Disseny d'un prototipus de xarxa MESH sense fils multir\'adio i multicanal sobre OLSR modificat amb canal de senyalitzaci\'o dedicat

Abstract: Wireless mesh cubes are used to improve the channel signaling.


Search space analysis with Wang-Landau sampling and slow adaptive walks

Abstract: Two complementary techniques for analyzing search spaces are proposed: (i) an algorithm to detect search points with potential to be local optima; and (ii) a slightly adjusted Wang-Landau sampling algorithm to explore larger search spaces. The detection algorithm assumes that local optima are points which are easier to reach and harder to leave by a slow adaptive walker. A slow adaptive walker moves to a nearest fitter point. Thus, points with larger outgoing step sizes relative to incoming step sizes are marked using the local optima score formulae as potential local optima points (PLOPs). Defining local optima in these more general terms allows their detection within the closure of a subset of a search space, and the sampling of a search space unshackled by a particular move set. Tests are done with NK and HIFF problems to confirm that PLOPs detected in the manner proposed retain characteristics of local optima, and that the adjusted Wang-Landau samples are more representative of the search space than samples produced by choosing points uniformly at random. While our approach shows promise, more needs to be done to reduce its computation cost that it may pave a way toward analyzing larger search spaces of practical meaning.


Multispectral Palmprint Recognition Using a Hybrid Feature

Abstract: Personal identification problem has been a major field of research in recent years. Biometrics-based technologies that exploit fingerprints, iris, face, voice and palmprints, have been in the center of attention to solve this problem. Palmprints can be used instead of fingerprints that have been of the earliest of these biometrics technologies. A palm is covered with the same skin as the fingertips but has a larger surface, giving us more information than the fingertips. The major features of the palm are palm-lines, including principal lines, wrinkles and ridges. Using these lines is one of the most popular approaches towards solving the palmprint recognition problem. Another robust feature is the wavelet energy of palms. In this paper we used a hybrid feature which combines both of these features. %Moreover, multispectral analysis is applied to improve the performance of the system. At the end, minimum distance classifier is used to match test images with one of the training samples. The proposed algorithm has been tested on a well-known multispectral palmprint dataset and achieved an average accuracy of 98.8\%.


Neighbor Discovery in a Wireless Sensor Network: Multipacket Reception Capability and Physical-Layer Signal Processing

Abstract: In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its \textit{neighbor} nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning \textit{sets}, rather than values, to random outcomes. The contributions in the paper are twofold: first, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of \textit{logical} discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the \textit{double} uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.


Cayley configuration spaces of 2D mechanisms, Part I: extreme points, continuous motion paths and minimal representations

Abstract: We consider longstanding questions concerning configuration spaces of 1-dof tree-decomposable linkages in 2D. By employing the notion Cayley configuration space, i.e., a set of intervals of realizable distance-values for an independent non-edge, we answer the following. (1) How to measure the complexity of the configuration space and efficiently compute that of low algebraic complexity? (2) How to restrict the Cayley configuration space to be a single interval? (3) How to efficiently obtain continuous motion paths between realizations? (4) How to bijectively represent of the Cartesian realization space as a curve in an ambient space of minimum dimension? (5) How robust is the complexity measure (1) and how to efficiently classify linkages according to it? In Part I of this paper, we deal with problems (1)-(4) by introducing the notions of (a) Cayley size, the number of intervals in the Cayley configuration space, (b) Cayley computational complexity of computing the interval endpoints, and (c) Cayley (algebraic) complexity of describing the interval endpoints. Specifically (i) We give an algorithm to find the interval endpoints of a Cayley configuration spac. For graphs with low Cayley complexity, we give the following. (ii) A natural, minimal set of local orientations, whose specification guarantees Cayley size of 1 and $O(|V|^2)$ Cayley computational complexity. Specifying fewer local orientations results in a superpolynomial blow-up of both Cayley size and computational complexity, provided P is different from NP. (iii) An algorithm--for generic linkages--to find a path of continuous motion (provided exists) between two given realizations, in time linear in a natural measure of path length. (iv) A canonical bijective representation of the Cartesian realization space in minimal ambient dimension, also for generic linkages.


Cayley Configuration Spaces of 1-dof Tree-decomposable Linkages, Part II: Combinatorial Characterization of Complexity

Abstract: We continue to study Cayley configuration spaces of 1-dof linkages in 2D begun in Part I of this paper, i.e. the set of attainable lengths for a non-edge. In Part II, we focus on the algebraic complexity of describing endpoints of the intervals in the set, i.e., the Cayley complexity. Specifically, We focus on Cayley configuration spaces of a natural class of 1-dof linkages, called 1-dof tree-decomposable linkages. The underlying graphs G satisfy the following: for some base non-edge f, G \cup f is quadratic-radically solvable (QRS), meaning that G \cup f is minimally rigid, and given lengths \bar{l} of all edges, the corresponding linkage (G \cup f, \bar{l}) can be simply realized by ruler and compass starting from f. It is clear that the Cayley complexity only depends on the graph G and possibly the non-edge f. Here we ask whether the Cayley complexity depends on the choice of a base non-edge f. We answer this question in the negative, thereby showing that low Cayley complexity is a property of the graph G (independent of the non-edge f). Then, we give a simple characterization of graphs with low Cayley complexity, leading to an efficient algorithmic characterization, i.e. an efficient algorithm for recognizing such graphs. Next, we show a surprising result that (graph) planarity is equivalent to low Cayley complexity for a natural subclass of 1-dof triangle-decomposable graphs. While this is a finite forbidden minor graph characterization of low Cayley complexity, we provide counterexamples showing impossibility of such finite forbidden minor characterizations when the above subclass is enlarged.


A self-rendering digital image encoding

Abstract: Without careful long-term preservation digital data may be lost to a number of factors, including physical media decay, lack of suitable decoding equipment, and the absence of software. When raw data can be read but lack suitable annotations as to provenance, the ability to interpret them is more straightforward if they can be assessed through simple visual techniques. In this regard digital images are a special case since their data have a natural representation on two-dimensional media surfaces. This paper presents a novel binary image pixel encoding that produces an approximate analog rendering of encoded images when the image bits are arranged spatially in an appropriate manner. This simultaneous digital and analog representation acts to inseparably annotate bits as image data, which may contribute to the longevity of so-encoded images.


Characterization of $2^n$-periodic binary sequences with fixed 3-error or 4-error linear complexity

Abstract: The linear complexity and the $k$-error linear complexity of a sequence have been used as important security measures for key stream sequence strength in linear feedback shift register design. By using the sieve method of combinatorics, the $k$-error linear complexity distribution of $2^n$-periodic binary sequences is investigated based on Games-Chan algorithm. First, for $k=2,3$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity less than $2^n$ are characterized. Second, for $k=3,4$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity $2^n$ are presented. Third, for $k=4,5$, the complete counting functions on the $k$-error linear complexity of $2^n$-periodic binary sequences with linear complexity less than $2^n$ are derived. As a consequence of these results, the counting functions for the number of $2^n$-periodic binary sequences with the 3-error linear complexity are obtained, and the complete counting functions on the 4-error linear complexity of $2^n$-periodic binary sequences are obvious.


Multi-Connected Ontologies

Abstract: Ontologies have been used for the purpose of bringing system and consistency to subject and knowledge areas. We present a criticism of the present mathematical structure of ontologies and indicate that they are not sufficient in their present form to represent the many different valid expressions of a subject knowledge domain. We propose an alternative structure for ontologies based on a richer multi connected complex network which contains the present ontology structure as a projection. We demonstrate how this new multi connected ontology should be represented as an asymmetric probability matrix.


Solving XCSP problems by using Gecode

Abstract: Gecode is one of the most efficient libraries that can be used for constraint solving. However, using it requires dealing with C++ programming details. On the other hand several formats for representing constraint networks have been proposed. Among them, XCSP has been proposed as a format based on XML which allows us to represent constraints defined either extensionally or intensionally, permits global constraints and has been the standard format of the international competition of constraint satisfaction problems solvers. In this paper we present a plug-in for solving problems specified in XCSP by exploiting the Gecode solver. This is done by dynamically translating constraints into Gecode library calls, thus avoiding the need to interact with C++.


Your browsing behavior for a Big Mac: Economics of Personal Information Online

Abstract: Most online services (Google, Facebook etc.) operate by providing a service to users for free, and in return they collect and monetize personal information (PI) of the users. This operational model is inherently economic, as the "good" being traded and monetized is PI. This model is coming under increased scrutiny as online services are moving to capture more PI of users, raising serious privacy concerns. However, little is known on how users valuate different types of PI while being online, as well as the perceptions of users with regards to exploitation of their PI by online service providers. In this paper, we study how users valuate different types of PI while being online, while capturing the context by relying on Experience Sampling. We were able to extract the monetary value that 168 participants put on different pieces of PI. We find that users value their PI related to their offline identities more (3 times) than their browsing behavior. Users also value information pertaining to financial transactions and social network interactions more than activities like search and shopping. We also found that while users are overwhelmingly in favor of exchanging their PI in return for improved online services, they are uncomfortable if these same providers monetize their PI.


The guarding game is E-complete

Abstract: The guarding game is a game in which several cops try to guard a region in a (directed or undirected) graph against Robber. Robber and the cops are placed on the vertices of the graph; they take turns in moving to adjacent vertices (or staying), cops inside the guarded region, Robber on the remaining vertices (the robber-region). The goal of Robber is to enter the guarded region at a vertex with no cop on it. The problem is to determine whether for a given graph and given number of cops the cops are able to prevent Robber from entering the guarded region. Fomin et al. [Fomin, Golovach, Hall, Mihalak, Vicari, Widmayer: How to Guard a Graph? Algorithmica 61(4), 839--856 (2011)] proved that the problem is NP-complete when the robber-region is restricted to a tree. Further they prove that is it PSPACE-complete when the robber-region is restricted to a directed acyclic graph, and they ask about the problem complexity for arbitrary graphs. In this paper we prove that the problem is E-complete for arbitrary directed graphs.


A general framework for online audio source separation

Abstract: We consider the problem of online audio source separation. Existing algorithms adopt either a sliding block approach or a stochastic gradient approach, which is faster but less accurate. Also, they rely either on spatial cues or on spectral cues and cannot separate certain mixtures. In this paper, we design a general online audio source separation framework that combines both approaches and both types of cues. The model parameters are estimated in the Maximum Likelihood (ML) sense using a Generalised Expectation Maximisation (GEM) algorithm with multiplicative updates. The separation performance is evaluated as a function of the block size and the step size and compared to that of an offline algorithm.


Building high-level features using large scale unsupervised learning

Abstract: We consider the problem of building high-level, class-specific feature detectors from only unlabeled data. For example, is it possible to learn a face detector using only unlabeled images? To answer this, we train a 9-layered locally connected sparse autoencoder with pooling and local contrast normalization on a large dataset of images (the model has 1 billion connections, the dataset has 10 million 200x200 pixel images downloaded from the Internet). We train this network using model parallelism and asynchronous SGD on a cluster with 1,000 machines (16,000 cores) for three days. Contrary to what appears to be a widely-held intuition, our experimental results reveal that it is possible to train a face detector without having to label images as containing a face or not. Control experiments show that this feature detector is robust not only to translation but also to scaling and out-of-plane rotation. We also find that the same network is sensitive to other high-level concepts such as cat faces and human bodies. Starting with these learned features, we trained our network to obtain 15.8% accuracy in recognizing 20,000 object categories from ImageNet, a leap of 70% relative improvement over the previous state-of-the-art.


Document Clustering based on Topic Maps

Abstract: Importance of document clustering is now widely acknowledged by researchers for better management, smart navigation, efficient filtering, and concise summarization of large collection of documents like World Wide Web (WWW). The next challenge lies in semantically performing clustering based on the semantic contents of the document. The problem of document clustering has two main components: (1) to represent the document in such a form that inherently captures semantics of the text. This may also help to reduce dimensionality of the document, and (2) to define a similarity measure based on the semantic representation such that it assigns higher numerical values to document pairs which have higher semantic relationship. Feature space of the documents can be very challenging for document clustering. A document may contain multiple topics, it may contain a large set of class-independent general-words, and a handful class-specific core-words. With these features in mind, traditional agglomerative clustering algorithms, which are based on either Document Vector model (DVM) or Suffix Tree model (STC), are less efficient in producing results with high cluster quality. This paper introduces a new approach for document clustering based on the Topic Map representation of the documents. The document is being transformed into a compact form. A similarity measure is proposed based upon the inferred information through topic maps data and structures. The suggested method is implemented using agglomerative hierarchal clustering and tested on standard Information retrieval (IR) datasets. The comparative experiment reveals that the proposed approach is effective in improving the cluster quality.


A comparison of two suffix tree-based document clustering algorithms

Abstract: Document clustering as an unsupervised approach extensively used to navigate, filter, summarize and manage large collection of document repositories like the World Wide Web (WWW). Recently, focuses in this domain shifted from traditional vector based document similarity for clustering to suffix tree based document similarity, as it offers more semantic representation of the text present in the document. In this paper, we compare and contrast two recently introduced approaches to document clustering based on suffix tree data model. The first is an Efficient Phrase based document clustering, which extracts phrases from documents to form compact document representation and uses a similarity measure based on common suffix tree to cluster the documents. The second approach is a frequent word/word meaning sequence based document clustering, it similarly extracts the common word sequence from the document and uses the common sequence/ common word meaning sequence to perform the compact representation, and finally, it uses document clustering approach to cluster the compact documents. These algorithms are using agglomerative hierarchical document clustering to perform the actual clustering step, the difference in these approaches are mainly based on extraction of phrases, model representation as a compact document, and the similarity measures used for clustering. This paper investigates the computational aspect of the two algorithms, and the quality of results they produced.


Scheduling Light-trails in WDM Rings

Abstract: We consider the problem of scheduling communication on optical WDM (wavelength division multiplexing) networks using the light-trails technology. We seek to design scheduling algorithms such that the given transmission requests can be scheduled using minimum number of wavelengths (optical channels). We provide algorithms and close lower bounds for two versions of the problem on an $n$ processor linear array/ring network. In the {\em stationary} version, the pattern of transmissions (given) is assumed to not change over time. For this, a simple lower bound is $c$, the congestion or the maximum total traffic required to pass through any link. We give an algorithm that schedules the transmissions using $O(c+\log{n})$ wavelengths. We also show a pattern for which $\Omega(c+\log{n}/\log\log{n})$ wavelengths are needed. In the {\em on-line} version, the transmissions arrive and depart dynamically, and must be scheduled without upsetting the previously scheduled transmissions. For this case we give an on-line algorithm which has competitive ratio $\Theta(\log{n})$. We show that this is optimal in the sense that every on-line algorithm must have competitive ratio $\Omega(\log{n})$. We also give an algorithm that appears to do well in simulation (for the classes of traffic we consider), but which has competitive ratio between $\Omega(\log^2n/\log \log{n})$ and $O(\log^2n)$. We present detailed simulations of both our algorithms.


On group feedback vertex set parameterized by the size of the cutset

Abstract: We study the parameterized complexity of a robust generalization of the classical Feedback Vertex Set problem, namely the Group Feedback Vertex Set problem; we are given a graph G with edges labeled with group elements, and the goal is to compute the smallest set of vertices that hits all cycles of G that evaluate to a non-null element of the group. This problem generalizes not only Feedback Vertex Set, but also Subset Feedback Vertex Set, Multiway Cut and Odd Cycle Transversal. Completing the results of Guillemot [Discr. Opt. 2011], we provide a fixed-parameter algorithm for the parameterization by the size of the cutset only. Our algorithm works even if the group is given as a polynomial-time oracle.


(1+epsilon)-Distance Oracle for Planar Labeled Graph

Abstract: Given a vertex-labeled graph, each vertex $v$ is attached with a label from a set of labels. The vertex-label query desires the length of the shortest path from the given vertex to the set of vertices with the given label. We show how to construct an oracle if the given graph is planar, such that $O(\frac{1}{\epsilon}n\log n)$ storing space is needed, and any vertex-label query could be answered in $O(\frac{1}{\epsilon}\log n\log \rho)$ time with stretch $1+\epsilon$. $\rho$ is the radius of the given graph, which is half of the diameter. For the case that $\rho = O(\log n)$, we construct an oracle that achieves $O(\log n)$ query time, without changing the order of storing space.


On the Complexity of Solving Quadratic Boolean Systems

Abstract: A fundamental problem in computer science is to find all the common zeroes of $m$ quadratic polynomials in $n$ unknowns over $\mathbb{F}_2$. The cryptanalysis of several modern ciphers reduces to this problem. Up to now, the best complexity bound was reached by an exhaustive search in $4\log_2 n\,2^n$ operations. We give an algorithm that reduces the problem to a combination of exhaustive search and sparse linear algebra. This algorithm has several variants depending on the method used for the linear algebra step. Under precise algebraic assumptions on the input system, we show that the deterministic variant of our algorithm has complexity bounded by $O(2^{0.841n})$ when $m=n$, while a probabilistic variant of the Las Vegas type has expected complexity $O(2^{0.792n})$. Experiments on random systems show that the algebraic assumptions are satisfied with probability very close to~1. We also give a rough estimate for the actual threshold between our method and exhaustive search, which is as low as~200, and thus very relevant for cryptographic applications.


Short Proofs for the Determinant Identities

Abstract: We study arithmetic proof systems P_c(F) and P_f(F) operating with arithmetic circuits and arithmetic formulas, respectively, that prove polynomial identities over a field F. We establish a series of structural theorems about these proof systems, the main one stating that P_c(F) proofs can be balanced: if a polynomial identity of syntactic degree d and depth k has a P_c(F) proof of size s, then it also has a P_c(F) proof of size poly(s,d) and depth O(k+\log^2 d + \log d\cd \log s). As a corollary, we obtain a quasipolynomial simulation of P_c(F) by P_f(F), for identities of a polynomial syntactic degree. Using these results we obtain the following: consider the identities det(XY) = det(X)det(Y) and det(Z)= z_{11}... z_{nn}, where X,Y and Z are nxn square matrices and Z is a triangular matrix with z_{11},..., z_{nn} on the diagonal (and det is the determinant polynomial). Then we can construct a polynomial-size arithmetic circuit det such that the above identities have P_c(F) proofs of polynomial-size and O(\log^2 n) depth. Moreover, there exists an arithmetic formula det of size n^{O(\log n)} such that the above identities have P_f(F) proofs of size n^{O(\log n)}. This yields a solution to a basic open problem in propositional proof complexity, namely, whether there are polynomial-size NC^2-Frege proofs for the determinant identities and the hard matrix identities, as considered, e.g., in Soltys and Cook (2004) (cf., Beame and Pitassi (1998)). We show that matrix identities like AB=I {\to} BA=I (for matrices over the two element field) as well as basic properties of the determinant have polynomial-size NC^2-Frege proofs, and quasipolynomial-size Frege proofs.


Automated PolyU Palmprint sample Registration and Coarse Classification

Abstract: Biometric based authentication for secured access to resources has gained importance, due to their reliable, invariant and discriminating features. Palmprint is one such biometric entity. Prior to classification and identification registering a sample palmprint is an important activity. In this paper we propose a computationally effective method for automated registration of samples from PlolyU palmprint database. In our approach we preprocess the sample and trace the border to find the nearest point from center of sample. Angle between vector representing the nearest point and vector passing through the center is used for automated palm sample registration. The angle of inclination between start and end point of heart line and life line is used for basic classification of palmprint samples in left class and right class.


Percentile Ranks and the Integrated Impact Indicator (I3)

Abstract: We tested Rousseau's (in press) recent proposal to define percentile classes in the case of the Integrated Impact Indicator (I3) so that the largest number in a set always belongs to the highest (100th) percentile rank class. In the case a set of nine uncited papers and one with citation, however, the uncited papers would all be placed in the 90th percentile rank. A lowly-cited document set would thus be advantaged when compared with a highly-cited one. Notwithstanding our reservations, we extended the program for computing I3 in Web-of-Science data (at http://www.leydesdorff.net/software/i3) with this option; the quantiles without a correction are now the default. As Rousseau mentions, excellence indicators (e.g., the top-10%) can be considered as special cases of I3: only two percentile rank classes are distinguished for the evaluation. Both excellence and impact indicators can be tested statistically using the z-test for independent proportions.


Visualization and Analysis of Frames in Collections of Messages: Content Analysis and the Measurement of Meaning

Abstract: A step-to-step introduction is provided on how to generate a semantic map from a collection of messages (full texts, paragraphs or statements) using freely available software and/or SPSS for the relevant statistics and the visualization. The techniques are discussed in the various theoretical contexts of (i) linguistics (e.g., Latent Semantic Analysis), (ii) sociocybernetics and social systems theory (e.g., the communication of meaning), and (iii) communication studies (e.g., framing and agenda-setting). We distinguish between the communication of information in the network space (social network analysis) and the communication of meaning in the vector space. The vector space can be considered a generated as an architecture by the network of relations in the network space; words are then not only related, but also positioned. These positions are expected rather than observed and therefore one can communicate meaning. Knowledge can be generated when these meanings can recursively be communicated and therefore also further codified.


Descriptor learning for omnidirectional image matching

Abstract: Feature matching in omnidirectional vision systems is a challenging problem, mainly because complicated optical systems make the theoretical modelling of invariance and construction of invariant feature descriptors hard or even impossible. In this paper, we propose learning invariant descriptors using a training set of similar and dissimilar descriptor pairs. We use the similarity-preserving hashing framework, in which we are trying to map the descriptor data to the Hamming space preserving the descriptor similarity on the training set. A neural network is used to solve the underlying optimization problem. Our approach outperforms not only straightforward descriptor matching, but also state-of-the-art similarity-preserving hashing methods.


Block local elimination algorithms for solving sparse discrete optimization problems

Abstract: Block elimination algorithms for solving sparse discrete optimization problems are considered. The numerical example is provided. The benchmarking is done in order to define real computational capabilities of block elimination algorithms combined with SYMPHONY solver. Analysis of the results show that for sufficiently large number of blocks and small enough size of separators between the blocks for staircase integer linear programming problem the local elimination algorithms in combination with a solver for solving subproblems in blocks allow to solve such problems much faster than used solver itself for solving the whole problem. Also the capabilities of postoptimal analysis (warm starting) are considered for solving packages of integer linear programming problems for corresponding blocks.


On Multiple Round Sponsored Search Auctions with Budgets

Abstract: In a sponsored search auction the advertisement slots on a search result page are generally ordered by click-through rate. Bidders have a valuation, which is usually assumed to be linear in the click-through rate, a budget constraint, and receive at most one slot per search result page (round). We study multi-round sponsored search auctions, where the different rounds are linked through the budget constraints of the bidders and the valuation of a bidder for all rounds is the sum of the valuations for the individual rounds. All mechanisms published so far either study one-round sponsored search auctions or the setting where every round has only one slot and all slots have the same click-through rate, which is identical to a multi-item auction. This paper contains the following three results: (1) We give the first mechanism for the multi-round sponsored search problem where different slots have different click-through rates. Our mechanism is incentive compatible in expectation, individually rational in expectation, Pareto optimal in expectation, and also ex-post Pareto optimal for each realized outcome. (2) Additionally we study the combinatorial setting, where each bidder is only interested in a subset of the rounds. We give a deterministic, incentive compatible, individually rational, and Pareto optimal mechanism for the setting where all slots have the same click-through rate. (3) We present an impossibility result for auctions where bidders have diminishing marginal valuations. Specifically, we show that even for the multi-unit (one slot per round) setting there is no incentive compatible, individually rational, and Pareto optimal mechanism for private diminishing marginal valuations and public budgets.


Proof nets for the Lambek-Grishin calculus

Abstract: Grishin's generalization of Lambek's Syntactic Calculus combines a non-commutative multiplicative conjunction and its residuals (product, left and right division) with a dual family: multiplicative disjunction, right and left difference. Interaction between these two families takes the form of linear distributivity principles. We study proof nets for the Lambek-Grishin calculus and the correspondence between these nets and unfocused and focused versions of its sequent calculus.


Two-Manifold Problems

Abstract: Recently, there has been much interest in spectral approaches to learning manifolds---so-called kernel eigenmap methods. These methods have had some successes, but their applicability is limited because they are not robust to noise. To address this limitation, we look at two-manifold problems, in which we simultaneously reconstruct two related manifolds, each representing a different view of the same data. By solving these interconnected learning problems together and allowing information to flow between them, two-manifold algorithms are able to succeed where a non-integrated approach would fail: each view allows us to suppress noise in the other, reducing bias in the same way that an instrumental variable allows us to remove bias in a {linear} dimensionality reduction problem. We propose a class of algorithms for two-manifold problems, based on spectral decomposition of cross-covariance operators in Hilbert space. Finally, we discuss situations where two-manifold problems are useful, and demonstrate that solving a two-manifold problem can aid in learning a nonlinear dynamical system from limited data.


Effects for Funargs

Abstract: Stack allocation and first-class functions don't naturally mix together. In this paper we show that a type and effect system can be the detergent that helps these features form a nice emulsion. Our interest in this problem comes from our work on the Chapel language, but this problem is also relevant to lambda expressions in C++ and blocks in Objective C. The difficulty in mixing first-class functions and stack allocation is a tension between safety, efficiency, and simplicity. To preserve safety, one must worry about functions outliving the variables they reference: the classic upward funarg problem. There are systems which regain safety but lose programmer-predictable efficiency, and ones that provide both safety and efficiency, but give up simplicity by exposing regions to the programmer. In this paper we present a simple design that combines a type and effect system, for safety, with function-local storage, for control over efficiency.


Well-typed Islands Parse Faster

Abstract: This paper addresses the problem of specifying and parsing the syntax of domain-specific languages (DSLs) in a modular, user-friendly way. That is, we want to enable the design of composable DSLs that combine the natural syntax of external DSLs with the easy implementation of internal DSLs. The challenge in parsing composable DSLs is that the composition of several (individually unambiguous) languages is likely to contain ambiguities. In this paper, we present the design of a system that uses a type-oriented variant of island parsing to efficiently parse the syntax of composable DSLs. In particular, we show how type-oriented island parsing is constant time with respect to the number of DSLs imported. We also show how to use our tool to implement DSLs on top of a host language such as Typed Racket.


The C++0x "Concepts" Effort

Abstract: C++0x is the working title for the revision of the ISO standard of the C++ programming language that was originally planned for release in 2009 but that was delayed to 2011. The largest language extension in C++0x was "concepts", that is, a collection of features for constraining template parameters. In September of 2008, the C++ standards committee voted the concepts extension into C++0x, but then in July of 2009, the committee voted the concepts extension back out of C++0x. This article is my account of the technical challenges and debates within the "concepts" effort in the years 2003 to 2009. To provide some background, the article also describes the design space for constrained parametric polymorphism, or what is colloquially know as constrained generics. While this article is meant to be generally accessible, the writing is aimed toward readers with background in functional programming and programming language theory. This article grew out of a lecture at the Spring School on Generic and Indexed Programming at the University of Oxford, March 2010.


The Maximum Clique Problem in Multiple Interval Graphs

Abstract: Multiple interval graphs are variants of interval graphs where instead of a single interval, each vertex is assigned a set of intervals on the real line. We study the complexity of the MAXIMUM CLIQUE problem in several classes of multiple interval graphs. The MAXIMUM CLIQUE problem, or the problem of finding the size of the maximum clique, is known to be NP-complete for $t$-interval graphs when $t\geq 3$ and polynomial-time solvable when $t=1$. The problem is also known to be NP-complete in $t$-track graphs when $t\geq 4$ and polynomial-time solvable when $t\leq 2$. We show that MAXIMUM CLIQUE is already NP-complete for unit 2-interval graphs and unit 3-track graphs. Further, we show that the problem is APX-complete for 2-interval graphs, 3-track graphs, unit 3-interval graphs and unit 4-track graphs. We also introduce two new classes of graphs called $t$-circular interval graphs and $t$-circular track graphs and study the complexity of the MAXIMUM CLIQUE problem in them. On the positive side, we present a polynomial time $t$-approximation algorithm for WEIGHTED MAXIMUM CLIQUE on $t$-interval graphs, improving earlier work with approximation ratio $4t$.


Computing Cartograms with Optimal Complexity

Abstract: In a rectilinear dual of a planar graph vertices are represented by simple rectilinear polygons and edges are represented by side-contact between the corresponding polygons. A rectilinear dual is called a cartogram if the area of each region is equal to a pre-specified weight of the corresponding vertex. The complexity of a cartogram is determined by the maximum number of corners (or sides) required for any polygon. In a series of papers the polygonal complexity of such representations for maximal planar graphs has been reduced from the initial 40 to 34, then to 12 and very recently to the currently best known 10. Here we describe a construction with 8-sided polygons, which is optimal in terms of polygonal complexity as 8-sided polygons are sometimes necessary. Specifically, we show how to compute the combinatorial structure and how to refine the representation into an area-universal rectangular layout in linear time. The exact cartogram can be computed from the area-universal rectangular layout with numerical iteration, or can be approximated with a hill-climbing heuristic. We also describe an alternative construction for Hamiltonian maximal planar graphs, which allows us to directly compute the cartograms in linear time. Moreover, we prove that even for Hamiltonian graphs 8-sided rectilinear polygons are necessary, by constructing a non-trivial lower bound example. The complexity of the cartograms can be reduced to 6 if the Hamiltonian path has the extra property that it is one-legged, as in outer-planar graphs. Thus, we have optimal representations (in terms of both polygonal complexity and running time) for Hamiltonian maximal planar and maximal outer-planar graphs.


Fast B-spline Curve Fitting by L-BFGS

Abstract: We propose a novel method for fitting planar B-spline curves to unorganized data points. In traditional methods, optimization of control points and foot points are performed in two very time-consuming steps in each iteration: 1) control points are updated by setting up and solving a linear system of equations; and 2) foot points are computed by projecting each data point onto a B-spline curve. Our method uses the L-BFGS optimization method to optimize control points and foot points simultaneously and therefore it does not need to perform either matrix computation or foot point projection in every iteration. As a result, our method is much faster than existing methods.


Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks

Abstract: In this paper, a family of ant colony algorithms called DAACA for data aggregation has been presented which contains three phases: the initialization, packet transmission and operations on pheromones. After initialization, each node estimates the remaining energy and the amount of pheromones to compute the probabilities used for dynamically selecting the next hop. After certain rounds of transmissions, the pheromones adjustment is performed periodically, which combines the advantages of both global and local pheromones adjustment for evaporating or depositing pheromones. Four different pheromones adjustment strategies are designed to achieve the global optimal network lifetime, namely Basic-DAACA, ES-DAACA, MM-DAACA and ACS-DAACA. Compared with some other data aggregation algorithms, DAACA shows higher superiority on average degree of nodes, energy efficiency, prolonging the network lifetime, computation complexity and success ratio of one hop transmission. At last we analyze the characteristic of DAACA in the aspects of robustness, fault tolerance and scalability.


A Localization Method for the Internet of Things

Abstract: Many localization algorithms and systems have been developed by means of wireless sensor networks for both indoor and outdoor environments. To achieve higher localization accuracy, extra hardware equipments are utilized by most of the existing localization solutions, which increase the cost and considerably limit the location-based applications. The Internet of Things (IOT) integrates many technologies, such as Internet, Zigbee, Bluetooth, infrared, WiFi, GPRS, 3G, etc, which can enable different ways to obtain the location information of various objects. Location-based service is a primary service of the IOT, while localization accuracy is a key issue. In this paper, a higher accuracy localization scheme is proposed which can effectively satisfy diverse requirements for many indoor and outdoor location services. The proposed scheme composes of two phases: 1) partition phase, in which the target region is split into small grids; 2) localization refinement phase, in which a higher accuracy of localization can be obtained by applying an algorithm designed in the paper. A trial system is set up to verify correctness of the proposed scheme and furthermore to illustrate its feasibility and availability. The experimental results show that the proposed scheme can improve the localization accuracy.


Faster Subset Selection for Matrices and Applications

Abstract: We study subset selection for matrices defined as follows: given a matrix $\matX \in \R^{n \times m}$ ($m > n$) and an oversampling parameter $k$ ($n \le k \le m$), select a subset of $k$ columns from $\matX$ such that the pseudo-inverse of the subsampled matrix has as smallest norm as possible. In this work, we focus on the Frobenius and the spectral matrix norms. We describe several novel (deterministic and randomized) approximation algorithms for this problem with approximation bounds that are optimal up to constant factors. Additionally, we show that the combinatorial problem of finding a low-stretch spanning tree in an undirected graph corresponds to subset selection, and discuss various implications of this reduction.


A Comparative Study of Location Management Schemes: Challenges and Guidelines

Abstract: One of the key issues in mobile communication is to find the current location of mobile terminal (MT) to deliver the services, which is called as location management (LM). Increasing users and diverse services demand for a high-quality skeleton for LM. As an MT moves within a cellular network, it registers its new location to the nearest base station (BS). When a call arrives for an MT, the network searches the target MT in the area where it was last registered. This paper presents comprehensive classification of existing major LM schemes, their comparative study and factors influencing their performance. Finally, guidelines for developing and rating a LM scheme are suggested with the help of LPCIC rule, which is the main contribution of this paper.


A Fault-Tolerant Emergency-Aware Access Control Scheme for Cyber-Physical Systems

Abstract: Access control is an issue of paramount importance in cyber-physical systems (CPS). In this paper, an access control scheme, namely FEAC, is presented for CPS. FEAC can not only provide the ability to control access to data in normal situations, but also adaptively assign emergency-role and permissions to specific subjects and inform subjects without explicit access requests to handle emergency situations in a proactive manner. In FEAC, emergency-group and emergency-dependency are introduced. Emergencies are processed in sequence within the group and in parallel among groups. A priority and dependency model called PD-AGM is used to select optimal response-action execution path aiming to eliminate all emergencies that occurred within the system. Fault-tolerant access control polices are used to address failure in emergency management. A case study of the hospital medical care application shows the effectiveness of FEAC.


A Failure Self-recovery Strategy with Balanced Energy Consumption for Wireless Ad Hoc Networks

Abstract: In energy constrained wireless sensor networks, it is significant to make full use of the limited energy and maximize the network lifetime even when facing some unexpected situation. In this paper, all sensor nodes are grouped into clusters, and for each cluster, it has a mobile cluster head to manage the whole cluster. We consider an emergent situation that one of the mobile cluster heads is broken down, and hence the whole cluster is consequently out of work. An efficient approach is proposed for recovering the failure cluster by selecting multiple static sensor nodes as the cluster heads to collect packets and transmit them to the sink node. Improved simulated annealing algorithm is utilized to achieve the uniform deployment of the cluster heads. The new cluster heads are dynamically changed in order to keep balanced energy consumption. Among the new cluster heads, packets are transmitted through multi-hop forwarding path which is cost-lowest path found by Dijkstra's algorithm. A balanced energy consumption model is provided to help find the cost-lowest path and prolong the lifetime of the network. The forwarding path is updated dynamically according to the cost of the path and residual energy of the node in that path. The experimental results show that the failure cluster is recovered and the lifetime of the cluster is prolonged.


A Hop-by-hop Cross-layer Congestion Control Scheme for Wireless Sensor Networks

Abstract: Congestions in wireless sensor networks (WSNs) could potentially cause packet loss, throughput impairment and energy waste. To address this issue, a hop-by-hop cross-layer congestion control scheme (HCCC) built on contention-based MAC protocol is proposed in this paper. According to MAC-layer channel information including buffer occupancy ratio and congestion degree of local node, HCCC dynamically adjusts channel access priority in MAC layer and data transmission rate of the node to tackle the problem of congestion. Simulations have been conducted to compare HCCC against closely-related existing schemes. The results show that HCCC exhibits considerable superiority in terms of packets loss ratio, throughput and energy efficiency.


Real-Time Performance Analysis of Infrastructure-based IEEE 802.11 Distributed Coordination Function

Abstract: With the increasing popularity of wireless networks, wireless local area networks (WLANs) have attracted significant research interest, which play a critical role in providing anywhere and anytime connectivity. For WLANs the IEEE 802.11 standard is the most mature technology and has been widely adopted for wireless networks. This paper analyzes real-time performance of the IEEE 802.11 standard that adopts the MAC protocol of Distributed Coordination Function (DCF) operating in infrastructure mode. Extensive simulations have been done to examine how the network performance in terms of realtime metrics including effective data rate, latency and packet loss rate will be impacted by some critical parameters (e.g. CWmin and packet payload). The results are presented and analyzed. The analysis of simulation results can provide support for parameter configuration and optimization of WLANs for realtime applications.


A Secured Health Care Application Architecture for Cyber-Physical Systems

Abstract: Cyber-physical systems (CPS) can be viewed as a new generation of systems with integrated control, communication and computational capabilities. Like the internet transformed how humans interact with one another, cyber-physical systems will transform how people interact with the physical world. Currently, the study of CPS is still in its infancy and there exist many research issues and challenges ranging from electricity power, health care, transportation and smart building etc. In this paper, an introduction of CPeSC3 (cyber physical enhanced secured wireless sensor networks (WSNs) integrated cloud computing for u-life care) architecture and its application to the health care monitoring and decision support systems is given. The proposed CPeSC3 architecture is composed of three main components, namely 1) communication core, 2) computation core, and 3) resource scheduling and management core. Detailed analysis and explanation are given for relevant models such as cloud computing, real time scheduling and security models. Finally, a medical health care application scenario is presented based on our practical test-bed which has been built for 3 years.


ART-GAS: An Adaptive and Real-Time GTS Allocation Scheme for IEEE 802.15.4

Abstract: IEEE 802.15.4 supports a Guaranteed Time Slot (GTS) allocation mechanism for time-critical and delay-sensitive data transmissions in Wireless Personal Area Networks (WPANs). However, the inflexible first-come-first-served GTS allocation policy and the passive deallocation mechanism significantly reduce network efficiency. In this paper, we propose an Adaptive and Real-Time GTS Allocation Scheme (ART-GAS) to provide differentiated services for devices with different priorities, which guarantees data transmissions for time-sensitive and high-traffic devices. The bandwidth utilization in IEEE 802.15.4-based PAN is improved. Simulation results show that our ART-GAS algorithm significantly outperforms the existing GTS mechanism specified in IEEE 802.15.4.


Building Smart Communities with Cyber-Physical Systems

Abstract: There is a growing trend towards the convergence of cyber-physical systems (CPS) and social computing, which will lead to the emergence of smart communities composed of various objects (including both human individuals and physical things) that interact and cooperate with each other. These smart communities promise to enable a number of innovative applications and services that will improve the quality of life. This position paper addresses some opportunities and challenges of building smart communities characterized by cyber-physical and social intelligence.


Monitoring Energy Consumption of Smartphones

Abstract: With the rapid development of new and innovative applications for mobile devices like smartphones, advances in battery technology have not kept pace with rapidly growing energy demands. Thus energy consumption has become a more and more important issue of mobile devices. To meet the requirements of saving energy, it is critical to monitor and analyze the energy consumption of applications on smartphones. For this purpose, we develop a smart energy monitoring system called SEMO for smartphones using Android operating system. It can profile mobile applications with battery usage information, which is vital for both developers and users.


A-GPS Assisted Wi-Fi Access Point Discovery on Mobile Devices for Energy Saving

Abstract: Mobile devices have been shipped with multiple wireless network interfaces in order to meet their diverse communication and networking demands. In this paper, we propose an A-GPS assisted scheme that discovers the nearest Wi-Fi network access points (APs) by using user's location information. This allows the user to switch to the Wi-Fi interface in an intelligent manner when she/he arrives at the nearest Wi-Fi network AP. Therefore, it avoids the long periods in idle state and greatly reduces the number of unnecessary Wi-Fi scans on the mobile device. The experimental results demonstrate that our scheme effectively saves energy for mobile devices integrated with Wi-Fi and cellular interfaces.


Towards Cost-Effective Storage Provisioning for DBMSs

Abstract: Data center operators face a bewildering set of choices when considering how to provision resources on machines with complex I/O subsystems. Modern I/O subsystems often have a rich mix of fast, high performing, but expensive SSDs sitting alongside with cheaper but relatively slower (for random accesses) traditional hard disk drives. The data center operators need to determine how to provision the I/O resources for specific workloads so as to abide by existing Service Level Agreements (SLAs), while minimizing the total operating cost (TOC) of running the workload, where the TOC includes the amortized hardware costs and the run time energy costs. The focus of this paper is on introducing this new problem of TOC-based storage allocation, cast in a framework that is compatible with traditional DBMS query optimization and query processing architecture. We also present a heuristic-based solution to this problem, called DOT. We have implemented DOT in PostgreSQL, and experiments using TPC-H and TPC-C demonstrate significant TOC reduction by DOT in various settings.


B+-tree Index Optimization by Exploiting Internal Parallelism of Flash-based Solid State Drives

Abstract: Previous research addressed the potential problems of the hard-disk oriented design of DBMSs of flashSSDs. In this paper, we focus on exploiting potential benefits of flashSSDs. First, we examine the internal parallelism issues of flashSSDs by conducting benchmarks to various flashSSDs. Then, we suggest algorithm-design principles in order to best benefit from the internal parallelism. We present a new I/O request concept, called psync I/O that can exploit the internal parallelism of flashSSDs in a single process. Based on these ideas, we introduce B+-tree optimization methods in order to utilize internal parallelism. By integrating the results of these methods, we present a B+-tree variant, PIO B-tree. We confirmed that each optimization method substantially enhances the index performance. Consequently, PIO B-tree enhanced B+-tree's insert performance by a factor of up to 16.3, while improving point-search performance by a factor of 1.2. The range search of PIO B-tree was up to 5 times faster than that of the B+-tree. Moreover, PIO B-tree outperformed other flash-aware indexes in various synthetic workloads. We also confirmed that PIO B-tree outperforms B+-tree in index traces collected inside the Postgresql DBMS with TPC-C benchmark.


High-Performance Concurrency Control Mechanisms for Main-Memory Databases

Abstract: A database system optimized for in-memory storage can support much higher transaction rates than current systems. However, standard concurrency control methods used today do not scale to the high transaction rates achievable by such systems. In this paper we introduce two efficient concurrency control methods specifically designed for main-memory databases. Both use multiversioning to isolate read-only transactions from updates but differ in how atomicity is ensured: one is optimistic and one is pessimistic. To avoid expensive context switching, transactions never block during normal processing but they may have to wait before commit to ensure correct serialization ordering. We also implemented a main-memory optimized version of single-version locking. Experimental results show that while single-version locking works well when transactions are short and contention is low performance degrades under more demanding conditions. The multiversion schemes have higher overhead but are much less sensitive to hotspots and the presence of long-running transactions.


Capturing Topology in Graph Pattern Matching

Abstract: Graph pattern matching is often defined in terms of subgraph isomorphism, an NP-complete problem. To lower its complexity, various extensions of graph simulation have been considered instead. These extensions allow pattern matching to be conducted in cubic-time. However, they fall short of capturing the topology of data graphs, i.e., graphs may have a structure drastically different from pattern graphs they match, and the matches found are often too large to understand and analyze. To rectify these problems, this paper proposes a notion of strong simulation, a revision of graph simulation, for graph pattern matching. (1) We identify a set of criteria for preserving the topology of graphs matched. We show that strong simulation preserves the topology of data graphs and finds a bounded number of matches. (2) We show that strong simulation retains the same complexity as earlier extensions of simulation, by providing a cubic-time algorithm for computing strong simulation. (3) We present the locality property of strong simulation, which allows us to effectively conduct pattern matching on distributed graphs. (4) We experimentally verify the effectiveness and efficiency of these algorithms, using real-life data and synthetic data.


RTED: A Robust Algorithm for the Tree Edit Distance

Abstract: We consider the classical tree edit distance between ordered labeled trees, which is defined as the minimum-cost sequence of node edit operations that transform one tree into another. The state-of-the-art solutions for the tree edit distance are not satisfactory. The main competitors in the field either have optimal worst-case complexity, but the worst case happens frequently, or they are very efficient for some tree shapes, but degenerate for others. This leads to unpredictable and often infeasible runtimes. There is no obvious way to choose between the algorithms. In this paper we present RTED, a robust tree edit distance algorithm. The asymptotic complexity of RTED is smaller or equal to the complexity of the best competitors for any input instance, i.e., RTED is both efficient and worst-case optimal. We introduce the class of LRH (Left-Right-Heavy) algorithms, which includes RTED and the fastest tree edit distance algorithms presented in literature. We prove that RTED outperforms all previously proposed LRH algorithms in terms of runtime complexity. In our experiments on synthetic and real world data we empirically evaluate our solution and compare it to the state-of-the-art.


Putting Lipstick on Pig: Enabling Database-style Workflow Provenance

Abstract: Workflow provenance typically assumes that each module is a "black-box", so that each output depends on all inputs (coarse-grained dependencies). Furthermore, it does not model the internal state of a module, which can change between repeated executions. In practice, however, an output may depend on only a small subset of the inputs (fine-grained dependencies) as well as on the internal state of the module. We present a novel provenance framework that marries database-style and workflow-style provenance, by using Pig Latin to expose the functionality of modules, thus capturing internal state and fine-grained dependencies. A critical ingredient in our solution is the use of a novel form of provenance graph that models module invocations and yields a compact representation of fine-grained workflow provenance. It also enables a number of novel graph transformation operations, allowing to choose the desired level of granularity in provenance querying (ZoomIn and ZoomOut), and supporting "what-if" workflow analytic queries. We implemented our approach in the Lipstick system and developed a benchmark in support of a systematic performance evaluation. Our results demonstrate the feasibility of tracking and querying fine-grained workflow provenance.


Relational Approach for Shortest Path Discovery over Large Graphs

Abstract: With the rapid growth of large graphs, we cannot assume that graphs can still be fully loaded into memory, thus the disk-based graph operation is inevitable. In this paper, we take the shortest path discovery as an example to investigate the technique issues when leveraging existing infrastructure of relational database (RDB) in the graph data management. Based on the observation that a variety of graph search queries can be implemented by iterative operations including selecting frontier nodes from visited nodes, making expansion from the selected frontier nodes, and merging the expanded nodes into the visited ones, we introduce a relational FEM framework with three corresponding operators to implement graph search tasks in the RDB context. We show new features such as window function and merge statement introduced by recent SQL standards can not only simplify the expression but also improve the performance of the FEM framework. In addition, we propose two optimization strategies specific to shortest path discovery inside the FEM framework. First, we take a bi-directional set Dijkstra's algorithm in the path finding. The bi-directional strategy can reduce the search space, and set Dijkstra's algorithm finds the shortest path in a set-at-a-time fashion. Second, we introduce an index named SegTable to preserve the local shortest segments, and exploit SegTable to further improve the performance. The final extensive experimental results illustrate our relational approach with the optimization strategies achieves high scalability and performance.


Mining Flipping Correlations from Large Datasets with Taxonomies

Abstract: In this paper we introduce a new type of pattern -- a flipping correlation pattern. The flipping patterns are obtained from contrasting the correlations between items at different levels of abstraction. They represent surprising correlations, both positive and negative, which are specific for a given abstraction level, and which "flip" from positive to negative and vice versa when items are generalized to a higher level of abstraction. We design an efficient algorithm for finding flipping correlations, the Flipper algorithm, which outperforms naive pattern mining methods by several orders of magnitude. We apply Flipper to real-life datasets and show that the discovered patterns are non-redundant, surprising and actionable. Flipper finds strong contrasting correlations in itemsets with low-to-medium support, while existing techniques cannot handle the pattern discovery in this frequency range.


A Statistical Approach Towards Robust Progress Estimation

Abstract: The need for accurate SQL progress estimation in the context of decision support administration has led to a number of techniques proposed for this task. Unfortunately, no single one of these progress estimators behaves robustly across the variety of SQL queries encountered in practice, meaning that each technique performs poorly for a significant fraction of queries. This paper proposes a novel estimator selection framework that uses a statistical model to characterize the sets of conditions under which certain estimators outperform others, leading to a significant increase in estimation robustness. The generality of this framework also enables us to add a number of novel "special purpose" estimators which increase accuracy further. Most importantly, the resulting model generalizes well to queries very different from the ones used to train it. We validate our findings using a large number of industrial real-life and benchmark workloads.


A Lower Bound for Estimating High Moments of a Data Stream

Abstract: We show an improved lower bound for the Fp estimation problem in a data stream setting for p>2. A data stream is a sequence of items from the domain [n] with possible repetitions. The frequency vector x is an n-dimensional non-negative integer vector x such that x(i) is the number of occurrences of i in the sequence. Given an accuracy parameter Omega(n^{-1/p}) < \epsilon < 1, the problem of estimating Fp is to estimate \norm{x}_p^p = \sum_{i \in [n]} \abs{x(i)}^p correctly to within a relative accuracy of 1\pm \epsilon with high constant probability in an online fashion and using as little space as possible. The current space lower bound for this problem is Omega(n^{1-2/p} \epsilon^{-2/p}+ n^{1-2/p}\epsilon^{-4/p}/ \log^{O(1)}(n)+ (\epsilon^{-2} + \log (n))). The first term in the lower bound expression was proved in \cite{B-YJKS:stoc02,cks:ccc03}, the second in \cite{wz:arxiv11} and the third in \cite{wood:soda04}. In this note, we show an Omega(p^2 n^{1-2/p} \epsilon^{-2}/\log (n)) bits space bound, for Omega(pn^{-1/p}) \le \epsilon \le 1/10.


Overview of EIREX 2010: Computing

Abstract: The first Information Retrieval Education through Experimentation track (EIREX 2010) was run at the University Carlos III of Madrid, during the 2010 spring semester. EIREX 2010 is the first in a series of experiments designed to foster new Information Retrieval (IR) education methodologies and resources, with the specific goal of teaching undergraduate IR courses from an experimental perspective. For an introduction to the motivation behind the EIREX experiments, see the first sections of [Urbano et al., 2011]. For information on other editions of EIREX and related data, see the website at http://ir.kr.inf.uc3m.es/eirex/. The EIREX series have the following goals: a) to help students get a view of the Information Retrieval process as they would find it in a real-world scenario, either industrial or academic; b) to make students realize the importance of laboratory experiments in Computer Science and have them initiated in their execution and analysis; c) to create a public repository of resources to teach Information Retrieval courses; d) to seek the collaboration and active participation of other Universities in this endeavor. This overview paper summarizes the results of the EIREX 2010 track, focusing on the creation of the test collection and the analysis to assess its reliability.


T-Learning

Abstract: Traditional Reinforcement Learning (RL) has focused on problems involving many states and few actions, such as simple grid worlds. Most real world problems, however, are of the opposite type, Involving Few relevant states and many actions. For example, to return home from a conference, humans identify only few subgoal states such as lobby, taxi, airport etc. Each valid behavior connecting two such states can be viewed as an action, and there are trillions of them. Assuming the subgoal identification problem is already solved, the quality of any RL method---in real-world settings---depends less on how well it scales with the number of states than on how well it scales with the number of actions. This is where our new method T-Learning excels, by evaluating the relatively few possible transits from one state to another in a policy-independent way, rather than a huge number of state-action pairs, or states in traditional policy-dependent ways. Illustrative experiments demonstrate that performance improvements of T-Learning over Q-learning can be arbitrarily large.


Quotient Complexities of Atoms of Regular Languages

Abstract: An atom of a regular language L with n (left) quotients is a non-empty intersection of uncomplemented or complemented quotients of L, where each of the n quotients appears in a term of the intersection. The quotient complexity of L, which is the same as the state complexity of L, is the number of quotients of L. We prove that, for any language L with quotient complexity n, the quotient complexity of any atom of L with r complemented quotients has an upper bound of 2^n-1 if r=0 or r=n, and 1+\sum_{k=1}^{r} \sum_{h=k+1}^{k+n-r} C_{h}^{n} \cdot C_{k}^{h} otherwise, where C_j^i is the binomial coefficient. For each n\ge 1, we exhibit a language whose atoms meet these bounds.


Design and Analysis of Coalitions in Data Swarming Systems

Abstract: We design and analyze a mechanism for forming coalitions of peers in a data swarming system where peers have heterogeneous upload capacities. A coalition is a set of peers that explicitly cooperate with other peers inside the coalition via choking, data replication, and capacity allocation strategies. Further, each peer interacts with other peers outside its coalition via potentially distinct choking, data replication, and capacity allocation strategies. Following on our preliminary work in IEEE ICNP 2011 that demonstrated significant performance benefits of coalitions, we present here a comprehensive analysis of the choking and data replication strategies for coalitions. We first develop an analytical model to understand a simple random choking strategy as a within-coalition strategy and show that it accurately predicts a coalition's performance. Our analysis formally shows that the random choking strategy can help a coalition achieve near-optimal performance by optimally choosing the re-choking interval lengths and the number unchoke slots. Further, our analytical model can be easily adapted to model a BitTorrent-like swarm. We also introduce a simple data replication strategy which significantly improves data availability within a coalition as compared to the rarest-first piece replication strategy employed in BitTorrent systems. We further propose a cooperation-aware better response strategy that achieves convergence of the dynamic coalition formation process when peers freely join or leave any coalition. Finally, using extensive simulations, we demonstrate improvements in the performance of a swarming system due to coalition formation.


Proceedings Second Workshop on Developments in Implicit Computational Complexity

Abstract: This volume contains the proceedings of the Second International Workshop on Developments in Implicit Computational complExity (DICE 2011), which took place on April 2-3 2011 in Saarbruecken, Germany, as a satellite event of the Joint European Conference on Theory and Practice of Software, ETAPS 2011. Implicit Computational Complexity aims at studying computational complexity without referring to external measuring conditions or particular machine models, but instead by considering restrictions on programming languages or logical principles implying complexity properties. The aim of this workshop was to bring together researchers working on implicit computational complexity, from its logical and semantics aspects to those related to the static analysis of programs, so as to foster their interaction and to give newcomers an overview of the current trends in this area. The first DICE workshop was held in 2010 at ETAPS and published in EPTCS, volume 23 (http://eptcs.org/content.cgi?DICE2010).


Why We Shouldn't Forget Multicast in Name-oriented Publish/Subscribe

Abstract: Name-oriented networks introduce the vision of an information-centric, secure, globally available publish-subscribe infrastructure. Current approaches concentrate on unicast-based pull mechanisms and thereby fall short in automatically updating content at receivers. In this paper, we argue that an inclusion of multicast will grant additional benefits to the network layer, namely efficient distribution of real-time data, a many-to-many communication model, and simplified rendezvous processes. These aspects are comprehensively reflected by a group-oriented naming concept that integrates the various available group schemes and introduces new use cases. A first draft of this name-oriented multicast access has been implemented in the HAMcast middleware.


Empirical study of performance of data binding in ASP.NET web applications

Abstract: Most developers use default properties of ASP.NET server controls when developing web applications. ASP.NET web applications typically employ server controls to provide dynamic web pages, and data-bound server controls to display and maintain database data. Though the default properties allow for fast creation of workable applications, creating a high-performance, multi-user, and scalable web application requires careful configuring of server controls and their enhancement using custom-made code. In providing commonly required functionality in data-driven ASP.NET web applications such as paging, sorting and filtering, our empirical study evaluated the impact of various technical approaches: automatic data binding in web server controls; data paging and sorting on web server; paging and sorting on database server; indexed and non-indexed database columns; clustered vs. non-clustered indices. The study observed significant performance differences between various technical approaches.


On the Performance of Exhaustive Search with Cooperating agents

Abstract: Despite the occurrence of elegant algorithms for solving complex problem, exhaustive search has retained its significance since many real-life problems exhibit no regular structure and exhaustive search is the only possible solution. The advent of high-performance computing either via multicore processors or distributed processors emphasizes the possibility for exhaustive search by multiple search agents. Here we analyse the performance of exhaustive search when it is conducted by multiple search agents. Several strategies for cooperation between the search agents are evaluated. We discover that the performance of the search improves with the increase in the level of cooperation. Same search performance can be achieved with homogeneous and heterogeneous search agents provided that the length of subregions allocated to individual search regions follow the differences in the speeds of heterogeneous search agents.


Lower bounding edit distances between permutations

Abstract: A number of fields, including the study of genome rearrangements and the design of interconnection networks, deal with the connected problems of sorting permutations in "as few moves as possible", using a given set of allowed operations, or computing the number of moves the sorting process requires, often referred to as the \emph{distance} of the permutation. These operations often act on just one or two segments of the permutation, e.g. by reversing one segment or exchanging two segments. The \emph{cycle graph} of the permutation to sort is a fundamental tool in the theory of genome rearrangements, and has proved useful in settling the complexity of many variants of the above problems. In this paper, we present an algebraic reinterpretation of the cycle graph of a permutation $\pi$ as an even permutation $\bar{\pi}$, and show how to reformulate our sorting problems in terms of particular factorisations of the latter permutation. Using our framework, we recover known results in a simple and unified way, and obtain a new lower bound on the \emph{prefix transposition distance} (where a \emph{prefix transposition} displaces the initial segment of a permutation), which is shown to outperform previous results. Moreover, we use our approach to improve the best known lower bound on the \emph{prefix transposition diameter} from $2n/3$ to $\lfloor3n/4\rfloor$, and investigate a few relations between some statistics on $\pi$ and $\bar{\pi}$.


Information Carriers and Identification of Information Objects: An Ontological Approach

Abstract: Even though library and archival practice, as well as Digital Preservation, have a long tradition in identifying information objects, the question of their precise identity under change of carrier or migration is still a riddle to science. The objective of this paper is to provide criteria for the unique identification of some important kinds of information objects, independent from the kind of carrier or specific encoding. Our approach is based on the idea that the substance of some kinds of information objects can completely be described in terms of discrete arrangements of finite numbers of known kinds of symbols, such as those implied by style guides for scientific journal submissions. Our theory is also useful for selecting or describing what has to be preserved. This is a fundamental problem since curators and archivists would like to formally record the decisions of what has to be preserved over time and to decide (or verify) whether a migration (transformation) preserves the intended information content. Furthermore, it is important for reasoning about the authenticity of digital objects, as well as for reducing the cost of digital preservation.


Methods and Techniques of Quality Management for ICT Audit Processes

Abstract: In modern organizations, Information and Communication Technologies are used to support the organizations' activities. To manage the quality of the organization processes, audit processes are implemented. Also, the audit processes can aim the quality of ICT systems themselves because their involvement in organization processes. The paper investigates the ways in which a quality management can be applied for audit processes in order to obtain a high level of quality for the audit recommendations.


Hiding Malicious Content in PDF Documents

Abstract: This paper is a proof-of-concept demonstration for a specific digital signatures vulnerability that shows the ineffectiveness of the WYSIWYS (What You See Is What You Sign) concept. The algorithm is fairly simple: the attacker generates a polymorphic file that has two different types of content (text, as a PDF document for example, and image: TIFF - two of the most widely used file formats). When the victim signs the dual content file, he/ she only sees a PDF document and is unaware of the hidden content inside the file. After obtaining the legally signed document from the victim, the attacker simply has to change the extension to the other file format. This will not invalidate the digital signature, as no bits were altered. The destructive potential of the attack is considerable, as the Portable Document Format (PDF) is widely used in e-government and in e-business contexts.


AES Encryption and Decryption Using Direct3D 10 API

Abstract: Current video cards (GPUs - Graphics Processing Units) are very programmable, have become much more powerful than the CPUs and they are very affordable. In this paper, we present an implementation for the AES algorithm using Direct3D 10 certified GPUs. The graphics API Direct3D 10 is the first version that allows the use of integer operations, making from the traditional GPUs (that works only with floating point numbers), General Purpose GPUs that can be used for a large number of algorithms, including encryption. We present the performance of the symmetric key encryption algorithm - AES, on a middle range GPU and on a middle range quad core CPU. On the testing system, the developed solution is almost 3 times faster on the GPU than on one single core CPU, showing that the GPU can perform as an efficient cryptographic accelerator.


Polyhedral Clinching Auctions and the Adwords Polytope

Abstract: A central issue in applying auction theory in practice is the problem of dealing with budget-constrained agents. A desirable goal in practice is to design incentive compatible, individually rational, and Pareto optimal auctions while respecting the budget constraints. Achieving this goal is particularly challenging in the presence of nontrivial combinatorial constraints over the set of feasible allocations. Toward this goal and motivated by AdWords auctions, we present an auction for {\em polymatroidal} environments satisfying the above properties. Our auction employs a novel clinching technique with a clean geometric description and only needs an oracle access to the submodular function defining the polymatroid. As a result, this auction not only simplifies and generalizes all previous results, it applies to several new applications including AdWords Auctions, bandwidth markets, and video on demand. In particular, our characterization of the AdWords auction as polymatroidal constraints might be of independent interest. This allows us to design the first mechanism for Ad Auctions taking into account simultaneously budgets, multiple keywords and multiple slots. We show that it is impossible to extend this result to generic polyhedral constraints. This also implies an impossibility result for multi-unit auctions with decreasing marginal utilities in the presence of budget constraints.


A note on anti-coordination and social interactions

Abstract: This note confirms a conjecture of [Bramoull\'{e}, Anti-coordination and social interactions, Games and Economic Behavior, 58, 2007: 30-49]. The problem, which we name the maximum independent cut problem, is a restricted version of the MAX-CUT problem, requiring one side of the cut to be an independent set. We show that the maximum independent cut problem does not admit any polynomial time algorithm with approximation ratio better than $n^{1-\epsilon}$, where $n$ is the number of nodes, and $\epsilon$ arbitrarily small, unless P=NP. For the rather special case where each node has a degree of at most four, the problem is still MAXSNP-hard.


Continuity in Information Algebras

Abstract: In this paper, the continuity and strong continuity in domain-free information algebras and labeled information algebras are introduced respectively. A more general concept of continuous function which is defined between two domain-free continuous information algebras is presented. It is shown that, with the operations combination and focusing, the set of all continuous functions between two domain-free s-continuous information algebras forms a new s-continuous information algebra. By studying the relationship between domain-free information algebras and labeled information algebras, it is demonstrated that they do correspond to each other on s-compactness.


A Task Based Sensor-Centeric Model for overall Energy Consumption

Abstract: Sensors have limited resources so it is important to manage the resources efficiently to maximize their use. A sensor's battery is a crucial resource as it singly determines the lifetime of sensor network applications. Since these devices are useful only when they are able to communicate with the world, radio transceiver of a sensor as an I/O and a costly unit plays a key role in its lifetime. This resource often consumes a big portion of the sensor's energy as it must be active most of the time to announce the existence of the sensor in the network. As such the radio component has to deal with its embedded sensor network whose parameters and operations have significant effects on the sensor's lifetime. In existing energy models, hardware is considered, but the environment and the network's parameters did not receive adequate attention. Energy consumption components of traditional network architecture are often considered individually and separately, and their influences on each other have not been considered in these approaches. In this paper we consider all possible tasks of a sensor in its embedded network and propose an energy management model. We categorize these tasks in five energy consuming constituents. The sensor's Energy Consumption (EC) is modeled on its energy consuming constituents and their input parameters and tasks. The sensor's EC can thus be reduced by managing and executing efficiently the tasks of its constituents. The proposed approach can be effective for power management, and it also can be used to guide the design of energy efficient wireless sensor networks through network parameterization and optimization.


Securing IEEE 802.11G WLAN Using OpenVPN and Its Impact Analysis

Abstract: Like most advances, wireless LAN poses both opportunities and risks. The evolution of wireless networking in recent years has raised many serious security issues. These security issues are of great concern for this technology as it is being subjected to numerous attacks. Because of the free-space radio transmission in wireless networks, eavesdropping becomes easy and consequently a security breach may result in unauthorized access, information theft, interference and service degradation. Virtual Private Networks (VPNs) have emerged as an important solution to security threats surrounding the use of public networks for private communications. While VPNs for wired line networks have matured in both research and commercial environments, the design and deployment of VPNs for WLAN is still an evolving field. This paper presents an approach to secure IEEE 802.11g WLAN using OpenVPN, a transport layer VPN solution and its impact on performance of IEEE 802.11g WLAN.


Testing Substitutability of Weak Preferences

Abstract: In many-to-many matching models, substitutable preferences constitute the largest domain for which a pairwise stable matching is guaranteed to exist. In this note, we extend the recently proposed algorithm of Hatfield et al. [3] to test substitutability of weak preferences. Interestingly, the algorithm is faster than the algorithm of Hatfield et al. by a linear factor on the domain of strict preferences.


Pattern Clustering using Cooperative Game Theory

Abstract: In this paper, we approach the classical problem of clustering using solution concepts from cooperative game theory such as Nucleolus and Shapley value. We formulate the problem of clustering as a characteristic form game and develop a novel algorithm DRAC (Density-Restricted Agglomerative Clustering) for clustering. With extensive experimentation on standard data sets, we compare the performance of DRAC with that of well known algorithms. We show an interesting result that four prominent solution concepts, Nucleolus, Shapley value, Gately point and \tau-value coincide for the defined characteristic form game. This vindicates the choice of the characteristic function of the clustering game and also provides strong intuitive foundation for our approach.


Computing Critical $k$-tuples in Power Networks

Abstract: In this paper the problem of finding the sparsest (i.e., minimum cardinality) critical $k$-tuple including one arbitrarily specified measurement is considered. The solution to this problem can be used to identify weak points in the measurement set, or aid the placement of new meters. The critical $k$-tuple problem is a combinatorial generalization of the critical measurement calculation problem. Using topological network observability results, this paper proposes an efficient and accurate approximate solution procedure for the considered problem based on solving a minimum-cut (Min-Cut) problem and enumerating all its optimal solutions. It is also shown that the sparsest critical $k$-tuple problem can be formulated as a mixed integer linear programming (MILP) problem. This MILP problem can be solved exactly using available solvers such as CPLEX and Gurobi. A detailed numerical study is presented to evaluate the efficiency and the accuracy of the proposed Min-Cut and MILP calculations.


Technical Note: Exploring \Sigma^P_2 / \Pi^P_2-hardness for Argumentation Problems with fixed distance to tractable classes

Abstract: We study the complexity of reasoning in abstracts argumentation frameworks close to graph classes that allow for efficient reasoning methods, i.e.\ to one of the classes of acyclic, noeven, biparite and symmetric AFs. In this work we show that certain reasoning problems on the second level of the polynomial hierarchy still maintain their full complexity when restricted to instances of fixed distance to one of the above graph classes.


Scikit-learn: Machine Learning in Python

Abstract: Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.org.


ProofPeer - A Cloud-based Interactive Theorem Proving System

Abstract: ProofPeer strives to be a system for cloud-based interactive theorem proving. After illustrating why such a system is needed, the paper presents some of the design challenges that ProofPeer needs to meet to succeed. Contexts are presented as a solution to the problem of sharing proof state among the users of ProofPeer. Chronicles are introduced as a way to organize and version contexts.


Reliability Analysis of Electric Power Systems Using an Object-oriented Hybrid Modeling Approach

Abstract: The ongoing evolution of the electric power systems brings about the need to cope with increasingly complex interactions of technical components and relevant actors. In order to integrate a more comprehensive spectrum of different aspects into a probabilistic reliability assessment and to include time-dependent effects, this paper proposes an object-oriented hybrid approach combining agent-based modeling techniques with classical methods such as Monte Carlo simulation. Objects represent both technical components such as generators and transmission lines and non-technical components such as grid operators. The approach allows the calculation of conventional reliability indices and the estimation of blackout frequencies. Furthermore, the influence of the time needed to remove line overloads on the overall system reliability can be assessed. The applicability of the approach is demonstrated by performing simulations on the IEEE Reliability Test System 1996 and on a model of the Swiss high-voltage grid.


Absorbing Subalgebras, Cyclic Terms, and the Constraint Satisfaction Problem

Abstract: The Algebraic Dichotomy Conjecture states that the Constraint Satisfaction Problem over a fixed template is solvable in polynomial time if the algebra of polymorphisms associated to the template lies in a Taylor variety, and is NP-complete otherwise. This paper provides two new characterizations of finitely generated Taylor varieties. The first characterization is using absorbing subalgebras and the second one cyclic terms. These new conditions allow us to reprove the conjecture of Bang-Jensen and Hell (proved by the authors) and the characterization of locally finite Taylor varieties using weak near-unanimity terms (proved by McKenzie and Mar\'oti) in an elementary and self-contained way.


The RegularGcc Matrix Constraint

Abstract: We study propagation of the RegularGcc global constraint. This ensures that each row of a matrix of decision variables satisfies a Regular constraint, and each column satisfies a Gcc constraint. On the negative side, we prove that propagation is NP-hard even under some strong restrictions (e.g. just 3 values, just 4 states in the automaton, or just 5 columns to the matrix). On the positive side, we identify two cases where propagation is fixed parameter tractable. In addition, we show how to improve propagation over a simple decomposition into separate Regular and Gcc constraints by identifying some necessary but insufficient conditions for a solution. We enforce these conditions with some additional weighted row automata. Experimental results demonstrate the potential of these methods on some standard benchmark problems.


Learning joint intensity-depth sparse representations

Abstract: This paper presents a method for learning overcomplete dictionaries composed of two modalities that describe a 3D scene: image intensity and scene depth. We propose a novel Joint Basis Pursuit (JBP) algorithm that finds related sparse features in two modalities using conic programming and integrate it into a two-step dictionary learning algorithm. JBP differs from related convex algorithms because it finds joint sparsity models with different atoms and different coefficient values for intensity and depth. This is crucial for recovering generative models where the same sparse underlying causes (3D features) give rise to different signals (intensity and depth). We give a theoretical bound for the sparse coefficient recovery error obtained by JBP, and show experimentally that JBP is far superior to the state of the art Group Lasso algorithm. When applied to the Middlebury depth-intensity database, our learning algorithm converges to a set of related features, such as pairs of depth and intensity edges or image textures and depth slants. Finally, we show that the learned dictionary and JBP achieve the state of the art depth inpainting performance on time-of-flight 3D data.


Formalizing Traceability and Derivability in Software Product Lines

Abstract: In the literature, the definition of product in a Software Product Line (SPL) is based upon the notion of consistency of the constraints, imposed by variability and traceability relations on the elements of the SPL. In this paper, we contend that consistency does not model the natural semantics of the implementability relation between problem and solution spaces correctly. Therefore, we define when a feature can be {\em derived} from a set of components . Using this, we define a product of the SPL by a <specification, architecture> pair, where all the features in the specification are derived from the components in the architecture. This notion of derivability is formulated in a simple yet expressive, abstract model of a productline with traceability relation. We then define a set of SPL analysis problems and show that these problems can be encoded as Quantified Boolean Formulas. Then, QSAT solvers like QUBE can be used to solve the analysis problems. We illustrate the methodology on a small fragment of a realistic productline.


An extension of data automata that captures XPath

Abstract: We define a new kind of automata recognizing properties of data words or data trees and prove that the automata capture all queries definable in Regular XPath. We show that the automata-theoretic approach may be applied to answer decidability and expressibility questions for XPath.


Interactive multiview video system with non-complex navigation at the decoder

Abstract: Multiview video with interactive and smooth view switching at the receiver is a challenging application with several issues in terms of effective use of storage and bandwidth resources, reactivity of the system, quality of the viewing experience and system complexity. The classical decoding system for generating virtual views first projects a reference or encoded frame to a given viewpoint and then fills in the holes due to potential occlusions. This last step still constitutes a complex operation with specific software or hardware at the receiver and requires a certain quantity of information from the neighboring frames for insuring consistency between the virtual images. In this work we propose a new approach that shifts most of the burden due to interactivity from the decoder to the encoder, by anticipating the navigation of the decoder and sending auxiliary information that guarantees temporal and interview consistency. This leads to an additional cost in terms of transmission rate and storage, which we minimize by using optimization techniques based on the user behavior modeling. We show by experiments that the proposed system represents a valid solution for interactive multiview systems with classical decoders.


LTL to B\"uchi Automata Translation: Fast and More Deterministic

Abstract: We introduce improvements in the algorithm by Gastin and Oddoux translating LTL formulae into B\"uchi automata via very weak alternating co-B\"uchi automata and generalized B\"uchi automata. Several improvements are based on specific properties of any formula where each branch of its syntax tree contains at least one eventually operator and at least one always operator. These changes usually result in faster translations and smaller automata. Other improvements reduce non-determinism in the produced automata. In fact, we modified all the steps of the original algorithm and its implementation known as LTL2BA. Experimental results show that our modifications are real improvements. Their implementations within an LTL2BA translation made LTL2BA very competitive with the current version of SPOT, sometimes outperforming it substantially.


A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems

Abstract: In contrast to the classical cyclic prefix (CP)-OFDM, the time domain synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard interval (GI). Conventional channel estimation methods for TDS-OFDM are based on the exploitation of the PN sequence and consequently suffer from intersymbol interference (ISI). This paper proposes a novel dataaided channel estimation method which combines the channel estimates obtained from the PN sequence and, most importantly, additional channel estimates extracted from OFDM data symbols. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training sequences. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not included in the feedback loop when rebuilding OFDM data symbols thereby reducing the complexity. Several improved techniques are proposed to refine the data-aided channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving average and Wiener filtering. Finally, the MMSE criteria is used to obtain the best combination results and an iterative process is proposed to progressively refine the estimation. Both MSE and BER simulations using specifications of the DTMB system are carried out to prove the effectiveness of the proposed algorithm even in very harsh channel conditions such as in the single frequency network (SFN) case.


LMEEC: Layered Multi-Hop Energy Efficient Cluster-based Routing Protocol for Wireless Sensor Networks

Abstract: In this paper, we propose LMEEC, a cluster-based routing protocol with low energy consumption for wireless sensor networks. Our protocol is based on a strategy which aims to provide a more reasonable exploitation of the selected nodes (cluster-heads) energy. Simulation results show the effectiveness of LMEEC in decreasing the energy consumption, and in prolonging the network lifetime, compared to LEACH.