Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs

Abstract: The competitive MNIST handwritten digit recognition benchmark has a long history of broken records since 1998. The most recent substantial improvement by others dates back 7 years (error rate 0.4%) . Recently we were able to significantly improve this result, using graphics cards to greatly speed up training of simple but deep MLPs, which achieved 0.35%, outperforming all the previous more complex methods. Here we report another substantial improvement: 0.31% obtained using a committee of MLPs.


An Improved Efficient Key Distribution Mechanism for Large-Scale Heterogeneous Mobile Sensor Networks

Abstract: Due to resource constraints of the sensor nodes, traditional public key cryptographic techniques are not feasible in most sensor network architectures. Several symmetric key distribution mechanisms are proposed for establishing pairwise keys between sensor nodes in sensor networks, but most of them are not scalable and also are not much suited for mobile sensor networks because they incur much communication as well as computational overheads. Moreover, these schemes are either vulnerable to a small number of compromised sensor nodes or involve expensive protocols for establishing keys. In this paper, we introduce a new scheme for establishing keys between sensor nodes with the help of additional high-end sensor nodes, called the auxiliary nodes. Our scheme provides unconditional security against sensor node captures and high network connectivity. In addition, our scheme requires minimal storage requirement for storing keys mainly due to only a single key before deployment in each node in the sensor network, supports efficiently addition of new nodes after initial deployment and also works for any deployment topology.


An Algorithm for Odd Gracefulness of the Tensor Product of Two Line Graphs

Abstract: An odd graceful labeling of a graph G=(V,E) is a function f:V(G)->[0,1,2,...,2|E(G)|-1} such that |f(u)-f(v)| is odd value less than or equal to 2|E(G)-1| for any u, v in V(G). In spite of the large number of papers published on the subject of graph labeling, there are few algorithms to be used by researchers to gracefully label graphs. This work provides generalized odd graceful solutions to all the vertices and edges for the tensor product of the two paths P_n and P_m denoted P_n^P_m . Firstly, we describe an algorithm to label the vertices and the edges of the vertex set V(P_n^P_m) and the edge set E(P_n^P_m) respectively. Finally, we prove that the graph P_n^P_m is odd graceful for all integers n and m.


Hardness of discrepancy computation and epsilon-net verification in high dimension

Abstract: Discrepancy measures how uniformly distributed a point set is with respect to a given set of ranges. There are two notions of discrepancy, namely continuous discrepancy and combinatorial discrepancy. Depending on the ranges, several possible variants arise, for example star discrepancy, box discrepancy, and discrepancy of half-spaces. In this paper, we investigate the hardness of these problems with respect to the dimension d of the underlying space. All these problems are solvable in time {n^O(d)}, but such a time dependency quickly becomes intractable for high-dimensional data. Thus it is interesting to ask whether the dependency on d can be moderated. We answer this question negatively by proving that the canonical decision problems are W[1]-hard with respect to the dimension. This is done via a parameterized reduction from the Clique problem. As the parameter stays linear in the input parameter, the results moreover imply that these problems require {n^\Omega(d)} time, unless 3-Sat can be solved in {2^o(n)} time. Further, we derive that testing whether a given set is an {\epsilon}-net with respect to half-spaces takes {n^\Omega(d)} time under the same assumption. As intermediate results, we discover the W[1]-hardness of other well known problems, such as determining the largest empty star inside the unit cube. For this, we show that it is even hard to approximate within a factor of {2^n}.


Remarks on separating words

Abstract: The separating words problem asks for the size of the smallest DFA needed to distinguish between two words of length <= n (by accepting one and rejecting the other). In this paper we survey what is known and unknown about the problem, consider some variations, and prove several new results.


Real Islamic Logic

Abstract: Four options for assigning a meaning to Islamic Logic are surveyed including a new proposal for an option named "Real Islamic Logic" (RIL). That approach to Islamic Logic should serve modern Islamic objectives in a way comparable to the functionality of Islamic Finance. The prospective role of RIL is analyzed from several perspectives: (i) parallel distributed systems design, (ii) reception by a community structured audience, (iii) informal logic and applied non-classical logics, and (iv) (in)tractability and artificial intelligence.


An implementation of range trees with fractional cascading in C++

Abstract: Range trees are multidimensional binary trees which are used to perform d-dimensional orthogonal range searching. In this technical report we study the implementation issues of range trees with fractional cascading, named layered range trees. We also document our implementation of range trees with fractional cascading in C++ using STL and generic programming techniques.


Representing First-Order Causal Theories by Logic Programs

Abstract: Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner, became a basis for the semantics of several expressive action languages. McCain's embedding of definite propositional causal theories into logic programming paved the way to the use of answer set solvers for answering queries about actions described in such languages. In this paper we extend this embedding to nondefinite theories and to first-order causal logic.


The Topology of Wireless Communication

Abstract: In this paper we study the topological properties of wireless communication maps and their usability in algorithmic design. We consider the SINR model, which compares the received power of a signal at a receiver against the sum of strengths of other interfering signals plus background noise. To describe the behavior of a multi-station network, we use the convenient representation of a \emph{reception map}. In the SINR model, the resulting \emph{SINR diagram} partitions the plane into reception zones, one per station, and the complementary region of the plane where no station can be heard. We consider the general case where transmission energies are arbitrary (or non-uniform). Under that setting, the reception zones are not necessarily convex or even connected. This poses the algorithmic challenge of designing efficient point location techniques as well as the theoretical challenge of understanding the geometry of SINR diagrams. We achieve several results in both directions. We establish a form of weaker convexity in the case where stations are aligned on a line. In addition, one of our key results concerns the behavior of a $(d+1)$-dimensional map. Specifically, although the $d$-dimensional map might be highly fractured, drawing the map in one dimension higher "heals" the zones, which become connected. In addition, as a step toward establishing a weaker form of convexity for the $d$-dimensional map, we study the interference function and show that it satisfies the maximum principle. Finally, we turn to consider algorithmic applications, and propose a new variant of approximate point location.


Logical, Metric, and Algorithmic Characterisations of Probabilistic Bisimulation

Abstract: Many behavioural equivalences or preorders for probabilistic processes involve a lifting operation that turns a relation on states into a relation on distributions of states. We show that several existing proposals for lifting relations can be reconciled to be different presentations of essentially the same lifting operation. More interestingly, this lifting operation nicely corresponds to the Kantorovich metric, a fundamental concept used in mathematics to lift a metric on states to a metric on distributions of states, besides the fact the lifting operation is related to the maximum flow problem in optimisation theory. The lifting operation yields a neat notion of probabilistic bisimulation, for which we provide logical, metric, and algorithmic characterisations. Specifically, we extend the Hennessy-Milner logic and the modal mu-calculus with a new modality, resulting in an adequate and an expressive logic for probabilistic bisimilarity, respectively. The correspondence of the lifting operation and the Kantorovich metric leads to a natural characterisation of bisimulations as pseudometrics which are post-fixed points of a monotone function. We also present an "on the fly" algorithm to check if two states in a finitary system are related by probabilistic bisimilarity, exploiting the close relationship between the lifting operation and the maximum flow problem.


An Identity Based Key Management Scheme in Wireless Sensor Networks

Abstract: Pairwise key establishment is one of the fundamental security services in sensor networks which enables sensor nodes in a sensor network to communicate securely with each other using cryptographic techniques. It is not feasible to apply traditional public key management techniques in resource-constrained sensor nodes, and also because the sensor nodes are vulnerable to physical capture. In this paper, we introduce a new scheme called the identity based key pre-distribution using a pseudo random function (IBPRF), which has better trade-off between communication overhead, network connectivity and resilience against node capture compared to the other key pre-distribution schemes. Our scheme can be easily adapted in mobile sensor networks. This scheme supports the addition of new sensor nodes after the initial deployment and also works for any deployment topology. In addition, we propose an improved version of our scheme to support large sensor networks.


An Unconditionally Secure Key Management Scheme for Large-Scale Heterogeneous Wireless Sensor Networks

Abstract: Key establishment in sensor networks becomes a challenging problem because of the resource limitations of the sensors and also due to vulnerability to physical capture of the sensor nodes. In this paper, we propose an unconditionally secure probabilistic group-based key pre-distribution scheme for a heterogeneous wireless sensor network. The proposed scheme always guarantees that no matter how many sensor nodes are compromised, the non-compromised nodes can still communicate with 100% secrecy, i.e., the proposed scheme is always unconditionally secure against node capture attacks. Moreover, it provides significantly better trade-off between communication overhead, computational overhead, network connectivity and security against node capture as compared to the existing key pre-distribution schemes. It also supports dynamic node addition after the initial deployment of the nodes in the network.


Note on minimally k-connected graphs

Abstract: A k-tree is either a complete graph on (k+1) vertices or given a k-tree G' with n vertices, a k-tree G with (n+1) vertices can be constructed by introducing a new vertex v and picking a k-clique Q in G' and then joining each vertex u in Q. A graph G is k-edge-connected if the graph remains connected even after deleting fewer edges than k from the graph. A k-edge-connected graph G is said to be minimally k-connected if G \ {e} is no longer k-edge-connected for any edge e belongs to E(G) where E(G) denotes the set of edges of G. In this paper we find two separate O (n2) algorithms so that a minimally 2-connected graph can be obtained from a 2-tree and a minimally k-connected graph can be obtained from a k-tree. In a k-tree (k \geq 2) we find the edges which are insensitive to the k-connectivity have both their end vertices of degrees greater than or equal to k+1.This property is fully exploited to find an algorithm which reduces any k-tree to a minimally k-connected graph.


Linearizable Implementations Do Not Suffice for Randomized Distributed Computation

Abstract: Linearizability is the gold standard among algorithm designers for deducing the correctness of a distributed algorithm using implemented shared objects from the correctness of the corresponding algorithm using atomic versions of the same objects. We show that linearizability does not suffice for this purpose when processes can exploit randomization, and we discuss the existence of alternative correctness conditions.


Cyclic and Inductive Calculi are equivalent

Abstract: Brotherston and Simpson [citation] have formalized and investigated cyclic reasoning, reaching the important conclusion that it is at least as powerful as inductive reasoning (specifically, they showed that each inductive proof can be translated into a cyclic proof). We add to their investigation by proving the converse of this result, namely that each inductive proof can be translated into an inductive one. This, in effect, establishes the equivalence between first order cyclic and inductive calculi.


Distributed Video Coding: Codec Architecture and Implementation

Abstract: Distributed Video Coding (DVC) is a new coding paradigm for video compression, based on Slepian- Wolf (lossless coding) and Wyner-Ziv (lossy coding) information theoretic results. DVC is useful for emerging applications such as wireless video cameras, wireless low-power surveillance networks and disposable video cameras for medical applications etc. The primary objective of DVC is low-complexity video encoding, where bulk of computation is shifted to the decoder, as opposed to low-complexity decoder in conventional video compression standards such as H.264 and MPEG etc. There are couple of early architectures and implementations of DVC from Stanford University[2][3] in 2002, Berkeley University PRISM (Power-efficient, Robust, hIgh-compression, Syndrome-based Multimedia coding)[4][5] in 2002 and European project DISCOVER (DIStributed COding for Video SERvices)[6] in 2007. Primarily there are two types of DVC techniques namely pixel domain and transform domain based. Transform domain design will have better rate-distortion (RD) performance as it exploits spatial correlation between neighbouring samples and compacts the block energy into as few transform coefficients as possible (aka energy compaction). In this paper, architecture, implementation details and "C" model results of our transform domain DVC are presented.


TiA -- Documentation of TOBI Interface A

Abstract: This document contains the documentation of TOBI (Tools for BCI) Interface A (TiA). TiA is a standardized interface to transmit raw biosignals. It is able to deal with multirate and block-oriented data transmission. Data is distinguished by different signal types (e.g., EEG, EOG, NIRS,...), whereby those signals can be acquired at the same time from different acquisition devices. TiA is built as a client-server model. Multiple clients can connect to one server. Information is exchanged via a control- and a separated data connection. Control commands and meta information are transmitted over the control connection. Raw biosignal data is delivered using the data connection in a unidirectional way. For this purpose a standardized handshaking protocol and raw data packet have been developed. Thus, an abstraction layer between hardware devices and data processing was evolved facilitating standardization.


Computer Modelling of 3D Geological Surface

Abstract: The geological surveying presently uses methods and tools for the computer modeling of 3D-structures of the geographical subsurface and geotechnical characterization as well as the application of geoinformation systems for management and analysis of spatial data, and their cartographic presentation. The objectives of this paper are to present a 3D geological surface model of Latur district in Maharashtra state of India. This study is undertaken through the several processes which are discussed in this paper to generate and visualize the automated 3D geological surface model of a projected area.


Automatic Extraction of Open Space Area from High Resolution Urban Satellite Imagery

Abstract: In the 21st century, Aerial and satellite images are information rich. They are also complex to analyze. For GIS systems, many features require fast and reliable extraction of open space area from high resolution satellite imagery. In this paper we will study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery. This automatic extraction algorithm uses some filters and segmentations and grouping is applying on satellite images. And the result images may use to calculate the total available open space area and the built up area. It may also use to compare the difference between present and past open space area using historical urban satellite images of that same projection


Trust Based Participant Driven Privacy Control in Participatory Sensing

Abstract: Widespread use of sensors and multisensory personal devices generate a lot of personal information. Sharing this information with others could help in various ways. However, this information may be misused when shared with all. Sharing of information between trusted parties overcomes this problem. This paper describes a model to share information based on interactions and opinions to build trust among peers. It also considers institutional and other controls, which influence the behaviour of the peers. The trust and control build confidence. The computed confidence bespeaks whether to reveal information or not thereby increasing trusted cooperation among peers.


Lost in translation: data integration tools meet the Semantic Web (experiences from the Ondex project)

Abstract: More information is now being published in machine processable form on the web and, as de-facto distributed knowledge bases are materializing, partly encouraged by the vision of the Semantic Web, the focus is shifting from the publication of this information to its consumption. Platforms for data integration, visualization and analysis that are based on a graph representation of information appear first candidates to be consumers of web-based information that is readily expressible as graphs. The question is whether the adoption of these platforms to information available on the Semantic Web requires some adaptation of their data structures and semantics. Ondex is a network-based data integration, analysis and visualization platform which has been developed in a Life Sciences context. A number of features, including semantic annotation via ontologies and an attention to provenance and evidence, make this an ideal candidate to consume Semantic Web information, as well as a prototype for the application of network analysis tools in this context. By analyzing the Ondex data structure and its usage, we have found a set of discrepancies and errors arising from the semantic mismatch between a procedural approach to network analysis and the implications of a web-based representation of information. We report in the paper on the simple methodology that we have adopted to conduct such analysis, and on issues that we have found which may be relevant for a range of similar platforms


High-Energy-First (HEF) Heuristic for Energy-Efficient Target Coverage Problem

Abstract: Target coverage problem in wireless sensor networks is concerned with maximizing the lifetime of the network while continuously monitoring a set of targets. A sensor covers targets which are within the sensing range. For a set of sensors and a set of targets, the sensor-target coverage relationship is assumed to be known. A sensor cover is a set of sensors that covers all the targets. The target coverage problem is to determine a set of sensor covers with maximum aggregated lifetime while constraining the life of each sensor by its initial battery life. The problem is proved to be NP-complete and heuristic algorithms to solve this problem are proposed. In the present study, we give a unified interpretation of earlier algorithms and propose a new and efficient algorithm. We show that all known algorithms are based on a common reasoning though they seem to be derived from different algorithmic paradigms. We also show that though some algorithms guarantee bound on the quality of the solution, this bound is not meaningful and not practical too. Our interpretation provides a better insight to the solution techniques. We propose a new greedy heuristic which prioritizes sensors on residual battery life. We show empirically that the proposed algorithm outperforms all other heuristics in terms of quality of solution. Our experimental study over a large set of randomly generated problem instances also reveals that a very na\"ive greedy approach yields solutions which is reasonably (appx. 10%) close to the actual optimal solutions.


Formal and Computational Properties of the Confidence Boost of Association Rules

Abstract: Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion of interest of an association rule, in terms of its "novelty" with respect to other rules. Namely: an irredundant rule is so because its confidence is higher than what the rest of the rules would suggest; then, one can ask: how much higher? We propose to measure such a sort of "novelty" through the confidence boost of a rule, which encompasses two previous similar notions (confidence width and rule blocking, of which the latter is closely related to the earlier measure "improvement"). Acting as a complement to confidence and support, the confidence boost helps to obtain small and crisp sets of mined association rules, and solves the well-known problem that, in certain cases, rules of negative correlation may pass the confidence bound. We analyze the properties of two versions of the notion of confidence boost, one of them a natural generalization of the other. We develop efficient algorithmics to filter rules according to their confidence boost, compare the concept to some similar notions in the bibliography, and describe the results of some experimentation employing the new notions on standard benchmark datasets. We describe an open-source association mining tool that embodies one of our variants of confidence boost in such a way that the data mining process does not require the user to select any value for any parameter.


Design and classification of dynamic multi-objective optimization problems

Abstract: In this work we provide a formal model for the different time-dependent components that can appear in dynamic multi-objective optimization problems, along with a classification of these components. Four main classes are identified, corresponding to the influence of the parameters, objective functions, previous states of the dynamic system and, last, environment changes, which in turn lead to online optimization problems. For illustration purposes, examples are provided for each class identified - by no means standing as the most representative ones or exhaustive in scope.


Robust Additively Coupled Games

Abstract: We study the robust Nash equilibrium (RNE) for a class of games in communications systems and networks where the impact of users on each other is an additive function of their strategies. Each user measures this impact, which may be corrupted by uncertainty in feedback delays, estimation errors, movements of users, etc. To study the outcome of the game in which such uncertainties are encountered, we utilize the worst-case robust optimization theory. The existence and uniqueness conditions of RNE are derived using finite-dimensions variational inequalities. To describe the effect of uncertainty on the performance of the system, we use two criteria measured at the RNE and at the equilibrium of the game without uncertainty. The first is the difference between the respective social utility of users and, the second is the differences between the strategies of users at their respective equilibria. These differences are obtained for the case of a unique NE and multiple NEs. To reach the RNE, we propose a distributed algorithm based on the proximal response map and derive the conditions for its convergence. Simulations of the power control game in interference channels, and Jackson networks validate our analysis.


Robust Spectrum Sharing via Worst Case Approach

Abstract: This paper considers non-cooperative and fully-distributed power-allocation for secondary-users (SUs) in spectrum-sharing environments when normalized-interference to each secondary-user is uncertain. We model each uncertain parameter by the sum of its nominal (estimated) value and a bounded additive error in a convex set, and show that the allocated power always converges to its equilibrium, called robust Nash equilibrium (RNE). In the case of a bounded and symmetric uncertainty set, we show that the power allocation problem for each SU is simplified, and can be solved in a distributed manner. We derive the conditions for RNE's uniqueness and for convergence of the distributed algorithm; and show that the total throughput (social utility) is less than that at NE when RNE is unique. We also show that for multiple RNEs, the the social utility may be higher at a RNE as compared to that at the corresponding NE, and demonstrate that this is caused by SUs' orthogonal utilization of bandwidth for increasing the social utility. Simulations confirm our analysis.


Constructing and Sampling Graphs with a Prescribed Joint Degree Distribution

Abstract: One of the most influential recent results in network analysis is that many natural networks exhibit a power-law or log-normal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have the right degree distribution, they are not good models for real life networks due to their differences on other important metrics like conductance. We believe this is, in part, because many of these real-world networks have very different joint degree distributions, i.e. the probability that a randomly selected edge will be between nodes of degree k and l. Assortativity is a sufficient statistic of the joint degree distribution, and it has been previously noted that social networks tend to be assortative, while biological and technological networks tend to be disassortative. We suggest understanding the relationship between network structure and the joint degree distribution of graphs is an interesting avenue of further research. An important tool for such studies are algorithms that can generate random instances of graphs with the same joint degree distribution. This is the main topic of this paper and we study the problem from both a theoretical and practical perspective. We provide an algorithm for constructing simple graphs from a given joint degree distribution, and a Monte Carlo Markov Chain method for sampling them. We also show that the state space of simple graphs with a fixed degree distribution is connected via end point switches. We empirically evaluate the mixing time of this Markov Chain by using experiments based on the autocorrelation of each edge. These experiments show that our Markov Chain mixes quickly on real graphs, allowing for utilization of our techniques in practice.


Programming Massively Parallel Architectures using MARTE: a Case Study

Abstract: Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics Processing Unit), have led the race of floating-point performance since 2003. While the performance improvement of general- purpose microprocessors has slowed significantly, the GPUs have continued to improve relentlessly. As of 2009, the ratio between many-core GPUs and multicore CPUs for peak floating-point calculation throughput is about 10 times. However, as parallel programming requires a non-trivial distribution of tasks and data, developers find it hard to implement their applications effectively. Aiming to improve the use of many-core processors, this work presents an case-study using UML and MARTE profile to specify and generate OpenCL code for intensive signal processing applications. Benchmark results show us the viability of the use of MDE approaches to generate GPU applications.


Distribution-Independent Evolvability of Linear Threshold Functions

Abstract: Valiant's (2007) model of evolvability models the evolutionary process of acquiring useful functionality as a restricted form of learning from random examples. Linear threshold functions and their various subclasses, such as conjunctions and decision lists, play a fundamental role in learning theory and hence their evolvability has been the primary focus of research on Valiant's framework (2007). One of the main open problems regarding the model is whether conjunctions are evolvable distribution-independently (Feldman and Valiant, 2008). We show that the answer is negative. Our proof is based on a new combinatorial parameter of a concept class that lower-bounds the complexity of learning from correlations. We contrast the lower bound with a proof that linear threshold functions having a non-negligible margin on the data points are evolvable distribution-independently via a simple mutation algorithm. Our algorithm relies on a non-linear loss function being used to select the hypotheses instead of 0-1 loss in Valiant's (2007) original definition. The proof of evolvability requires that the loss function satisfies several mild conditions that are, for example, satisfied by the quadratic loss function studied in several other works (Michael, 2007; Feldman, 2009; Valiant, 2010). An important property of our evolution algorithm is monotonicity, that is the algorithm guarantees evolvability without any decreases in performance. Previously, monotone evolvability was only shown for conjunctions with quadratic loss (Feldman, 2009) or when the distribution on the domain is severely restricted (Michael, 2007; Feldman, 2009; Kanade et al., 2010)


A Reference Based, Tree Structured Time Synchronization Approach and its Analysis in WSN

Abstract: Time synchronization for wireless sensor networks (WSNs) has been studied in recent years as a fundamental and significant research issue. Many applications based on these WSNs assume local clocks at each sensor node that need to be synchronized to a common notion of time. Time synchronization in a WSN is critical for accurate time stamping of events and fine-tuned coordination among the sensor nodes to reduce power consumption. This paper proposes a bidirectional, reference based, tree structured time synchronization service for WSNs along with network evaluation phase. This offers a push mechanism for (i) accurate and (ii) low overhead for global time synchronization. Analysis study of proposed approach shows that it is lightweight as the number of required broadcasting messages is constant in one broadcasting domain.


Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform

Abstract: Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform. Numerical results show that the proposed algorithm can obtained higher peak signal to noise ratio (PSNR) than wavelet based denoising algorithms using MR Images in the presence of AWGN.


Automatic Open Space Area Extraction and Change Detection from High Resolution Urban Satellite Images

Abstract: In this paper, we study efficient and reliable automatic extraction algorithm to find out the open space area from the high resolution urban satellite imagery, and to detect changes from the extracted open space area during the period 2003, 2006 and 2008. This automatic extraction and change detection algorithm uses some filters, segmentation and grouping that are applied on satellite images. The resultant images may be used to calculate the total available open space area and the built up area. It may also be used to compare the difference between present and past open space area using historical urban satellite images of that same projection, which is an important geo spatial data management application.


Generating contour lines using different elevation data file formats

Abstract: In terrain mapping, there are so many ways to measure and estimate the terrain measurements like contouring, vertical profiling, hill shading, hypsometric tinting, perspective view, etc. Here in this paper we are using the contouring techniques to generate the contours for the different digital elevation data like DEM, HGT, IMG etc. The elevation data is captured in dem, hgt and img formats of the same projected area and the contour is generated using the existing techniques and applications. The exact differences, errors of elevation (contour) intervals, slopes and heights are analyzed and recovered.


Detection of Spatial Changes using Spatial Data Mining

Abstract: The Change detection based on analysis and samples are analyzed. Land use/cover change detection based on SDM is discussed.


An Introduction to Functional dependency in Relational Databases

Abstract: This write-up is the suggested lecture notes for a second level course on advanced topics in database systems for master's students of Computer Science with a theoretical focus. A prerequisite in algorithms and an exposure to database systems are required. Additional reading may require exposure to mathematical logic. The starting point for these notes are from M.Y.Vardi's survey listed herein as a reference - some of the proofs are presented as such . This select rewrite on functional dependency is intended to provide a few clarifications even though radically new design approaches are now being proposed.


On the Certification of the Restricted Isometry Property

Abstract: Compressed sensing is a technique for finding sparse solutions to underdetermined linear systems. This technique relies on properties of the sensing matrix such as the restricted isometry property. Sensing matrices that satisfy the restricted isometry property with optimal parameters are mainly obtained via probabilistic arguments. Given any matrix, deciding whether it satisfies the restricted isometry property is a non-trivial computational problem. In this paper, we give reductions from dense subgraph problems to the certification of the restricted isometry property. This gives evidence that certifying the restricted isometry property is unlikely to be feasible in polynomial-time. Moreover, on the positive side we propose an improvement on the brute-force enumeration algorithm for checking the restricted isometry property. Another contribution of independent interest is a spectral algorithm for certifying that a random graph does not contain any dense k-subgraph. This "skewed spectral algorithm" performs better than the basic spectral algorithm in a certain range of parameters.


Model Checking CTL is Almost Always Inherently Sequential

Abstract: The model checking problem for CTL is known to be P-complete (Clarke, Emerson, and Sistla (1986), see Schnoebelen (2002)). We consider fragments of CTL obtained by restricting the use of temporal modalities or the use of negations---restrictions already studied for LTL by Sistla and Clarke (1985) and Markey (2004). For all these fragments, except for the trivial case without any temporal operator, we systematically prove model checking to be either inherently sequential (P-complete) or very efficiently parallelizable (LOGCFL-complete). For most fragments, however, model checking for CTL is already P-complete. Hence our results indicate that, in cases where the combined complexity is of relevance, approaching CTL model checking by parallelism cannot be expected to result in any significant speedup. We also completely determine the complexity of the model checking problem for all fragments of the extensions ECTL, CTL+, and ECTL+.


User Modeling Combining Access Logs, Page Content and Semantics

Abstract: The paper proposes an approach to modeling users of large Web sites based on combining different data sources: access logs and content of the accessed pages are combined with semantic information about the Web pages, the users and the accesses of the users to the Web site. The assumption is that we are dealing with a large Web site providing content to a large number of users accessing the site. The proposed approach represents each user by a set of features derived from the different data sources, where some feature values may be missing for some users. It further enables user modeling based on the provided characteristics of the targeted user subset. The approach is evaluated on real-world data where we compare performance of the automatic assignment of a user to a predefined user segment when different data sources are used to represent the users.


On Understanding and Machine Understanding

Abstract: In the present paper, we try to propose a self-similar network theory for the basic understanding. By extending the natural languages to a kind of so called idealy sufficient language, we can proceed a few steps to the investigation of the language searching and the language understanding of AI. Image understanding, and the familiarity of the brain to the surrounding environment are also discussed. Group effects are discussed by addressing the essense of the power of influences, and constructing the influence network of a society. We also give a discussion of inspirations.


Ubiquitous Positioning: A Taxonomy for Location Determination on Mobile Navigation System

Abstract: The location determination in obstructed area can be very challenging especially if Global Positioning System are blocked. Users will find it difficult to navigate directly on-site in such condition, especially indoor car park lot or obstructed environment. Sometimes, it needs to combine with other sensors and positioning methods in order to determine the location with more intelligent, reliable and ubiquity. By using ubiquitous positioning in mobile navigation system, it is a promising ubiquitous location technique in a mobile phone since as it is a familiar personal electronic device for many people. However, as research on ubiquitous positioning systems goes beyond basic methods there is an increasing need for better comparison of proposed ubiquitous positioning systems. System developers are also lacking of good frameworks for understanding different options during building ubiquitous positioning systems. This paper proposes taxonomy to address both of these problems. The proposed taxonomy has been constructed from a literature study of papers and articles on positioning estimation that can be used to determine location everywhere on mobile navigation system. For researchers the taxonomy can also be used as an aid for scoping out future research in the area of ubiquitous positioning.


An Empirical Study of Real-World SPARQL Queries

Abstract: Understanding how users tailor their SPARQL queries is crucial when designing query evaluation engines or fine-tuning RDF stores with performance in mind. In this paper we analyze 3 million real-world SPARQL queries extracted from logs of the DBPedia and SWDF public endpoints. We aim at finding which are the most used language elements both from syntactical and structural perspectives, paying special attention to triple patterns and joins, since they are indeed some of the most expensive SPARQL operations at evaluation phase. We have determined that most of the queries are simple and include few triple patterns and joins, being Subject-Subject, Subject-Object and Object-Object the most common join types. The graph patterns are usually star-shaped and despite triple pattern chains exist, they are generally short.


Mining User Comment Activity for Detecting Forum Spammers in YouTube

Abstract: Research shows that comment spamming (comments which are unsolicited, unrelated, abusive, hateful, commercial advertisements etc) in online discussion forums has become a common phenomenon in Web 2.0 applications and there is a strong need to counter or combat comment spamming. We present a method to automatically detect comment spammer in YouTube (largest and a popular video sharing website) forums. The proposed technique is based on mining comment activity log of a user and extracting patterns (such as time interval between subsequent comments, presence of exactly same comment across multiple unrelated videos) indicating spam behavior. We perform empirical analysis on data crawled from YouTube and demonstrate that the proposed method is effective for the task of comment spammer detection.


Bounds and Inequalities Relating h-Index, g-Index, e-Index and Generalized Impact Factor

Abstract: Finding relationships among different indices such as h-index, g-index, e-index, and generalized impact factor is a challenging task. In this paper, we describe some bounds and inequalities relating h-index, g-index, e-index, and generalized impact factor. We derive the bounds and inequalities relating these indexing parameters from their basic definitions and without assuming any continuous model to be followed by any of them.


From Linked Data to Relevant Data -- Time is the Essence

Abstract: The Semantic Web initiative puts emphasis not primarily on putting data on the Web, but rather on creating links in a way that both humans and machines can explore the Web of data. When such users access the Web, they leave a trail as Web servers maintain a history of requests. Web usage mining approaches have been studied since the beginning of the Web given the log's huge potential for purposes such as resource annotation, personalization, forecasting etc. However, the impact of any such efforts has not really gone beyond generating statistics detailing who, when, and how Web pages maintained by a Web server were visited.


Nested Refinements for Dynamic Languages

Abstract: Programs written in dynamic languages make heavy use of features --- run-time type tests, value-indexed dictionaries, polymorphism, and higher-order functions --- that are beyond the reach of type systems that employ either purely syntactic or purely semantic reasoning. We present a core calculus, System D, that merges these two modes of reasoning into a single powerful mechanism of nested refinement types wherein the typing relation is itself a predicate in the refinement logic. System D coordinates SMT-based logical implication and syntactic subtyping to automatically typecheck sophisticated dynamic language programs. By coupling nested refinements with McCarthy's theory of finite maps, System D can precisely reason about the interaction of higher-order functions, polymorphism, and dictionaries. The addition of type predicates to the refinement logic creates a circularity that leads to unique technical challenges in the metatheory, which we solve with a novel stratification approach that we use to prove the soundness of System D.


Study of the effect of cost policies in the convergence of selfish strategies in Pure Nash Equilibria in Congestion Games

Abstract: In this work we study of competitive situations among users of a set of global resources. More precisely we study the effect of cost policies used by these resources in the convergence time to a pure Nash equilibrium. The work is divided in two parts. In the theoretical part we prove lower and upper bounds on the convergence time for various cost policies. We then implement all the models we study and provide some experimental results. These results follows the theoretical with one exception which is the most interesting among the experiments. In the case of coalitional users the theoretical upper bound is pseudo-polynomial to the number of users but the experimental results shows that the convergence time is polynomial.


Algorithms for computing the greatest simulations and bisimulations between fuzzy automata

Abstract: Recently, two types of simulations (forward and backward simulations) and four types of bisimulations (forward, backward, forward-backward, and backward-forward bisimulations) between fuzzy automata have been introduced. If there is at least one simulation/bisimulation of some of these types between the given fuzzy automata, it has been proved that there is the greatest simulation/bisimulation of this kind. In the present paper, for any of the above-mentioned types of simulations/bisimulations we provide an effective algorithm for deciding whether there is a simulation/bisimulation of this type between the given fuzzy automata, and for computing the greatest one, whenever it exists. The algorithms are based on the method developed in [J. Ignjatovi\'c, M. \'Ciri\'c, S. Bogdanovi\'c, On the greatest solutions to certain systems of fuzzy relation inequalities and equations, Fuzzy Sets and Systems 161 (2010) 3081-3113], which comes down to the computing of the greatest post-fixed point, contained in a given fuzzy relation, of an isotone function on the lattice of fuzzy relations.


Using Variable Threshold to Increase Capacity in a Feedback Neural Network

Abstract: The article presents new results on the use of variable thresholds to increase the capacity of a feedback neural network. Non-binary networks are also considered in this analysis.


Termination Proofs in the Dependency Pair Framework May Induce Multiple Recursive Derivational Complexity

Abstract: We study the derivational complexity of rewrite systems whose termination is provable in the dependency pair framework using the processors for reduction pairs, dependency graphs, or the subterm criterion. We show that the derivational complexity of such systems is bounded by a multiple recursive function, provided the derivational complexity induced by the employed base techniques is at most multiple recursive. Moreover we show that this upper bound is tight.


Data-Oblivious External-Memory Algorithms for the Compaction, Selection, and Sorting of Outsourced Data

Abstract: We present data-oblivious algorithms in the external-memory model for compaction, selection, and sorting. Motivation for such problems comes from clients who use outsourced data storage services and wish to mask their data access patterns. We show that compaction and selection can be done data-obliviously using $O(N/B)$ I/Os, and sorting can be done, with a high probability of success, using $O((N/B)\log_{M/B} (N/B))$ I/Os. Our methods use a number of new algorithmic techniques, including data-oblivious uses of invertible Bloom lookup tables, a butterfly-like compression network, randomized data thinning, and "shuffle-and-deal" data perturbation. In addition, since data-oblivious sorting is the bottleneck in the "inner loop" in existing oblivious RAM simulations, our sorting result improves the amortized time overhead to do oblivious RAM simulation by a logarithmic factor in the external-memory model.


Defeating Internet attacks and Spam using "disposable" Mobile IPv6 home addresses

Abstract: We propose a model of operation for next generation wireless Internet, in which a mobile host has hundreds of "disposable" Mobile IPv6 home addresses. Each correspondent is distributed a different disposable home address. If attacked on a given home address, the mobile user can block packets to that address and become unreachable to the attacker. Blocking one address does not affect other addresses. Other correspondents can still reach the mobile host. A new home address can also be requested via e-mail, instant messaging, or directly from the target host using a protocol that we develop. This model is especially useful against battery exhausting Denial-of-Service (DoS) attacks and CPU exhausting distributed DoS attacks, since it seems to be the only viable solution, currently. We show however that this model can also be used to defeat other attacks and also to stop spam.


A protocol for a message system for the tiles of the heptagrid, in the hyperbolic plane

Abstract: This paper introduces a communication system for the tiles of the heptagrid, a tiling of the hyperbolic plane. The method can be extended to other tilings of this plane. The paper focuses on an actual implementation at the programming stage with a short account of two experiments.


Progress of concepts and processes in library information system: towards Library 2.0

Abstract: The main principle of the Library 2.0 is in the fact that the information has to be spread from the library to the user and viceversa, to allow fast and permanent adaptation of the library services. Within the framework of the implementation of the "Departmental Plan of the Public Services Reading" by the "General Council of Moselle", the division of the public reading develops a departmental portal as main vector of the information with various users' profile. The context of this research work takes a part of a Master degree training Diploma in STI-Economic Intelligence (Nancy2 University), combining facets of R&D in a professional context at the "Conseil G\'en\'eral de la Moselle" in France.


A family of abstract interpretations for static analysis of concurrent higher-order programs

Abstract: We develop a framework for computing two foundational analyses for concurrent higher-order programs: (control-)flow analysis (CFA) and may-happen-in-parallel analysis (MHP). We pay special attention to the unique challenges posed by the unrestricted mixture of first-class continuations and dynamically spawned threads. To set the stage, we formulate a concrete model of concurrent higher-order programs: the P(CEK*)S machine. We find that the systematic abstract interpretation of this machine is capable of computing both flow and MHP analyses. Yet, a closer examination finds that the precision for MHP is poor. As a remedy, we adapt a shape analytic technique-singleton abstraction-to dynamically spawned threads (as opposed to objects in the heap). We then show that if MHP analysis is not of interest, we can substantially accelerate the computation of flow analysis alone by collapsing thread interleavings with a second layer of abstraction.


Game theoretic modeling of pilot behavior during mid-air encounters

Abstract: We show how to combine Bayes nets and game theory to predict the behavior of hybrid systems involving both humans and automated components. We call this novel framework "Semi Network-Form Games," and illustrate it by predicting aircraft pilot behavior in potential near mid-air collisions. At present, at the beginning of such potential collisions, a collision avoidance system in the aircraft cockpit advises the pilots what to do to avoid the collision. However studies of mid-air encounters have found wide variability in pilot responses to avoidance system advisories. In particular, pilots rarely perfectly execute the recommended maneuvers, despite the fact that the collision avoidance system's effectiveness relies on their doing so. Rather pilots decide their actions based on all information available to them (advisory, instrument readings, visual observations). We show how to build this aspect into a semi network-form game model of the encounter and then present computational simulations of the resultant model.


Differentially Private Spatial Decompositions

Abstract: Differential privacy has recently emerged as the de facto standard for private data release. This makes it possible to provide strong theoretical guarantees on the privacy and utility of released data. While it is well-known how to release data based on counts and simple functions under this guarantee, it remains to provide general purpose techniques to release different kinds of data. In this paper, we focus on spatial data such as locations and more generally any data that can be indexed by a tree structure. Directly applying existing differential privacy methods to this type of data simply generates noise. Instead, we introduce a new class of "private spatial decompositions": these adapt standard spatial indexing methods such as quadtrees and kd-trees to provide a private description of the data distribution. Equipping such structures with differential privacy requires several steps to ensure that they provide meaningful privacy guarantees. Various primitives, such as choosing splitting points and describing the distribution of points within a region, must be done privately, and the guarantees of the different building blocks composed to provide an overall guarantee. Consequently, we expose the design space for private spatial decompositions, and analyze some key examples. Our experimental study demonstrates that it is possible to build such decompositions efficiently, and use them to answer a variety of queries privately with high accuracy.


Encipher of information on the basis of geometrical presentations

Abstract: In this paper, we examine a ciphertext on the basis of using geometrical objects. Each symbol normative alphabet is determined as a point on the plane. We consider possible ways for presentation of these points.


On primary and secondary repetitions in words

Abstract: Combinatorial properties of maximal repetitions (runs) in formal words are studied. We classify all maximal repetitions in a word as primary and secondary where the set of all primary repetitions determines all the other repetitons in the word. Essential combinatorial properties of primary repetitions are established.


Computational Rationalization: The Inverse Equilibrium Problem

Abstract: Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior is an approximately optimal solution to an unknown decision problem. These techniques learn a utility function that explains the example behavior and can then be used to accurately predict or imitate future behavior in similar observed or unobserved situations. In this work, we consider similar tasks in competitive and cooperative multi-agent domains. Here, unlike single-agent settings, a player cannot myopically maximize its reward --- it must speculate on how the other agents may act to influence the game's outcome. Employing the game-theoretic notion of regret and the principle of maximum entropy, we introduce a technique for predicting and generalizing behavior, as well as recovering a reward function in these domains.


On the Correspondence between Display Postulates and Deep Inference in Nested Sequent Calculi for Tense Logics

Abstract: We consider two styles of proof calculi for a family of tense logics, presented in a formalism based on nested sequents. A nested sequent can be seen as a tree of traditional single-sided sequents. Our first style of calculi is what we call "shallow calculi", where inference rules are only applied at the root node in a nested sequent. Our shallow calculi are extensions of Kashima's calculus for tense logic and share an essential characteristic with display calculi, namely, the presence of structural rules called "display postulates". Shallow calculi enjoy a simple cut elimination procedure, but are unsuitable for proof search due to the presence of display postulates and other structural rules. The second style of calculi uses deep-inference, whereby inference rules can be applied at any node in a nested sequent. We show that, for a range of extensions of tense logic, the two styles of calculi are equivalent, and there is a natural proof theoretic correspondence between display postulates and deep inference. The deep inference calculi enjoy the subformula property and have no display postulates or other structural rules, making them a better framework for proof search.


Distributed k-Core Decomposition

Abstract: Among the novel metrics used to study the relative importance of nodes in complex networks, k-core decomposition has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system analysis and design. This paper proposes new distributed algorithms for the computation of the k-core decomposition of a network, with the purpose of (i) enabling the run-time computation of k-cores in "live" distributed systems and (ii) allowing the decomposition, over a set of connected machines, of very large graphs, that cannot be hosted in a single machine. Lower bounds on the algorithms complexity are given, and an exhaustive experimental analysis on real-world graphs is provided.


Context-free ordinals

Abstract: We consider context-free languages equipped with the lexicographic ordering. We show that when the lexicographic ordering of a context-free language is scattered, then its Hausdorff rank is less than $\omega^\omega$. As a corollary of this result we obtain that an ordinal is the order type of a well-ordered context-free language iff it is less than $\omega^{\omega^\omega}$.


Multifaceted Faculty Network Design and Management: Practice and Experience Report

Abstract: We report on our experience on multidimensional aspects of our faculty's network design and management, including some unique aspects such as campus-wide VLANs and ghosting, security and monitoring, switching and routing, and others. We outline a historical perspective on certain research, design, and development decisions and discuss the network topology, its scalability, and management in detail; the services our network provides, and its evolution. We overview the security aspects of the management as well as data management and automation and the use of the data by other members of the IT group in the faculty.


Using a Non-Commutative Bernstein Bound to Approximate Some Matrix Algorithms in the Spectral Norm

Abstract: We focus on \emph{row sampling} based approximations for matrix algorithms, in particular matrix multipication, sparse matrix reconstruction, and \math{\ell_2} regression. For \math{\matA\in\R^{m\times d}} (\math{m} points in \math{d\ll m} dimensions), and appropriate row-sampling probabilities, which typically depend on the norms of the rows of the \math{m\times d} left singular matrix of \math{\matA} (the \emph{leverage scores}), we give row-sampling algorithms with linear (up to polylog factors) dependence on the stable rank of \math{\matA}. This result is achieved through the application of non-commutative Bernstein bounds. Keywords: row-sampling; matrix multiplication; matrix reconstruction; estimating spectral norm; linear regression; randomized


Orthogonal Range Searching on the RAM, Revisited

Abstract: We present several new results on one of the most extensively studied topics in computational geometry, orthogonal range searching. All our results are in the standard word RAM model for points in rank space: ** We present two data structures for 2-d orthogonal range emptiness. The first achieves O(n lglg n) space and O(lglg n) query time. This improves the previous results by Alstrup, Brodal, and Rauhe(FOCS'00), with O(n lg^eps n) space and O(lglg n) query time, or with O(nlglg n) space and O(lg^2 lg n) query time. Our second data structure uses O(n) space and answers queries in O(lg^eps n) time. The best previous O(n)-space data structure, due to Nekrich (WADS'07), answers queries in O(lg n/lglg n) time. ** For 3-d orthogonal range reporting, we obtain space O(n lg^{1+eps} n) and query time O(lglg n + k), for any constant eps>0. This improves previous results by Afshani (ESA'08), Karpinski and Nekrich (COCOON'09), and Chan (SODA'11), with O(n lg^3 n) space and O(lglg n + k) query time, or with O(n lg^{1+eps} n) space and O(lg^2 lg n + k) query time. This implies improved bounds for orthogonal range reporting in all constant dimensions above 3. ** We give a randomized algorithm for 4-d offline dominance range reporting/emptiness with running time O(n lg n + k). This resolves two open problems from Preparata and Shamos' seminal book: **** given n axis-aligned rectangles in the plane, we can report all k enclosure pairs in O(n lg n + k) expected time. The best known result was an O([n lg n + k] lglg n) algorithm from SoCG'95 by Gupta, Janardan, Smid, and Dasgupta. **** given n points in 4-d, we can find all maximal points in O(n lg n) expected time. The best previous result was an O(n lg n lglg n) algorithm due to Gabow, Bentley, and Tarjan (STOC'84). This implies record time bounds for the maxima problem in all constant dimensions above 4.


Visual Localisation of Mobile Devices in an Indoor Environment under Network Delay Conditions

Abstract: Current progresses in home automation and service robotic environment have highlighted the need to develop interoperability mechanisms that allow a standard communication between the two systems. During the development of the DHCompliant protocol, the problem of locating mobile devices in an indoor environment has been investigated. The communication of the device with the location service has been carried out to study the time delay that web services offer in front of the sockets. The importance of obtaining data from real-time location systems portends that a basic tool for interoperability, such as web services, can be ineffective in this scenario because of the delays added in the invocation of services. This paper is focused on introducing a web service to resolve a coordinates request without any significant delay in comparison with the sockets.


On the Complexity of Edge Packing and Vertex Packing

Abstract: This paper studies the computational complexity of the Edge Packing problem and the Vertex Packing problem. The edge packing problem (denoted by $\bar{EDS}$) and the vertex packing problem (denoted by $\bar{DS} $) are linear programming duals of the edge dominating set problem and the dominating set problem respectively. It is shown that these two problems are equivalent to the set packing problem with respect to hardness of approximation and parametric complexity. It follows that $\bar{EDS}$ and $\bar{DS}$ cannot be approximated asymptotically within a factor of $O(N^{1/2-\epsilon})$ for any $\epsilon>0$ unless $NP=ZPP$ where, $N$ is the number of vertices in the given graph. This is in contrast with the fact that the edge dominating set problem is 2-approximable where as the dominating set problem is known to have an $O(\log$ $|V|)$ approximation algorithm. It also follows from our proof that $\bar{EDS}$ and $\bar{DS}$ are $W[1]$-complete.


Designing a Miniature Wheel Arrangement for Mobile Robot Platforms

Abstract: In this research report details of design of a miniature wheel arrangement are presented. This miniature wheel arrangement is essentially a direction control mechanism intended for use on a mobile robot platform or base. The design is a specific one employing a stepper motor as actuator and as described can only be used on a certain type of wheeled robots. However, as a basic steering control element, more than one of these miniature wheel arrangements can be grouped together to implement more elaborate and intelligent direction control schemes on varying configurations of wheeled mobile robot platforms.


A Comparison of Link Layer Attacks on Wireless Sensor Networks

Abstract: Wireless sensor networks (WSNs) have many potential applications [1, 5] and unique challenges. They usually consist of hundreds or thousands small sensor nodes such as MICA2, which operate autonomously; conditions such as cost, invisible deployment and many application domains, lead to small size and limited resources sensors [2]. WSNs are susceptible to many types of link layer attacks [1] and most of traditional networks security techniques are unusable on WSNs [2]; due to wireless and shared nature of communication channel, untrusted transmissions, deployment in open environments, unattended nature and limited resources [1]. So, security is a vital requirement for these networks; but we have to design a proper security mechanism that attends to WSN's constraints and requirements. In this paper, we focus on security of WSNs, divide it (the WSNs security) into four categories and will consider them, include: an overview of WSNs, security in WSNs, the threat model on WSNs, a wide variety of WSNs' link layer attacks and a comparison of them. This work enables us to identify the purpose and capabilities of the attackers; also, the goal and effects of the link layer attacks on WSNs are introduced. Also, this paper discusses known approaches of security detection and defensive mechanisms against the link layer attacks; this would enable it security managers to manage the link layer attacks of WSNs more effectively.


Polynomial kernels for Proper Interval Completion and related problems

Abstract: Given a graph G = (V,E) and a positive integer k, the Proper Interval Completion problem asks whether there exists a set F of at most k pairs of (V \times V)\E such that the graph H = (V,E \cup F) is a proper interval graph. The Proper Interval Completion problem finds applications in molecular biology and genomic research. First announced by Kaplan, Tarjan and Shamir in FOCS '94, this problem is known to be FPT, but no polynomial kernel was known to exist. We settle this question by proving that Proper Interval Completion admits a kernel with at most O(k^5) vertices. Moreover, we prove that a related problem, the so-called Bipartite Chain Deletion problem, admits a kernel with at most O(k^2) vertices, completing a previous result of Guo.


Recoverable Values for Independent Sets

Abstract: The notion of {\em recoverable value} was advocated in work of Feige, Immorlica, Mirrokni and Nazerzadeh [Approx 2009] as a measure of quality for approximation algorithms. There this concept was applied to facility location problems. In the current work we apply a similar framework to the maximum independent set problem (MIS). We say that an approximation algorithm has {\em recoverable value} $\rho$, if for every graph it recovers an independent set of size at least $\max_I \sum_{v\in I} \min[1,\rho/(d(v) + 1)]$, where $d(v)$ is the degree of vertex $v$, and $I$ ranges over all independent sets in $G$. Hence, in a sense, from every vertex $v$ in the maximum independent set the algorithm recovers a value of at least $\rho/(d_v + 1)$ towards the solution. This quality measure is most effective in graphs in which the maximum independent set is composed of low degree vertices. It easily follows from known results that some simple algorithms for MIS ensure $\rho \ge 1$. We design a new randomized algorithm for MIS that ensures an expected recoverable value of at least $\rho \ge 7/3$. In addition, we show that approximating MIS in graphs with a given $k$-coloring within a ratio larger than $2/k$ is unique games hard. This rules out a natural approach for obtaining $\rho \ge 2$.


To Parallelize or Not to Parallelize, Speed Up Issue

Abstract: Running parallel applications requires special and expensive processing resources to obtain the required results within a reasonable time. Before parallelizing serial applications, some analysis is recommended to be carried out to decide whether it will benefit from parallelization or not. In this paper we discuss the issue of speed up gained from parallelization using Message Passing Interface (MPI) to compromise between the overhead of parallelization cost and the gained parallel speed up. We also propose an experimental method to predict the speed up of MPI applications.


Application of Threshold Techniques for Readability Improvement of Jawi Historical Manuscript Images

Abstract: Historical documents such as old books and manuscripts have a high aesthetic value and highly appreciated. Unfortunately, there are some documents cannot be read due to quality problems like faded paper, ink expand, uneven colour tone, torn paper and other elements disruption such as the existence of small spots. The study aims to produce a copy of manuscript that shows clear wordings so they can easily be read and the copy can also be displayed for visitors. 16 samples of Jawi historical manuscript with different quality problems were obtained from The Royal Museum of Pahang, Malaysia. We applied three binarization techniques; Otsu's method represents global threshold technique; Sauvola and Niblack method which are categorized as local threshold techniques. We compared the binarized images with the original manuscript to be visually inspected by the museum's curator. The unclear features were marked and analyzed. Most of the examined images show that with optimal parameters and effective pre processing technique, local thresholding methods are work well compare with the other one. Niblack's and Sauvola's techniques seem to be the suitable approaches for these types of images. Most of binarized images with these two methods show improvement for readability and character recognition. For this research, even the differences of image result were hard to be distinguished by human capabilities, after comparing the time cost and overall achievement rate of recognized symbols, Niblack's method is performing better than Sauvola's. We could improve the post processing step by adding edge detection techniques and further enhanced by an innovative image refinement technique and a formulation of a class proper method.


Symmetry of information and bounds on nonuniform randomness extraction via Kolmogorov extractors

Abstract: We prove a strong Symmetry of Information relation for random strings (in the sense of Kolmogorov complexity) and establish tight bounds on the amount on nonuniformity that is necessary for extracting a string with randomness rate 1 from a single source of randomness. More precisely, as instantiations of more general results, we show: (1) For all n-bit random strings x and y, x is random conditioned by y if and only if y is random conditioned by x, and (2) while O(1) amount of advice regarding the source is not enough for extracting a string with randomness rate 1 from a source string with constant random rate, \omega(1) amount of advice is. The proofs use Kolmogorov extractors as the main technical device.


Codeco: A Grammar Notation for Controlled Natural Language in Predictive Editors

Abstract: Existing grammar frameworks do not work out particularly well for controlled natural languages (CNL), especially if they are to be used in predictive editors. I introduce in this paper a new grammar notation, called Codeco, which is designed specifically for CNLs and predictive editors. Two different parsers have been implemented and a large subset of Attempto Controlled English (ACE) has been represented in Codeco. The results show that Codeco is practical, adequate and efficient.


Binary words avoiding a pattern and marked succession rule

Abstract: In this paper we study the enumeration and the construction of particular binary words avoiding the pattern $1^{j+1}0^j$. By means of the theory of Riordan arrays, we solve the enumeration problem and we give a particular succession rule, called jumping and marked succession rule, which describes the growth of such words according to their number of ones. Moreover, the problem of associating a word to a path in the generating tree obtained by the succession rule is solved by introducing an algorithm which constructs all binary words and then kills those containing the forbidden pattern.


Poster Abstract: If You Have Time, Save Energy with Pull

Abstract: We analyze push and pull for data collection in wireless sensor networks. Most applications to date use the traditional push approach, where nodes transmit sensed data immedi- ately to the sink. Using a pull approach, nodes store the data in their local flash memory, and only engage in commu- nication during dedicated collection phases. We show how one can transform an existing push-based collection protocol into a pull-based one, and compare the power consumption of both approaches on a 35-node testbed. Our results show that substantial energy gains are possible with pull, provided that the application can tolerate a long latency.


Key Management in Wireless Sensor Networks Using a Modified Blom Scheme

Abstract: Key establishment between any pair of nodes is an essential requirement for providing secure services in wireless sensor networks. Blom's scheme is a prominent key management scheme but its shortcomings include large computation overhead and memory cost. We propose a new scheme in this paper that modifies Blom's scheme in a manner that reduces memory and computation costs. This paper also provides the value for secure parameter t such that the network is resilient.


Load Balancing in a Networked Environment through Homogenization

Abstract: Distributed processing across a networked environment suffers from unpredictable behavior of speedup due to heterogeneous nature of the hardware and software in the remote machines. It is challenging to get a better performance from a distributed system by distributing task in an intelligent manner such that the heterogeneous nature of the system do not have any effect on the speedup ratio. This paper introduces homogenization, a technique that distributes and balances the workload in such a manner that the user gets the highest speedup possible from a distributed environment. Along with providing better performance, homogenization is totally transparent to the user and requires no interaction with the system.


Triangular Dynamic Architecture for Distributed Computing in a LAN Environment

Abstract: A computationally intensive large job, granulized to concurrent pieces and operating in a dynamic environment should reduce the total processing time. However, distributing jobs across a networked environment is a tedious and difficult task. Job distribution in a Local Area Network based on Triangular Dynamic Architecture (TDA) is a mechanism that establishes a dynamic environment for job distribution, load balancing and distributed processing with minimum interaction from the user. This paper introduces TDA and discusses its architecture and shows the benefits gained by utilizing such architecture in a distributed computing environment.


Agent Based Processing of Global Evaluation Function

Abstract: Load balancing across a networked environment is a monotonous job. Moreover, if the job to be distributed is a constraint satisfying one, the distribution of load demands core intelligence. This paper proposes parallel processing through Global Evaluation Function by means of randomly initialized agents for solving Constraint Satisfaction Problems. A potential issue about the number of agents in a machine under the invocation of distribution is discussed here for securing the maximum benefit from Global Evaluation and parallel processing. The proposed system is compared with typical solution that shows an exclusive outcome supporting the nobility of parallel implementation of Global Evaluation Function with certain number of agents in each invoked machine.


Image Encryption Using Differential Evolution Approach in Frequency Domain

Abstract: This paper presents a new effective method for image encryption which employs magnitude and phase manipulation using Differential Evolution (DE) approach. The novelty of this work lies in deploying the concept of keyed discrete Fourier transform (DFT) followed by DE operations for encryption purpose. To this end, a secret key is shared between both encryption and decryption sides. Firstly two dimensional (2-D) keyed discrete Fourier transform is carried out on the original image to be encrypted. Secondly crossover is performed between two components of the encrypted image, which are selected based on Linear Feedback Shift Register (LFSR) index generator. Similarly, keyed mutation is performed on the real parts of a certain components selected based on LFSR index generator. The LFSR index generator initializes it seed with the shared secret key to ensure the security of the resulting indices. The process shuffles the positions of image pixels. A new image encryption scheme based on the DE approach is developed which is composed with a simple diffusion mechanism. The deciphering process is an invertible process using the same key. The resulting encrypted image is found to be fully distorted, resulting in increasing the robustness of the proposed work. The simulation results validate the proposed image encryption scheme.


A Review of Interference Reduction in Wireless Networks Using Graph Coloring Methods

Abstract: The interference imposes a significant negative impact on the performance of wireless networks. With the continuous deployment of larger and more sophisticated wireless networks, reducing interference in such networks is quickly being focused upon as a problem in today's world. In this paper we analyze the interference reduction problem from a graph theoretical viewpoint. A graph coloring methods are exploited to model the interference reduction problem. However, additional constraints to graph coloring scenarios that account for various networking conditions result in additional complexity to standard graph coloring. This paper reviews a variety of algorithmic solutions for specific network topologies.


The Space Complexity of Long-lived and One-Shot Timestamp Implementations

Abstract: This paper is concerned with the problem of implementing an unbounded timestamp object from multi-writer atomic registers, in an asynchronous distributed system of n processors with distinct identifiers where timestamps are taken from an arbitrary universe. Ellen, Fatourou and Ruppert (2008) showed that sqrt{n}/2-O(1) registers are required for any obstruction-free implementation of long-lived timestamp systems from atomic registers (meaning processors can repeatedly get timestamps). We improve this existing lower bound in two ways. First we establish a lower bound of n/6 - O(1) registers for the obstruction-free long-lived timestamp problem. Previous such linear lower bounds were only known for constrained versions of the timestamp problem. This bound is asymptotically tight; Ellen, Fatourou and Ruppert (2008) constructed a wait-free algorithm that uses n-1 registers. Second we show that sqrt{n} - O(1) registers are required for any obstruction-free implementation of one-shot timestamp systems(meaning each processor can get a timestamp at most once). We show that this bound is also asymptotically tight by providing a wait-free one-shot timestamp system that uses fewer than 2 sqrt{n} registers, thus establishing a space complexity gap between one-shot and long-lived timestamp systems.


Heuristic Algorithm for Interpretation of Non-Atomic Categorical Attributes in Similarity-based Fuzzy Databases - Scalability Evaluation

Abstract: In this work we are analyzing scalability of the heuristic algorithm we used in the past to discover knowledge from multi-valued symbolic attributes in fuzzy databases. The non-atomic descriptors, characterizing a single attribute of a database record, are commonly used in fuzzy databases to reflect uncertainty about the recorded observation. In this paper, we present implementation details and scalability tests of the algorithm, which we developed to precisely interpret such non-atomic values and to transfer (i.e. defuzzify) the fuzzy tuples to the forms acceptable for many regular (i.e. atomic values based) data mining algorithms. Important advantages of our approach are: (1) its linear scalability, and (2) its unique capability of incorporating background knowledge, implicitly stored in the fuzzy database models in the form of fuzzy similarity hierarchy, into the interpretation/defuzzification process.


Computational Complexity Results for Genetic Programming and the Sorting Problem

Abstract: Genetic Programming (GP) has found various applications. Understanding this type of algorithm from a theoretical point of view is a challenging task. The first results on the computational complexity of GP have been obtained for problems with isolated program semantics. With this paper, we push forward the computational complexity analysis of GP on a problem with dependent program semantics. We study the well-known sorting problem in this context and analyze rigorously how GP can deal with different measures of sortedness.


Improved Edge Awareness in Discontinuity Preserving Smoothing

Abstract: Discontinuity preserving smoothing is a fundamentally important procedure that is useful in a wide variety of image processing contexts. It is directly useful for noise reduction, and frequently used as an intermediate step in higher level algorithms. For example, it can be particularly useful in edge detection and segmentation. Three well known algorithms for discontinuity preserving smoothing are nonlinear anisotropic diffusion, bilateral filtering, and mean shift filtering. Although slight differences make them each better suited to different tasks, all are designed to preserve discontinuities while smoothing. However, none of them satisfy this goal perfectly: they each have exception cases in which smoothing may occur across hard edges. The principal contribution of this paper is the identification of a property we call edge awareness that should be satisfied by any discontinuity preserving smoothing algorithm. This constraint can be incorporated into existing algorithms to improve quality, and usually has negligible changes in runtime performance and/or complexity. We present modifications necessary to augment diffusion and mean shift, as well as a new formulation of the bilateral filter that unifies the spatial and range spaces to achieve edge awareness.


Using Short Message Service (SMS) to Support Business Continuity

Abstract: Now a day's many organizations are required to communicate online on a daily basis, 24-hour, seven-days-a-week, to gain the desired competitive advantages and profits; although there are a variety of disruptions that may occur within business application such as broken (off-line) database-links and unhanded database exceptions. Such cases will end the automated business work, and force business users to continue business procedures and functionalities via paper work, which causes additional resources with less business competitive advantages. In this paper, we will propose a new model in which we embed short message services (SMS) within business applications using the SMS Gateway such as "Ozeki Message Server", and programmed application packages. By using our proposed model, we can maintain business continuity when a partial disruption occurs and then switch to our application model. As a result to the experimental work, we conclude that our model supports business continuity since it supports the account balance modification while the database link is disrupted. In addition, we carried out each step twice and the scenario was reliable since all of its steps were reliable.


A Comparative Case Study of Code Reuse With Language Oriented Programming

Abstract: There is a gap between our ability to reuse high-level concepts in software design and our ability to reuse the code implementing them. Language Oriented Programming (LOP) is a software development paradigm that aims to close this gap, through extensive use of Domain Specific Languages (DSLs). With LOP, the high-level reusable concepts become reusable DSL constructs, and their translation into code level concepts is done in the DSL implementation. Particular products are implemented using DSL code, thus reusing only high-level concepts. In this paper we provide a comparison between two implementation approaches for LOP: (a) using external DSLs with a projectional language workbench (MPS); and (b) using internal DSLs with an LOP language (Cedalion). To demonstrate how reuse is achieved in each approach, we present a small case study, where LOP is used to build a Software Product Line (SPL) of calculator software.


Abstract Processes of Place/Transition Systems

Abstract: A well-known problem in Petri net theory is to formalise an appropriate causality-based concept of process or run for place/transition systems. The so-called individual token interpretation, where tokens are distinguished according to their causal history, giving rise to the processes of Goltz and Reisig, is often considered too detailed. The problem of defining a fully satisfying more abstract concept of process for general place/transition systems has so-far not been solved. In this paper, we recall the proposal of defining an abstract notion of process, here called BD-process, in terms of equivalence classes of Goltz-Reisig processes, using an equivalence proposed by Best and Devillers. It yields a fully satisfying solution for at least all one-safe nets. However, for certain nets which intuitively have different conflicting behaviours, it yields only one maximal abstract process. Here we identify a class of place/transition systems, called structural conflict nets, where conflict and concurrency due to token multiplicity are clearly separated. We show that, in the case of structural conflict nets, the equivalence proposed by Best and Devillers yields a unique maximal abstract process only for conflict-free nets. Thereby BD-processes constitute a simple and fully satisfying solution in the class of structural conflict nets.


Multi-path Routing Metrics for Reliable Wireless Mesh Routing Topologies

Abstract: Several emerging classes of applications that run over wireless networks have a need for mathematical models and tools to systematically characterize the reliability of the network. We propose two metrics for measuring the reliability of wireless mesh routing topologies, one for flooding and one for unicast routing. The Flooding Path Probability (FPP) metric measures the end-to-end packet delivery probability when each node broadcasts a packet after hearing from all its upstream neighbors. The Unicast Retransmission Flow (URF) metric measures the end-to-end packet delivery probability when a relay node retransmits a unicast packet on its outgoing links until it receives an acknowledgement or it tries all the links. Both metrics rely on specific packet forwarding models, rather than heuristics, to derive explicit expressions of the end-to-end packet delivery probability from individual link probabilities and the underlying connectivity graph. We also propose a distributed, greedy algorithm that uses the URF metric to construct a reliable routing topology. This algorithm constructs a Directed Acyclic Graph (DAG) from a weighted, undirected connectivity graph, where each link is weighted by its success probability. The algorithm uses a vector of decreasing reliability thresholds to coordinate when nodes can join the routing topology. Simulations demonstrate that, on average, this algorithm constructs a more reliable topology than the usual minimum hop DAG.


LIFO-search on digraphs: A searching game for cycle-rank

Abstract: We consider the extension of the last-in-first-out graph searching game of Giannopoulou and Thilikos to digraphs. We show that all common variations of the game require the same number of searchers, and the minimal number of searchers required is one more than the cycle-rank of the digraph. We also obtain a tight duality theorem, giving a precise min-max characterization of obstructions for cycle-rank.


Buffer Overflow Management with Class Segregation

Abstract: We consider a new model for buffer management of network switches with Quality of Service (QoS) requirements. A stream of packets, each attributed with a value representing its Class of Service (CoS), arrives over time at a network switch and demands a further transmission. The switch is equipped with multiple queues of limited capacities, where each queue stores packets of one value only. The objective is to maximize the total value of the transmitted packets (i.e., the weighted throughput). We analyze a natural greedy algorithm, GREEDY, which sends in each time step a packet with the greatest value. For general packet values $(v_1 < \cdots < v_m)$, we show that GREEDY is $(1+r)$-competitive, where $r = \max_{1\le i \le m-1} \{v_i/v_{i+1}\}$. Furthermore, we show a lower bound of $2 - v_m / \sum_{i=1}^m v_i$ on the competitiveness of any deterministic online algorithm. In the special case of two packet values (1 and $\alpha > 1$), GREEDY is shown to be optimal with a competitive ratio of $(\alpha + 2)/(\alpha + 1)$.


Internal Constraints of the Trifocal Tensor

Abstract: The fundamental matrix and trifocal tensor are convenient algebraic representations of the epipolar geometry of two and three view configurations, respectively. The estimation of these entities is central to most reconstruction algorithms, and a solid understanding of their properties and constraints is therefore very important. The fundamental matrix has 1 internal constraint which is well understood, whereas the trifocal tensor has 8 independent algebraic constraints. The internal tensor constraints can be represented in many ways, although there is only one minimal and sufficient set of 8 constraints known. In this paper, we derive a second set of minimal and sufficient constraints that is simpler. We also show how this can be used in a new parameterization of the trifocal tensor. We hope that this increased understanding of the internal constraints may lead to improved algorithms for estimating the trifocal tensor, although the primary contribution is an improved theoretical understanding.


Colorful Triangle Counting and a MapReduce Implementation

Abstract: In this note we introduce a new randomized algorithm for counting triangles in graphs. We show that under mild conditions, the estimate of our algorithm is strongly concentrated around the true number of triangles. Specifically, if $p \geq \max{(\frac{\Delta \log{n}}{t}, \frac{\log{n}}{\sqrt{t}})}$, where $n$, $t$, $\Delta$ denote the number of vertices in $G$, the number of triangles in $G$, the maximum number of triangles an edge of $G$ is contained, then for any constant $\epsilon>0$ our unbiased estimate $T$ is concentrated around its expectation, i.e., $ \Prob{|T - \Mean{T}| \geq \epsilon \Mean{T}} = o(1)$. Finally, we present a \textsc{MapReduce} implementation of our algorithm.


Automatic Performance Debugging of SPMD-style Parallel Programs

Abstract: The simple program and multiple data (SPMD) programming model is widely used for both high performance computing and Cloud computing. In this paper, we design and implement an innovative system, AutoAnalyzer, that automates the process of debugging performance problems of SPMD-style parallel programs, including data collection, performance behavior analysis, locating bottlenecks, and uncovering their root causes. AutoAnalyzer is unique in terms of two features: first, without any apriori knowledge, it automatically locates bottlenecks and uncovers their root causes for performance optimization; second, it is lightweight in terms of the size of performance data to be collected and analyzed. Our contributions are three-fold: first, we propose two effective clustering algorithms to investigate the existence of performance bottlenecks that cause process behavior dissimilarity or code region behavior disparity, respectively; meanwhile, we present two searching algorithms to locate bottlenecks; second, on a basis of the rough set theory, we propose an innovative approach to automatically uncovering root causes of bottlenecks; third, on the cluster systems with two different configurations, we use two production applications, written in Fortran 77, and one open source code-MPIBZIP2 (http://compression.ca/mpibzip2/), written in C++, to verify the effectiveness and correctness of our methods. For three applications, we also propose an experimental approach to investigating the effects of different metrics on locating bottlenecks.


The Impact of Memory Models on Software Reliability in Multiprocessors

Abstract: The memory consistency model is a fundamental system property characterizing a multiprocessor. The relative merits of strict versus relaxed memory models have been widely debated in terms of their impact on performance, hardware complexity and programmability. This paper adds a new dimension to this discussion: the impact of memory models on software reliability. By allowing some instructions to reorder, weak memory models may expand the window between critical memory operations. This can increase the chance of an undesirable thread-interleaving, thus allowing an otherwise-unlikely concurrency bug to manifest. To explore this phenomenon, we define and study a probabilistic model of shared-memory parallel programs that takes into account such reordering. We use this model to formally derive bounds on the \emph{vulnerability} to concurrency bugs of different memory models. Our results show that for 2 (or a small constant number of) concurrent threads, weaker memory models do indeed have a higher likelihood of allowing bugs. On the other hand, we show that as the number of parallel threads increases, the gap between the different memory models becomes proportionally insignificant. This suggests the counter-intuitive rule that \emph{as the number of parallel threads in the system increases, the importance of using a strict memory model diminishes}; which potentially has major implications on the choice of memory consistency models in future multi-core systems.


Cook's Theory and the Twentieth Century Mathematics

Abstract: A comprehensive review on Cook's contribution in the theory of NP-Completeness with relations to modern mathematics.


QCSP on partially reflexive forests

Abstract: We study the (non-uniform) quantified constraint satisfaction problem QCSP(H) as H ranges over partially reflexive forests. We obtain a complexity-theoretic dichotomy: QCSP(H) is either in NL or is NP-hard. The separating condition is related firstly to connectivity, and thereafter to accessibility from all vertices of H to connected reflexive subgraphs. In the case of partially reflexive paths, we give a refinement of our dichotomy: QCSP(H) is either in NL or is Pspace-complete.


Sparse Vector Distributions and Recovery from Compressed Sensing

Abstract: It is well known that the performance of sparse vector recovery algorithms from compressive measurements can depend on the distribution underlying the non-zero elements of a sparse vector. However, the extent of these effects has yet to be explored, and formally presented. In this paper, I empirically investigate this dependence for seven distributions and fifteen recovery algorithms. The two morals of this work are: 1) any judgement of the recovery performance of one algorithm over that of another must be prefaced by the conditions for which this is observed to be true, including sparse vector distributions, and the criterion for exact recovery; and 2) a recovery algorithm must be selected carefully based on what distribution one expects to underlie the sensed sparse signal.


DOLFIN: Automated Finite Element Computing

Abstract: We describe here a library aimed at automating the solution of partial differential equations using the finite element method. By employing novel techniques for automated code generation, the library combines a high level of expressiveness with efficient computation. Finite element variational forms may be expressed in near mathematical notation, from which low-level code is automatically generated, compiled and seamlessly integrated with efficient implementations of computational meshes and high-performance linear algebra. Easy-to-use object-oriented interfaces to the library are provided in the form of a C++ library and a Python module. This paper discusses the mathematical abstractions and methods used in the design of the library and its implementation. A number of examples are presented to demonstrate the use of the library in application code.


Bayesian Mechanism Design for Budget-Constrained Agents

Abstract: We study Bayesian mechanism design problems in settings where agents have budgets. Specifically, an agent's utility for an outcome is given by his value for the outcome minus any payment he makes to the mechanism, as long as the payment is below his budget, and is negative infinity otherwise. This discontinuity in the utility function presents a significant challenge in the design of good mechanisms, and classical "unconstrained" mechanisms fail to work in settings with budgets. The goal of this paper is to develop general reductions from budget-constrained Bayesian MD to unconstrained Bayesian MD with small loss in performance. We consider this question in the context of the two most well-studied objectives in mechanism design---social welfare and revenue---and present constant factor approximations in a number of settings. Some of our results extend to settings where budgets are private and agents need to be incentivized to reveal them truthfully.


Capacity of Byzantine Consensus with Capacity-Limited Point-to-Point Links

Abstract: We consider the problem of maximizing the throughput of Byzantine consensus, when communication links have finite capacity. Byzantine consensus is a classical problem in distributed computing. In existing literature, the communication links are implicitly assumed to have infinite capacity. The problem changes significantly when the capacity of links is finite. We define the throughput and capacity of consensus, and identify upper bound of achievable consensus throughput. We propose an algorithm that achieves consensus capacity in complete four-node networks with at most 1 failure with arbitrary distribution of link capacities.


Distributed Denial of Service is a Scalability Problem

Abstract: Distributed denial of service attacks are often considered a security problem. While this may be the way to view the problem with today's Internet, new network architectures attempting to address the issue should view it as a scalability problem. In addition, they need to address the problem based on a rigorous foundation.