OpenRaiser/Intern-Atlas huggingface dataset:
A Dynamic Programming Framework for Combinatorial Optimization Problems on Graphs with Bounded Pathwidth
Venue: arXiv cs.DS 2012
Year: 2012

In this paper we present an algorithmic framework for solving a class of combinatorial optimization problems on graphs with bounded pathwidth. The problems are NP-hard in general, but solvable in linear time on this type of graphs. The problems are relevant for assessing network reliability and improving the network's performance and fault tolerance. The main technique considered in this paper is dynamic programming.
Secrecy via Sources and Channels
Venue: arXiv cs.IT 2012
Year: 2012

Alice and Bob want to share a secret key and to communicate an independent message, both of which they desire to be kept secret from an eavesdropper Eve. We study this problem of secret communication and secret key generation when two resources are available -- correlated sources at Alice, Bob, and Eve, and a noisy broadcast channel from Alice to Bob and Eve which is independent of the sources. We are interested in characterizing the fundamental trade-off between the rates of the secret message and secret key. We present an achievable solution and prove its optimality for the parallel channels and sources case when each sub-channel and source component satisfies a degradation order (either in favor of the legitimate receiver or the eavesdropper). This includes the case of jointly Gaussian sources and an additive Gaussian channel, for which the secrecy region is evaluated.
Distributed Parameter Estimation in Sensor Networks: Nonlinear Observation Models and Imperfect Communication
Venue: arXiv cs.MA 2012
Year: 2012

The paper studies distributed static parameter (vector) estimation in sensor networks with nonlinear observation models and noisy inter-sensor communication. It introduces \emph{separably estimable} observation models that generalize the observability condition in linear centralized estimation to nonlinear distributed estimation. It studies two distributed estimation algorithms in separably estimable models, the $\mathcal{NU}$ (with its linear counterpart $\mathcal{LU}$) and the $\mathcal{NLU}$. Their update rule combines a \emph{consensus} step (where each sensor updates the state by weight averaging it with its neighbors' states) and an \emph{innovation} step (where each sensor processes its local current observation.) This makes the three algorithms of the \textit{consensus + innovations} type, very different from traditional consensus. The paper proves consistency (all sensors reach consensus almost surely and converge to the true parameter value,) efficiency, and asymptotic unbiasedness. For $\mathcal{LU}$ and $\mathcal{NU}$, it proves asymptotic normality and provides convergence rate guarantees. The three algorithms are characterized by appropriately chosen decaying weight sequences. Algorithms $\mathcal{LU}$ and $\mathcal{NU}$ are analyzed in the framework of stochastic approximation theory; algorithm $\mathcal{NLU}$ exhibits mixed time-scale behavior and biased perturbations, and its analysis requires a different approach that is developed in the paper.
Datalog and Constraint Satisfaction with Infinite Templates
Venue: arXiv cs.LO 2012
Year: 2012

On finite structures, there is a well-known connection between the expressive power of Datalog, finite variable logics, the existential pebble game, and bounded hypertree duality. We study this connection for infinite structures. This has applications for constraint satisfaction with infinite templates. If the template Gamma is omega-categorical, we present various equivalent characterizations of those Gamma such that the constraint satisfaction problem (CSP) for Gamma can be solved by a Datalog program. We also show that CSP(Gamma) can be solved in polynomial time for arbitrary omega-categorical structures Gamma if the input is restricted to instances of bounded treewidth. Finally, we characterize those omega-categorical templates whose CSP has Datalog width 1, and those whose CSP has strict Datalog width k.
Inferring Company Structure from Limited Available Information
Venue: arXiv cs.DS 2012
Year: 2012

In this paper we present several algorithmic techniques for inferring the structure of a company when only a limited amount of information is available. We consider problems with two types of inputs: the number of pairs of employees with a given property and restricted information about the hierarchical structure of the company. We provide dynamic programming and greedy algorithms for these problems.
On parsimonious edge-colouring of graphs with maximum degree three
Venue: arXiv cs.DM 2012
Year: 2012

In a graph $G$ of maximum degree $Δ$ let $γ$ denote the largest fraction of edges that can be $Δ$ edge-coloured. Albertson and Haas showed that $γ\geq 13/15$ when $G$ is cubic . We show here that this result can be extended to graphs with maximum degree 3 with the exception of a graph on 5 vertices. Moreover, there are exactly two graphs with maximum degree 3 (one being obviously the Petersen graph) for which $γ= 13/15$. This extends a result given by Steffen. These results are obtained by using structural properties of the so called $δ$-minimum edge colourings for graphs with maximum degree 3. Keywords : Cubic graph; Edge-colouring
Ergodic Interference Alignment
Venue: arXiv cs.IT 2012
Year: 2012

This paper develops a new communication strategy, ergodic interference alignment, for the K-user interference channel with time-varying fading. At any particular time, each receiver will see a superposition of the transmitted signals plus noise. The standard approach to such a scenario results in each transmitter-receiver pair achieving a rate proportional to 1/K its interference-free ergodic capacity. However, given two well-chosen time indices, the channel coefficients from interfering users can be made to exactly cancel. By adding up these two observations, each receiver can obtain its desired signal without any interference. If the channel gains have independent, uniform phases, this technique allows each user to achieve at least 1/2 its interference-free ergodic capacity at any signal-to-noise ratio. Prior interference alignment techniques were only able to attain this performance as the signal-to-noise ratio tended to infinity. Extensions are given for the case where each receiver wants a message from more than one transmitter as well as the "X channel" case (with two receivers) where each transmitter has an independent message for each receiver. Finally, it is shown how to generalize this strategy beyond Gaussian channel models. For a class of finite field interference channels, this approach yields the ergodic capacity region.
The Incidence Chromatic Number of Toroidal Grids
Venue: arXiv cs.DM 2012
Year: 2012

An incidence in a graph $G$ is a pair $(v,e)$ with $v \in V(G)$ and $e \in E(G)$, such that $v$ and $e$ are incident. Two incidences $(v,e)$ and $(w,f)$ are adjacent if $v=w$, or $e=f$, or the edge $vw$ equals $e$ or $f$. The incidence chromatic number of $G$ is the smallest $k$ for which there exists a mapping from the set of incidences of $G$ to a set of $k$ colors that assigns distinct colors to adjacent incidences. In this paper, we prove that the incidence chromatic number of the toroidal grid $T_{m,n}=C_m\Box C_n$ equals 5 when $m,n \equiv 0 \pmod 5$ and 6 otherwise.
Towards a Theory of Anonymous Networking
Venue: arXiv cs.NI 2012
Year: 2012

The problem of anonymous networking when an eavesdropper observes packet timings in a communication network is considered. The goal is to hide the identities of source-destination nodes, and paths of information flow in the network. One way to achieve such an anonymity is to use mixers. Mixers are nodes that receive packets from multiple sources and change the timing of packets, by mixing packets at the output links, to prevent the eavesdropper from finding sources of outgoing packets. In this paper, we consider two simple but fundamental scenarios: double input-single output mixer and double input-double output mixer. For the first case, we use the information-theoretic definition of the anonymity, based on average entropy per packet, and find an optimal mixing strategy under a strict latency constraint. For the second case, perfect anonymity is considered, and maximal throughput strategies with perfect anonymity are found under a strict latency constraint and an average queue length constraint.
Secure Source Coding with a Helper
Venue: arXiv cs.IT 2012
Year: 2012

We consider a secure source coding problem with a rate-limited helper. In particular, Alice observes an independent and identically distributed (i.i.d.) source X and wishes to transmit this source losslessly to Bob over a rate-limited link. A helper (Helen), observes an i.i.d. correlated source Y and can transmit information to Bob over a separate rate-limited link. A passive eavesdropper (Eve) can observe the coded output of Alice, i.e., the link from Alice to Bob is public. The uncertainty about the source X at Eve, is measured by the conditional entropy of the source given the coded output of Alice. We completely characterize the rate-equivocation region for this secure source coding model, where we show that Slepian-Wolf binning of X with respect to the coded side information received at Bob is optimal. We next consider a modification of this model in which Alice also has access to the coded output of Helen. For the two-sided helper model, we characterize the rate-equivocation region. While the availability of side information at Alice does not reduce the rate of transmission from Alice, it significantly enhances the resulting equivocation at Eve. In particular, the resulting equivocation for the two-sided helper case is shown to be min(H(X),R_y), i.e., one bit from the two-sided helper provides one bit of uncertainty at Eve. From this result, we infer that Slepian-Wolf binning of X is suboptimal and one can further decrease the information leakage to the eavesdropper by utilizing the side information at Alice. We finally generalize these results to the case in which there is additional un-coded side information W available at Bob and characterize the rate-equivocation regions under the assumption that Y-X-W forms a Markov chain.
PageRank Optimization by Edge Selection
Venue: arXiv cs.DS 2012
Year: 2012

The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts - including ranking websites - and can be interpreted as the average portion of time spent at the node by an infinite random walk. We consider the problem of maximizing the PageRank of a node by selecting some of the edges from a set of edges that are under our control. By applying results from Markov decision theory, we show that an optimal solution to this problem can be found in polynomial time. Our core solution results in a linear programming formulation, but we also provide an alternative greedy algorithm, a variant of policy iteration, which runs in polynomial time, as well. Finally, we show that, under the slight modification for which we are given mutually exclusive pairs of edges, the problem of PageRank optimization becomes NP-hard.
Bounds for Algebraic Gossip on Graphs
Venue: arXiv cs.IT 2012
Year: 2012

We study the stopping times of gossip algorithms for network coding. We analyze algebraic gossip (i.e., random linear coding) and consider three gossip algorithms for information spreading Pull, Push, and Exchange. The stopping time of algebraic gossip is known to be linear for the complete graph, but the question of determining a tight upper bound or lower bounds for general graphs is still open. We take a major step in solving this question, and prove that algebraic gossip on any graph of size n is O(D*n) where D is the maximum degree of the graph. This leads to a tight bound of Theta(n) for bounded degree graphs and an upper bound of O(n^2) for general graphs. We show that the latter bound is tight by providing an example of a graph with a stopping time of Omega(n^2). Our proofs use a novel method that relies on Jackson's queuing theorem to analyze the stopping time of network coding; this technique is likely to become useful for future research.
A new approach to content-based file type detection
Venue: arXiv cs.LG 2012
Year: 2012

File type identification and file type clustering may be difficult tasks that have an increasingly importance in the field of computer and network security. Classical methods of file type detection including considering file extensions and magic bytes can be easily spoofed. Content-based file type detection is a newer way that is taken into account recently. In this paper, a new content-based method for the purpose of file type detection and file type clustering is proposed that is based on the PCA and neural networks. The proposed method has a good accuracy and is fast enough.
SMEmail - A New Protocol for the Secure E-mail in Mobile Environments
Venue: arXiv cs.CR 2012
Year: 2012

The electronic mail plays an unavoidable role in the humankind communications. With the great interest for the connection via mobile platforms, and the growing number of vulnerabilities and attacks, it is essential to provide suitable security solutions regarding the limitations of resource restricted platforms. Although some solutions such as PGP and S/MIME are currently available for the secure e-mail over the Internet, they are based on traditional public key cryptography that involves huge computational costs. In this paper, a new secure application-layer protocol, called SMEmail, is introduced that provides several security attributes such as confidentiality, integrity, authentication, non-repudiation, and forward secrecy of message confidentiality for the electronic mails. SMEmail offers an elliptic curve-based public key solution that uses public keys for the secure key establishment of a symmetric encryption, and is so suitable for the resource restricted platforms such as mobile phones.
LPKI - A Lightweight Public Key Infrastructure for the Mobile Environments
Venue: arXiv cs.CR 2012
Year: 2012

The non-repudiation as an essential requirement of many applications can be provided by the asymmetric key model. With the evolution of new applications such as mobile commerce, it is essential to provide secure and efficient solutions for the mobile environments. The traditional public key cryptography involves huge computational costs and is not so suitable for the resource-constrained platforms. The elliptic curve-based approaches as the newer solutions require certain considerations that are not taken into account in the traditional public key infrastructures. The main contribution of this paper is to introduce a Lightweight Public Key Infrastructure (LPKI) for the constrained platforms such as mobile phones. It takes advantages of elliptic curve cryptography and signcryption to decrease the computational costs and communication overheads, and adapting to the constraints. All the computational costs of required validations can be eliminated from end-entities by introduction of a validation authority to the introduced infrastructure and delegating validations to such a component. LPKI is so suitable for mobile environments and for applications such as mobile commerce where the security is the great concern.
Downlink Performance Analysis for a Generalized Shotgun Cellular System
Venue: arXiv cs.IT 2012
Year: 2012

In this paper, we analyze the signal-to-interference-plus-noise ratio (SINR) performance at a mobile station (MS) in a random cellular network. The cellular network is formed by base-stations (BSs) placed in a one, two or three dimensional space according to a possibly non-homogeneous Poisson point process, which is a generalization of the so-called shotgun cellular system. We develop a sequence of equivalence relations for the SCSs and use them to derive semi-analytical expressions for the coverage probability at the MS when the transmissions from each BS may be affected by random fading with arbitrary distributions as well as attenuation following arbitrary path-loss models. For homogeneous Poisson point processes in the interference-limited case with power-law path-loss model, we show that the SINR distribution is the same for all fading distributions and is not a function of the base station density. In addition, the influence of random transmission powers, power control, multiple channel reuse groups on the downlink performance are also discussed. The techniques developed for the analysis of SINR have applications beyond cellular networks and can be used in similar studies for cognitive radio networks, femtocell networks and other heterogeneous and multi-tier networks.
Mergeable Dictionaries
Venue: arXiv cs.DS 2012
Year: 2012

A data structure is presented for the Mergeable Dictionary abstract data type, which supports the following operations on a collection of disjoint sets of totally ordered data: Predecessor-Search, Split and Merge. While Predecessor-Search and Split work in the normal way, the novel operation is Merge. While in a typical mergeable dictionary (e.g. 2-4 Trees), the Merge operation can only be performed on sets that span disjoint intervals in keyspace, the structure here has no such limitation, and permits the merging of arbitrarily interleaved sets. Tarjan and Brown present a data structure which can handle arbitrary Merge operations in O(log n) amortized time per operation if the set of operations is restricted to exclude the Split operation. In the presence of Split operations, the amortized time complexity of their structure becomes Ω(n). A data structure which supports both Split and Merge operations in O(log^2 n) amortized time per operation was given by Farach and Thorup. In contrast, our data structure supports all operations, including Split and Merge, in O(log n) amortized time, thus showing that interleaved Merge operations can be supported at no additional cost vis-a-vis disjoint Merge operations.
Decoding by Sampling: A Randomized Lattice Algorithm for Bounded Distance Decoding
Venue: arXiv cs.IT 2012
Year: 2012

Despite its reduced complexity, lattice reduction-aided decoding exhibits a widening gap to maximum-likelihood (ML) performance as the dimension increases. To improve its performance, this paper presents randomized lattice decoding based on Klein's sampling technique, which is a randomized version of Babai's nearest plane algorithm (i.e., successive interference cancelation (SIC)). To find the closest lattice point, Klein's algorithm is used to sample some lattice points and the closest among those samples is chosen. Lattice reduction increases the probability of finding the closest lattice point, and only needs to be run once during pre-processing. Further, the sampling can operate very efficiently in parallel. The technical contribution of this paper is two-fold: we analyze and optimize the decoding radius of sampling decoding resulting in better error performance than Klein's original algorithm, and propose a very efficient implementation of random rounding. Of particular interest is that a fixed gain in the decoding radius compared to Babai's decoding can be achieved at polynomial complexity. The proposed decoder is useful for moderate dimensions where sphere decoding becomes computationally intensive, while lattice reduction-aided decoding starts to suffer considerable loss. Simulation results demonstrate near-ML performance is achieved by a moderate number of samples, even if the dimension is as high as 32.
Cryptanalysis of an Elliptic Curve-based Signcryption Scheme
Venue: arXiv cs.CR 2012
Year: 2012

The signcryption is a relatively new cryptographic technique that is supposed to fulfill the functionalities of encryption and digital signature in a single logical step. Although several signcryption schemes are proposed over the years, some of them are proved to have security problems. In this paper, the security of Han et al.'s signcryption scheme is analyzed, and it is proved that it has many security flaws and shortcomings. Several devastating attacks are also introduced to the mentioned scheme whereby it fails all the desired and essential security attributes of a signcryption scheme.
The Burbea-Rao and Bhattacharyya centroids
Venue: arXiv cs.IT 2012
Year: 2012

We study the centroid with respect to the class of information-theoretic Burbea-Rao divergences that generalize the celebrated Jensen-Shannon divergence by measuring the non-negative Jensen difference induced by a strictly convex and differentiable function. Although those Burbea-Rao divergences are symmetric by construction, they are not metric since they fail to satisfy the triangle inequality. We first explain how a particular symmetrization of Bregman divergences called Jensen-Bregman distances yields exactly those Burbea-Rao divergences. We then proceed by defining skew Burbea-Rao divergences, and show that skew Burbea-Rao divergences amount in limit cases to compute Bregman divergences. We then prove that Burbea-Rao centroids are unique, and can be arbitrarily finely approximated by a generic iterative concave-convex optimization algorithm with guaranteed convergence property. In the second part of the paper, we consider the Bhattacharyya distance that is commonly used to measure overlapping degree of probability distributions. We show that Bhattacharyya distances on members of the same statistical exponential family amount to calculate a Burbea-Rao divergence in disguise. Thus we get an efficient algorithm for computing the Bhattacharyya centroid of a set of parametric distributions belonging to the same exponential families, improving over former specialized methods found in the literature that were limited to univariate or "diagonal" multivariate Gaussians. To illustrate the performance of our Bhattacharyya/Burbea-Rao centroid algorithm, we present experimental performance results for $k$-means and hierarchical clustering methods of Gaussian mixture models.
Degrees of Freedom Region of a Class of Multi-source Gaussian Relay Networks
Venue: arXiv cs.IT 2012
Year: 2012

We study a layered $K$-user $M$-hop Gaussian relay network consisting of $K_m$ nodes in the $m^{\operatorname{th}}$ layer, where $M\geq2$ and $K=K_1=K_{M+1}$. We observe that the time-varying nature of wireless channels or fading can be exploited to mitigate the inter-user interference. The proposed amplify-and-forward relaying scheme exploits such channel variations and works for a wide class of channel distributions including Rayleigh fading. We show a general achievable degrees of freedom (DoF) region for this class of Gaussian relay networks. Specifically, the set of all $(d_1,..., d_K)$ such that $d_i\leq 1$ for all $i$ and $\sum_{i=1}^K d_i\leq K_Σ$ is achievable, where $d_i$ is the DoF of the $i^{\operatorname{th}}$ source--destination pair and $K_Σ$ is the maximum integer such that $K_Σ\leq \min_m\{K_m\}$ and $M/K_Σ$ is an integer. We show that surprisingly the achievable DoF region coincides with the cut-set outer bound if $M/\min_m\{K_m\}$ is an integer, thus interference-free communication is possible in terms of DoF. We further characterize an achievable DoF region assuming multi-antenna nodes and general message set, which again coincides with the cut-set outer bound for a certain class of networks.