumers' service quality expectation can be achieved. In utility computing systems, the level of customer satisfaction is crucial, making SLAs significantly important in these environments. Fundamental issue is the management of SLAs, including SLA autonomy management or trade off among multiple Quality of Service (QoS) parameters. Many SLA languages and frameworks have been developed as solutions; however, there is no overall classification for these extensive works. Therefore, the aim of this chapter is to present a comprehensive survey of how SLAs are created, managed and used in utility computing environment. We discuss existing use cases from Grid and Cloud computing systems to identify the level of SLA realization in state-of-art systems and emerging challenges for future research.


Improved approximations for robust mincut and shortest path

Abstract: In two-stage robust optimization the solution to a problem is built in two stages: In the first stage a partial, not necessarily feasible, solution is exhibited. Then the adversary chooses the "worst" scenario from a predefined set of scenarios. In the second stage, the first-stage solution is extended to become feasible for the chosen scenario. The costs at the second stage are larger than at the first one, and the objective is to minimize the total cost paid in the two stages. We give a 2-approximation algorithm for the robust mincut problem and a ({\gamma}+2)-approximation for the robust shortest path problem, where {\gamma} is the approximation ratio for the Steiner tree. This improves the factors (1+\sqrt2) and 2({\gamma}+2) from [Golovin, Goyal and Ravi. Pay today for a rainy day: Improved approximation algorithms for demand-robust min-cut and shortest path problems. STACS 2006]. In addition, our solution for robust shortest path is simpler and more efficient than the earlier ones; this is achieved by a more direct algorithm and analysis, not using some of the standard demand-robust optimization techniques.


Electrical Flows, Laplacian Systems, and Faster Approximation of Maximum Flow in Undirected Graphs

Abstract: We introduce a new approach to computing an approximately maximum s-t flow in a capacitated, undirected graph. This flow is computed by solving a sequence of electrical flow problems. Each electrical flow is given by the solution of a system of linear equations in a Laplacian matrix, and thus may be approximately computed in nearly-linear time. Using this approach, we develop the fastest known algorithm for computing approximately maximum s-t flows. For a graph having n vertices and m edges, our algorithm computes a (1-\epsilon)-approximately maximum s-t flow in time \tilde{O}(mn^{1/3} \epsilon^{-11/3}). A dual version of our approach computes a (1+\epsilon)-approximately minimum s-t cut in time \tilde{O}(m+n^{4/3}\eps^{-8/3}), which is the fastest known algorithm for this problem as well. Previously, the best dependence on m and n was achieved by the algorithm of Goldberg and Rao (J. ACM 1998), which can be used to compute approximately maximum s-t flows in time \tilde{O}(m\sqrt{n}\epsilon^{-1}), and approximately minimum s-t cuts in time \tilde{O}(m+n^{3/2}\epsilon^{-3}).


Simplification of cross-field topology

Abstract: We present an innovative algorithm that simplifies the topology of a cross-field. Our algorithm works through macro-operations that allow us editing the graph of separatrices, which is extracted from a cross-field, while maintaining it topologically consistent. We present preliminary results of our implementation.