OpenRaiser/Intern-Atlas huggingface dataset:
Performance Analysis for Heterogeneous Cellular Systems with Range Expansion
Venue: arXiv cs.IT 2012
Year: 2012

Recently heterogeneous base station structure has been adopted in cellular systems to enhance system throughput and coverage. In this paper, the uplink coverage probability for the heterogeneous cellular systems is analyzed and derived in closed-form. The randomness on the locations and number of mobile users is taken into account in the analysis. Based on the analytical results, the impacts of various system parameters on the uplink performance are investigated in detail. The correctness of the analytical results is also verified by simulation results. These analytical results can thus serve as a guidance for system design without the need of time consuming simulations.
Lattice Coding and the Generalized Degrees of Freedom of the Interference Channel with Relay
Venue: arXiv cs.IT 2012
Year: 2012

The generalized degrees of freedom (GDoF) of the symmetric two-user Gaussian interference relay channel (IRC) is studied. While it is known that the relay does not increase the DoF of the IC, this is not known for the more general GDoF. For the characterization of the GDoF, new sum-capacity upper bounds and lower bounds are derived. The lower bounds are obtained by a new scheme, which is based on functional decode-and-forward (FDF). The GDoF is characterized for the regime in which the source-relay link is weaker than the interference link, which constitutes half the overall space of channel parameters. It is shown that the relay can indeed increase the GDoF of the IRC and that it is achieved by FDF.
INSTRUCT: Space-Efficient Structure for Indexing and Complete Query Management of String Databases
Venue: arXiv cs.DB 2012
Year: 2012

The tremendous expanse of search engines, dictionary and thesaurus storage, and other text mining applications, combined with the popularity of readily available scanning devices and optical character recognition tools, has necessitated efficient storage, retrieval and management of massive text databases for various modern applications. For such applications, we propose a novel data structure, INSTRUCT, for efficient storage and management of sequence databases. Our structure uses bit vectors for reusing the storage space for common triplets, and hence, has a very low memory requirement. INSTRUCT efficiently handles prefix and suffix search queries in addition to the exact string search operation by iteratively checking the presence of triplets. We also propose an extension of the structure to handle substring search efficiently, albeit with an increase in the space requirements. This extension is important in the context of trie-based solutions which are unable to handle such queries efficiently. We perform several experiments portraying that INSTRUCT outperforms the existing structures by nearly a factor of two in terms of space requirements, while the query times are better. The ability to handle insertion and deletion of strings in addition to supporting all kinds of queries including exact search, prefix/suffix search and substring search makes INSTRUCT a complete data structure.
A new path algorithm for the weighted multi-graphs WMGPA: application to the Direct Topological Method
Venue: arXiv cs.DS 2012
Year: 2012

The aim of this paper is to present an algorithm which gives all the possible paths that start from a specific node to another of a weighted multi-graph. This algorithm is intended to be applied for the direct topological method.
Robust Principal Component Analysis Using Statistical Estimators
Venue: arXiv cs.AI 2012
Year: 2012

Principal Component Analysis (PCA) finds a linear mapping and maximizes the variance of the data which makes PCA sensitive to outliers and may cause wrong eigendirection. In this paper, we propose techniques to solve this problem; we use the data-centering method and reestimate the covariance matrix using robust statistic techniques such as median, robust scaling which is a booster to data-centering and Huber M-estimator which measures the presentation of outliers and reweight them with small values. The results on several real world data sets show that our proposed method handles outliers and gains better results than the original PCA and provides the same accuracy with lower computation cost than the Kernel PCA using the polynomial kernel in classification tasks.
Multimedia Traffic Routing in Multilayer WDM Networks
Venue: arXiv cs.NI 2012
Year: 2012

The advent of real-time multimedia services over the Internet has stimulated new technologies for expanding the information carrying capacity of optical network backbones. Multilayer wavelength division multiplexing (WDM) packet switching is an emerging technology for increasing the bandwidth of optical networks. Two algorithms for the routing of the multimedia traffic flows were applied: (i) Capacitated Shortest Path First (CSPF) routing, which minimizes the distance of each flow linking the given source and destination nodes and satisfying capacity constraints; and (ii) Flow Deviation Algorithm (FDA) routing, which minimizes the network-wide average packet delay.
Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks
Venue: arXiv cs.IT 2012
Year: 2012

This paper investigates the performance of an orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) spectrum sharing communication system that assumes random allocation and absence of the primary user's (PU) channel occupation information, i.e., no spectrum sensing is employed to acquire information about the availability of unused subcarriers. In case of a single secondary user (SU) in the secondary network, due to the lack of information of PUs' activities, the SU randomly allocates the subcarriers of the primary network and collide with the PUs' subcarriers with a certain probability. To maintain the quality of service (QoS) requirement of PUs, the interference that SU causes onto PUs is controlled by adjusting SU's transmit power below a predefined threshold, referred to as interference temperature. In this work, the average capacity of SU with subcarrier collisions is employed as performance measure to investigate the proposed random allocation scheme for both general and Rayleigh channel fading models. Bounds and scaling laws of average capacity with respect to the number of SU's, PUs' and available subcarriers are derived. In addition, in the presence of multiple SUs, the multiuser diversity gain of SUs assuming an opportunistic scheduling is also investigated. To avoid the interference at the SUs that might be caused by the random allocation scheme and obtain the maximum sum rate for SUs based on the available subcarriers, an efficient centralized sequential algorithm based on the opportunistic scheduling and random allocation (utilization) methods is proposed to ensure the orthogonality of assigned subcarriers.
Parameterized Runtime Analyses of Evolutionary Algorithms for the Euclidean Traveling Salesperson Problem
Venue: arXiv cs.NE 2012
Year: 2012

Parameterized runtime analysis seeks to understand the influence of problem structure on algorithmic runtime. In this paper, we contribute to the theoretical understanding of evolutionary algorithms and carry out a parameterized analysis of evolutionary algorithms for the Euclidean traveling salesperson problem (Euclidean TSP). We investigate the structural properties in TSP instances that influence the optimization process of evolutionary algorithms and use this information to bound the runtime of simple evolutionary algorithms. Our analysis studies the runtime in dependence of the number of inner points $k$ and shows that $(μ+ λ)$ evolutionary algorithms solve the Euclidean TSP in expected time $O((μ/λ) \cdot n^3γ(ε) + nγ(ε) + (μ/λ) \cdot n^{4k}(2k-1)!)$ where $γ$ is a function of the minimum angle $ε$ between any three points. Finally, our analysis provides insights into designing a mutation operator that improves the upper bound on expected runtime. We show that a mixed mutation strategy that incorporates both 2-opt moves and permutation jumps results in an upper bound of $O((μ/λ) \cdot n^3γ(ε) + nγ(ε) + (μ/λ) \cdot n^{2k}(k-1)!)$ for the $(μ+λ)$ EA.
Significance of Quality Metrics in Software Development Process
Venue: arXiv cs.SE 2012
Year: 2012

In recent years, Software has become an indispensable part of every segment from simple Office Automation to Space Technology and E-mail to E-commerce. The evolution in Software architecture is always an open issue for researchers to address complex systems with numerous domain-specific requirements. Success of a system is based on quality outcome of every stage of development with proper measuring techniques. Metrics are measures of Process, Product and People (P3) who are involved in the development process, acts as quality indicators reflecting the maturity level of the company. Several process metrics has been defined and practiced to measure the software deliverables comprising of requirement analysis through maintenance. Metrics at each stage has its own significance to increase the quality of the milestones and hence the quality of end product. This paper highlights the significance of software quality metrics followed at major phases of software development namely requirement, design and implementation. This paper thereby aims to bring awareness towards existing metrics and leads towards enhancement of them in order to reflect continuous process improvement in the company for their sustainability in the market.
Distributed backbone structure for deterministic algorithms in the SINR model of wireless networks
Venue: arXiv cs.DC 2012
Year: 2012

The Signal-to-Interference-and-Noise-Ratio (SINR) physical model is one of the legitimate models of wireless networks. Despite of the vast amount of study done in design and analysis of centralized algorithms supporting wireless communication under the SINR physical model, little is known about distributed algorithms in this model, especially deterministic ones. In this work we construct, in a deterministic distributed way, a backbone structure on the top of a given wireless network, which can be used for transforming many algorithms designed in a simpler model of ad hoc broadcast networks without interference into the SINR physical model with uniform power of stations, without increasing their asymptotic time complexity. The time cost of the backbone data structure construction is only O(Delta polylog n) rounds, where Delta is roughly the inverse of network density and n is the number of nodes in the whole network. The core of the construction is a novel combinatorial structure called SINR-selector, which is introduced and constructed in this paper. We demonstrate the power of the backbone data structure by using it for obtaining efficient O(D+Delta polylog n)-round and O(D+k+Delta polylog n)-round deterministic distributed solutions for leader election and multi-broadcast, respectively, where D is the network diameter and k is the number of messages to be disseminated.
Optimization of Quadratic Forms: NP Hard Problems : Neural Networks
Venue: arXiv cs.CC 2012
Year: 2012

In this research paper, the problem of optimization of a quadratic form over the convex hull generated by the corners of hypercube is attempted and solved. Some results related to stable states/vectors, anti-stable states/vectors (over the hypercube) are discussed. Some results related to the computation of global optimum stable state (an NP hard problem) are discussed. It is hoped that the results shed light on resolving the P \neq NP problem.
A Game-Theoretical Approach for Finding Optimal Strategies in an Intruder Classification Game
Venue: arXiv cs.GT 2012
Year: 2012

We consider a game in which a strategic defender classifies an intruder as spy or spammer. The classification is based on the number of file server and mail server attacks observed during a fixed window. The spammer naively attacks (with a known distribution) his main target: the mail server. The spy strategically selects the number of attacks on his main target: the file server. The defender strategically selects his classification policy: a threshold on the number of file server attacks. We model the interaction of the two players (spy and defender) as a nonzero-sum game: The defender needs to balance missed detections and false alarms in his objective function, while the spy has a tradeoff between attacking the file server more aggressively and increasing the chances of getting caught. We give a characterization of the Nash equilibria in mixed strategies, and demonstrate how the Nash equilibria can be computed in polynomial time. Our characterization gives interesting and non-intuitive insights on the players' strategies at equilibrium: The defender uniformly randomizes between a set of thresholds that includes very large values. The strategy of the spy is a truncated version of the spammer's distribution. We present numerical simulations that validate and illustrate our theoretical results.
Towards Algorithmic Synthesis of Synchronization for Shared-Memory Concurrent Programs
Venue: arXiv cs.LO 2012
Year: 2012

We present a framework that takes a concurrent program composed of unsynchronized processes, along with a temporal specification of their global concurrent behaviour, and automatically generates a concurrent program with synchronization ensuring correct global behaviour. Our methodology supports finite-state concurrent programs composed of processes that may have local and shared variables, may be straight-line or branching programs, may be ongoing or terminating, and may have program-initialized or user-initialized variables. The specification language is an extension of propositional Computation Tree Logic (CTL) that enables easy specification of safety and liveness properties over control and data variables. The framework also supports synthesis of synchronization at different levels of abstraction and granularity.
Incubators vs Zombies: Fault-Tolerant, Short, Thin and Lanky Spanners for Doubling Metrics
Venue: arXiv cs.DS 2012
Year: 2012

Recently Elkin and Solomon gave a construction of spanners for doubling metrics that has constant maximum degree, hop-diameter O(log n) and lightness O(log n) (i.e., weight O(log n)w(MST). This resolves a long standing conjecture proposed by Arya et al. in a seminal STOC 1995 paper. However, Elkin and Solomon's spanner construction is extremely complicated; we offer a simple alternative construction that is very intuitive and is based on the standard technique of net tree with cross edges. Indeed, our approach can be readily applied to our previous construction of k-fault tolerant spanners (ICALP 2012) to achieve k-fault tolerance, maximum degree O(k^2), hop-diameter O(log n) and lightness O(k^3 log n).
Estimating Node Influenceability in Social Networks
Venue: arXiv cs.SI 2012
Year: 2012

Influence analysis is a fundamental problem in social network analysis and mining. The important applications of the influence analysis in social network include influence maximization for viral marketing, finding the most influential nodes, online advertising, etc. For many of these applications, it is crucial to evaluate the influenceability of a node. In this paper, we study the problem of evaluating influenceability of nodes in social network based on the widely used influence spread model, namely, the independent cascade model. Since this problem is #P-complete, most existing work is based on Naive Monte-Carlo (\nmc) sampling. However, the \nmc estimator typically results in a large variance, which significantly reduces its effectiveness. To overcome this problem, we propose two families of new estimators based on the idea of stratified sampling. We first present two basic stratified sampling (\bss) estimators, namely \bssi estimator and \bssii estimator, which partition the entire population into $2^r$ and $r+1$ strata by choosing $r$ edges respectively. Second, to further reduce the variance, we find that both \bssi and \bssii estimators can be recursively performed on each stratum, thus we propose two recursive stratified sampling (\rss) estimators, namely \rssi estimator and \rssii estimator. Theoretically, all of our estimators are shown to be unbiased and their variances are significantly smaller than the variance of the \nmc estimator. Finally, our extensive experimental results on both synthetic and real datasets demonstrate the efficiency and accuracy of our new estimators.
Bottom-up Broadband Initiatives in the Commons for Europe Project
Venue: arXiv cs.CY 2012
Year: 2012

This paper offers an overview of the Commons for Europe (C4EU) project and the role of Bottom-up Broadband (BuB) in developing the information society. BuB is characterized by the fact that the beneficiaries of the networks actively participate in the planning, deployment and maintenance tasks. For the beneficiaries, this represent a paradigm shift from a consumer-only position to an active-participant position. We summarize a representative set of the BuB pilot proposals that have been considered in the context of the C4EU project. A selection of these proposals will be executed and carefully documented to define good practices in BuB deployments. The documentation will include project templates, work plans, case studies, replicable success models and regulatory guidelines. The overall goal of the project is to assess the validity of the BuB model to effectively and efficiently complement exiting traditional deployments in satisfying the networking and technological needs of the European citizens and organizations.
A Fast Projected Fixed-Point Algorithm for Large Graph Matching
Venue: arXiv cs.CV 2012
Year: 2012

We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high computational complexity and therefore do not have good scalability with respect to graph size. For matching two weighted graphs of $n$ nodes, our algorithm has time complexity only $O(n^3)$ per iteration and space complexity $O(n^2)$. In addition to its scalability, our algorithm is easy to implement, robust, and able to match undirected weighted attributed graphs of different sizes. While the convergence rate of previous iterative graph matching algorithms is unknown, our algorithm is theoretically guaranteed to converge at a linear rate. Extensive experiments on large synthetic and real graphs (more than 1,000 nodes) were conducted to evaluate the performance of various algorithms. Results show that in most cases our proposed algorithm achieves better performance than previous state-of-the-art algorithms in terms of both speed and accuracy in large graph matching. In particular, with high accuracy, our algorithm takes only a few seconds (in a PC) to match two graphs of 1,000 nodes.
Background Subtraction for Online Calibration of Baseline RSS in RF Sensing Networks
Venue: arXiv cs.NI 2012
Year: 2012

Radio frequency (RF) sensing networks are a class of wireless sensor networks (WSNs) which use RF signals to accomplish tasks such as passive device-free localization and tracking. The algorithms used for these tasks usually require access to measurements of baseline received signal strength (RSS) on each link. However, it is often impossible to collect this calibration data (measurements collected during an offline calibration period when the region of interest is empty of targets). We propose adapting background subtraction methods from the field of computer vision to estimate baseline RSS values from measurements taken while the system is online and obstructions may be present. This is done by forming an analogy between the intensity of a background pixel in an image and the baseline RSS value of a WSN link and then translating the concepts of temporal similarity, spatial similarity and spatial ergodicity which underlie specific background subtraction algorithms to WSNs. Using experimental data, we show that these techniques are capable of estimating baseline RSS values with enough accuracy that RF tomographic tracking can be carried out in a variety of different environments without the need for a calibration period.
On the toggling-branching recurrence of Computability Logic
Venue: arXiv cs.LO 2012
Year: 2012

We introduce a new, substantially simplified version of the toggling-branching recurrence operation of Computability Logic, prove its equivalence to Japaridze's old, "canonical" version, and also prove that both versions preserve the static property of their arguments.
On the Hardness of Entropy Minimization and Related Problems
Venue: arXiv cs.IT 2012
Year: 2012

We investigate certain optimization problems for Shannon information measures, namely, minimization of joint and conditional entropies $H(X,Y)$, $H(X|Y)$, $H(Y|X)$, and maximization of mutual information $I(X;Y)$, over convex regions. When restricted to the so-called transportation polytopes (sets of distributions with fixed marginals), very simple proofs of NP-hardness are obtained for these problems because in that case they are all equivalent, and their connection to the well-known \textsc{Subset sum} and \textsc{Partition} problems is revealed. The computational intractability of the more general problems over arbitrary polytopes is then a simple consequence. Further, a simple class of polytopes is shown over which the above problems are not equivalent and their complexity differs sharply, namely, minimization of $H(X,Y)$ and $H(Y|X)$ is trivial, while minimization of $H(X|Y)$ and maximization of $I(X;Y)$ are strongly NP-hard problems. Finally, two new (pseudo)metrics on the space of discrete probability distributions are introduced, based on the so-called variation of information quantity, and NP-hardness of their computation is shown.
Controllers with Minimal Observation Power (Application to Timed Systems)
Venue: arXiv cs.SY 2012
Year: 2012

We consider the problem of controller synthesis under imperfect information in a setting where there is a set of available observable predicates equipped with a cost function. The problem that we address is the computation of a subset of predicates sufficient for control and whose cost is minimal. Our solution avoids a full exploration of all possible subsets of predicates and reuses some information between different iterations. We apply our approach to timed systems. We have developed a tool prototype and analyze the performance of our optimization algorithm on two case studies.
Stable Independence in Perfect Maps
Venue: arXiv cs.AI 2012
Year: 2012

With the aid of the concept of stable independence we can construct, in an efficient way, a compact representation of a semi-graphoid independence relation. We show that this representation provides a new necessary condition for the existence of a directed perfect map for the relation. The test for this condition is based to a large extent on the transitivity property of a special form of d-separation. The complexity of the test is linear in the size of the representation. The test, moreover, brings the additional benefit that it can be used to guide the early stages of network construction.
A Differential Semantics of Lazy AR Propagation
Venue: arXiv cs.AI 2012
Year: 2012

In this paper we present a differential semantics of Lazy AR Propagation (LARP) in discrete Bayesian networks. We describe how both single and multi dimensional partial derivatives of the evidence may easily be calculated from a junction tree in LARP equilibrium. We show that the simplicity of the calculations stems from the nature of LARP. Based on the differential semantics we describe how variable propagation in the LARP architecture may give access to additional partial derivatives. The cautious LARP (cLARP) scheme is derived to produce a flexible cLARP equilibrium that offers additional opportunities for calculating single and multidimensional partial derivatives of the evidence and subsets of the evidence from a single propagation. The results of an empirical evaluation illustrates how the access to a largely increased number of partial derivatives comes at a low computational cost.