OpenRaiser/Intern-Atlas huggingface dataset:
Dynamic Task Fetching Over Time Varying Wireless Channels for Mobile Computing Applications
Venue: arXiv cs.NI 2009
Year: 2009

The processing, computation and memory requirements posed by emerging mobile broadband services require adaptive memory management and prefetching techniques at the mobile terminals for satisfactory application performance and sustained device battery lifetime. In this work we investigate a scenario where tasks with varied computational requirements are fetched by a mobile device from a central server over an error prone wireless link. We examine the buffer dynamics at the mobile terminal and the central server under varying wireless channel connectivity and device memory congestion states as variable sizes tasks are executed on the terminal. Our goal is to minimize the latency experienced by these tasks while judiciously utilizing the device buffering capability. We use a dynamic programming framework to model the optimal prefetching policy. We further propose a) a prefetching algorithm Fetch-or- Not (FON), which uses quasi-static assumption on system state to make prefetching decisions, and b) a prefetching policy RFON, which uses randomized approximation to the optimal solution thus obviating the need for dynamic online optimization and substantially reducing the computational complexity. Through performance evaluation under slow and fast fading scenarios we show that proposed algorithms come close to performance of the optimal scheme.
Better Gap-Hamming Lower Bounds via Better Round Elimination
Venue: arXiv cs.CC 2009
Year: 2009

Gap Hamming Distance is a well-studied problem in communication complexity, in which Alice and Bob have to decide whether the Hamming distance between their respective n-bit inputs is less than n/2-sqrt(n) or greater than n/2+sqrt(n). We show that every k-round bounded-error communication protocol for this problem sends a message of at least Omega(n/(k^2\log k)) bits. This lower bound has an exponentially better dependence on the number of rounds than the previous best bound, due to Brody and Chakrabarti. Our communication lower bound implies strong space lower bounds on algorithms for a number of data stream computations, such as approximating the number of distinct elements in a stream. Subsequent to this result, the bound has been improved by some of us to the optimal Omega(n), independent of k, by using different techniques.
Time and Memory Efficient Lempel-Ziv Compression Using Suffix Arrays
Venue: arXiv cs.DS 2009
Year: 2009

The well-known dictionary-based algorithms of the Lempel-Ziv (LZ) 77 family are the basis of several universal lossless compression techniques. These algorithms are asymmetric regarding encoding/decoding time and memory requirements, with the former being much more demanding. In the past years, considerable attention has been devoted to the problem of finding efficient data structures to support these searches, aiming at optimizing the encoders in terms of speed and memory. Hash tables, binary search trees and suffix trees have been widely used for this purpose, as they allow fast search at the expense of memory. Some recent research has focused on suffix arrays (SA), due to their low memory requirements and linear construction algorithms. Previous work has shown how the LZ77 decomposition can be computed using a single SA or an SA with an auxiliary array with the longest common prefix information. The SA-based algorithms use less memory than the tree-based encoders, allocating the strictly necessary amount of memory, regardless of the contents of the text to search/encode. In this paper, we improve on previous work by proposing faster SA-based algorithms for LZ77 encoding and sub-string search, keeping their low memory requirements. For some compression settings, on a large set of benchmark files, our low-memory SA-based encoders are also faster than tree-based encoders. This provides time and memory efficient LZ77 encoding, being a possible replacement for trees on well known encoders like LZMA. Our algorithm is also suited for text classification, because it provides a compact way to describe text in a bag-of-words representation, as well as a fast indexing mechanism that allows to quickly find all the sets of words that start with a given symbol, over a static dictionary.
Rate Distortion and Denoising of Individual Data Using Kolmogorov complexity
Venue: arXiv cs.IT 2009
Year: 2009

We examine the structure of families of distortion balls from the perspective of Kolmogorov complexity. Special attention is paid to the canonical rate-distortion function of a source word which returns the minimal Kolmogorov complexity of all distortion balls containing that word subject to a bound on their cardinality. This canonical rate-distortion function is related to the more standard algorithmic rate-distortion function for the given distortion measure. Examples are given of list distortion, Hamming distortion, and Euclidean distortion. The algorithmic rate-distortion function can behave differently from Shannon's rate-distortion function. To this end, we show that the canonical rate-distortion function can and does assume a wide class of shapes (unlike Shannon's); we relate low algorithmic mutual information to low Kolmogorov complexity (and consequently suggest that certain aspects of the mutual information formulation of Shannon's rate-distortion function behave differently than would an analogous formulation using algorithmic mutual information); we explore the notion that low Kolmogorov complexity distortion balls containing a given word capture the interesting properties of that word (which is hard to formalize in Shannon's theory) and this suggests an approach to denoising; and, finally, we show that the different behavior of the rate-distortion curves of individual source words to some extent disappears after averaging over the source words.
Theory of sexes by Geodakian as it is advanced by Iskrin
Venue: arXiv cs.NE 2009
Year: 2009

In 1960s V.Geodakian proposed a theory that explains sexes as a mechanism for evolutionary adaptation of the species to changing environmental conditions. In 2001 V.Iskrin refined and augmented the concepts of Geodakian and gave a new and interesting explanation to several phenomena which involve sex, and sex ratio, including the war-years phenomena. He also introduced a new concept of the "catastrophic sex ratio." This note is an attempt to digest technical aspects of the new ideas by Iskrin.
Stochastic Formal Methods for Hybrid Systems
Venue: arXiv cs.MS 2009
Year: 2009

We provide a framework to bound the probability that accumulated errors were never above a given threshold on hybrid systems. Such systems are used for example to model an aircraft or a nuclear power plant on one side and its software on the other side. This report contains simple formulas based on Lévy's and Markov's inequalities and it presents a formal theory of random variables with a special focus on producing concrete results. We selected four very common applications that fit in our framework and cover the common practices of hybrid systems that evolve for a long time. We compute the number of bits that remain continuously significant in the first two applications with a probability of failure around one against a billion, where worst case analysis considers that no significant bit remains. We are using PVS as such formal tools force explicit statement of all hypotheses and prevent incorrect uses of theorems.
Linear-Codes-Based Lossless Joint Source-Channel Coding for Multiple-Access Channels
Venue: arXiv cs.IT 2009
Year: 2009

A general lossless joint source-channel coding (JSCC) scheme based on linear codes and random interleavers for multiple-access channels (MACs) is presented and then analyzed in this paper. By the information-spectrum approach and the code-spectrum approach, it is shown that a linear code with a good joint spectrum can be used to establish limit-approaching lossless JSCC schemes for correlated general sources and general MACs, where the joint spectrum is a generalization of the input-output weight distribution. Some properties of linear codes with good joint spectra are investigated. A formula on the "distance" property of linear codes with good joint spectra is derived, based on which, it is further proved that, the rate of any systematic codes with good joint spectra cannot be larger than the reciprocal of the corresponding alphabet cardinality, and any sparse generator matrices cannot yield linear codes with good joint spectra. The problem of designing arbitrary rate coding schemes is also discussed. A novel idea called "generalized puncturing" is proposed, which makes it possible that one good low-rate linear code is enough for the design of coding schemes with multiple rates. Finally, various coding problems of MACs are reviewed in a unified framework established by the code-spectrum approach, under which, criteria and candidates of good linear codes in terms of spectrum requirements for such problems are clearly presented.
Uplink Capacity and Interference Avoidance for Two-Tier Femtocell Networks
Venue: arXiv cs.NI 2009
Year: 2009

Two-tier femtocell networks-- comprising a conventional macrocellular network plus embedded femtocell hotspots-- offer an economically viable solution to achieving high cellular user capacity and improved coverage. With universal frequency reuse and DS-CDMA transmission however, the ensuing cross-tier cochannel interference (CCI) causes unacceptable outage probability. This paper develops an uplink capacity analysis and interference avoidance strategy in such a two-tier CDMA network. We evaluate a network-wide area spectral efficiency metric called the \emph{operating contour (OC)} defined as the feasible combinations of the average number of active macrocell users and femtocell base stations (BS) per cell-site that satisfy a target outage constraint. The capacity analysis provides an accurate characterization of the uplink outage probability, accounting for power control, path-loss and shadowing effects. Considering worst case CCI at a corner femtocell, results reveal that interference avoidance through a time-hopped CDMA physical layer and sectorized antennas allows about a 7x higher femtocell density, relative to a split spectrum two-tier network with omnidirectional femtocell antennas. A femtocell exclusion region and a tier selection based handoff policy offers modest improvements in the OCs. These results provide guidelines for the design of robust shared spectrum two-tier networks.
The Stackelberg Minimum Spanning Tree Game
Venue: arXiv cs.GT 2009
Year: 2009

We consider a one-round two-player network pricing game, the Stackelberg Minimum Spanning Tree game or StackMST. The game is played on a graph (representing a network), whose edges are colored either red or blue, and where the red edges have a given fixed cost (representing the competitor's prices). The first player chooses an assignment of prices to the blue edges, and the second player then buys the cheapest possible minimum spanning tree, using any combination of red and blue edges. The goal of the first player is to maximize the total price of purchased blue edges. This game is the minimum spanning tree analog of the well-studied Stackelberg shortest-path game. We analyze the complexity and approximability of the first player's best strategy in StackMST. In particular, we prove that the problem is APX-hard even if there are only two different red costs, and give an approximation algorithm whose approximation ratio is at most $\min \{k,1+\ln b,1+\ln W\}$, where $k$ is the number of distinct red costs, $b$ is the number of blue edges, and $W$ is the maximum ratio between red costs. We also give a natural integer linear programming formulation of the problem, and show that the integrality gap of the fractional relaxation asymptotically matches the approximation guarantee of our algorithm.
The World as Evolving Information
Venue: arXiv cs.IT 2010
Year: 2010

This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex. The paper presents eight tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, psychological, philosophical, and complexity principles. These are further used to discuss the notions of life, cognition and their evolution.
Optimal Causal Inference: Estimating Stored Information and Approximating Causal Architecture
Venue: arXiv cs.IT 2010
Year: 2010

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate distortion theory to use causal shielding---a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that, in the limit in which a model complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of underlying causal states can be found by optimal causal estimation. A previously derived model complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid over-fitting.
The RDF Virtual Machine
Venue: arXiv cs.PL 2010
Year: 2010

The Resource Description Framework (RDF) is a semantic network data model that is used to create machine-understandable descriptions of the world and is the basis of the Semantic Web. This article discusses the application of RDF to the representation of computer software and virtual computing machines. The Semantic Web is posited as not only a web of data, but also as a web of programs and processes.
Improving Classical Authentication with Quantum Communication
Venue: arXiv cs.IT 2010
Year: 2010

We propose a quantum-enhanced protocol to authenticate classical messages, with improved security with respect to the classical scheme introduced by Brassard in 1983. In that protocol, the shared key is the seed of a pseudo-random generator (PRG) and a hash function is used to create the authentication tag of a public message. We show that a quantum encoding of secret bits offers more security than the classical XOR function introduced by Brassard. Furthermore, we establish the relationship between the bias of a PRG and the amount of information about the key that the attacker can retrieve from a block of authenticated messages. Finally, we prove that quantum resources can improve both the secrecy of the key generated by the PRG and the secrecy of the tag obtained with a hidden hash function.
AMS Without 4-Wise Independence on Product Domains
Venue: arXiv cs.DS 2010
Year: 2010

In their seminal work, Alon, Matias, and Szegedy introduced several sketching techniques, including showing that 4-wise independence is sufficient to obtain good approximations of the second frequency moment. In this work, we show that their sketching technique can be extended to product domains $[n]^k$ by using the product of 4-wise independent functions on $[n]$. Our work extends that of Indyk and McGregor, who showed the result for $k = 2$. Their primary motivation was the problem of identifying correlations in data streams. In their model, a stream of pairs $(i,j) \in [n]^2$ arrive, giving a joint distribution $(X,Y)$, and they find approximation algorithms for how close the joint distribution is to the product of the marginal distributions under various metrics, which naturally corresponds to how close $X$ and $Y$ are to being independent. By using our technique, we obtain a new result for the problem of approximating the $\ell_2$ distance between the joint distribution and the product of the marginal distributions for $k$-ary vectors, instead of just pairs, in a single pass. Our analysis gives a randomized algorithm that is a $(1 \pm ε)$ approximation (with probability $1-δ$) that requires space logarithmic in $n$ and $m$ and proportional to $3^k$.
Path Gain Algebraic Formulation for the Scalar Linear Network Coding Problem
Venue: arXiv cs.IT 2010
Year: 2010

In the algebraic view, the solution to a network coding problem is seen as a variety specified by a system of polynomial equations typically derived by using edge-to-edge gains as variables. The output from each sink is equated to its demand to obtain polynomial equations. In this work, we propose a method to derive the polynomial equations using source-to-sink path gains as the variables. In the path gain formulation, we show that linear and quadratic equations suffice; therefore, network coding becomes equivalent to a system of polynomial equations of maximum degree 2. We present algorithms for generating the equations in the path gains and for converting path gain solutions to edge-to-edge gain solutions. Because of the low degree, simplification is readily possible for the system of equations obtained using path gains. Using small-sized network coding problems, we show that the path gain approach results in simpler equations and determines solvability of the problem in certain cases. On a larger network (with 87 nodes and 161 edges), we show how the path gain approach continues to provide deterministic solutions to some network coding problems.
Modeling Time in Computing: A Taxonomy and a Comparative Survey
Venue: arXiv cs.GL 2010
Year: 2010

The increasing relevance of areas such as real-time and embedded systems, pervasive computing, hybrid systems control, and biological and social systems modeling is bringing a growing attention to the temporal aspects of computing, not only in the computer science domain, but also in more traditional fields of engineering. This article surveys various approaches to the formal modeling and analysis of the temporal features of computer-based systems, with a level of detail that is suitable also for non-specialists. In doing so, it provides a unifying framework, rather than just a comprehensive list of formalisms. The paper first lays out some key dimensions along which the various formalisms can be evaluated and compared. Then, a significant sample of formalisms for time modeling in computing are presented and discussed according to these dimensions. The adopted perspective is, to some extent, historical, going from "traditional" models and formalisms to more modern ones.
Mathematical Structure of Quantum Decision Theory
Venue: arXiv cs.AI 2010
Year: 2010

One of the most complex systems is the human brain whose formalized functioning is characterized by decision theory. We present a "Quantum Decision Theory" of decision making, based on the mathematical theory of separable Hilbert spaces. This mathematical structure captures the effect of superposition of composite prospects, including many incorporated intentions, which allows us to explain a variety of interesting fallacies and anomalies that have been reported to particularize the decision making of real human beings. The theory describes entangled decision making, non-commutativity of subsequent decisions, and intention interference of composite prospects. We demonstrate how the violation of the Savage's sure-thing principle (disjunction effect) can be explained as a result of the interference of intentions, when making decisions under uncertainty. The conjunction fallacy is also explained by the presence of the interference terms. We demonstrate that all known anomalies and paradoxes, documented in the context of classical decision theory, are reducible to just a few mathematical archetypes, all of which finding straightforward explanations in the frame of the developed quantum approach.
Capacity-achieving Feedback Scheme for Gaussian Finite-State Markov Channels with Channel State Information
Venue: arXiv cs.IT 2010
Year: 2010

In this paper, we propose capacity-achieving communication schemes for Gaussian finite-state Markov channels (FSMCs) subject to an average channel input power constraint, under the assumption that the transmitters can have access to delayed noiseless output feedback as well as instantaneous or delayed channel state information (CSI). We show that the proposed schemes reveals connections between feedback communication and feedback control.
Spectral Sparsification of Graphs
Venue: arXiv cs.DS 2010
Year: 2010

We introduce a new notion of graph sparsificaiton based on spectral similarity of graph Laplacians: spectral sparsification requires that the Laplacian quadratic form of the sparsifier approximate that of the original. This is equivalent to saying that the Laplacian of the sparsifier is a good preconditioner for the Laplacian of the original. We prove that every graph has a spectral sparsifier of nearly linear size. Moreover, we present an algorithm that produces spectral sparsifiers in time $\softO{m}$, where $m$ is the number of edges in the original graph. This construction is a key component of a nearly-linear time algorithm for solving linear equations in diagonally-dominant matrcies. Our sparsification algorithm makes use of a nearly-linear time algorithm for graph partitioning that satisfies a strong guarantee: if the partition it outputs is very unbalanced, then the larger part is contained in a subgraph of high conductance.
Rate-Distortion via Markov Chain Monte Carlo
Venue: arXiv cs.IT 2010
Year: 2010

We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstruction sequence from a Boltzmann distribution associated with an energy function that incorporates the distortion between the source and reconstruction, the compressibility of the reconstruction, and the point sought on the rate-distortion curve. To sample from this distribution, we use a `heat bath algorithm': Starting from an initial candidate reconstruction (say the original source sequence), at every iteration, an index i is chosen and the i-th sequence component is replaced by drawing from the conditional probability distribution for that component given all the rest. At the end of this process, the encoder conveys the reconstruction to the decoder using universal lossless compression. The complexity of each iteration is independent of the sequence length and only linearly dependent on a certain context parameter (which grows sub-logarithmically with the sequence length). We show that the proposed algorithms achieve optimum rate-distortion performance in the limits of large number of iterations, and sequence length, when employed on any stationary ergodic source. Experimentation shows promising initial results. Employing our lossy compressors on noisy data, with appropriately chosen distortion measure and level, followed by a simple de-randomization operation, results in a family of denoisers that compares favorably (both theoretically and in practice) with other MCMC-based schemes, and with the Discrete Universal Denoiser (DUDE).