OpenRaiser/Intern-Atlas huggingface dataset:
Graph-Controlled Insertion-Deletion Systems
Venue: arXiv cs.FL 2010
Year: 2010

In this article, we consider the operations of insertion and deletion working in a graph-controlled manner. We show that like in the case of context-free productions, the computational power is strictly increased when using a control graph: computational completeness can be obtained by systems with insertion or deletion rules involving at most two symbols in a contextual or in a context-free manner and with the control graph having only four nodes.
Remembering Chandra Kintala
Venue: arXiv cs.FL 2010
Year: 2010

With this contribution we would like to remember Chandra M. R. Kintala who passed away in November 2009. We will give short overviews of his CV and his contributions to the field of theoretical and applied computer science and, given the opportunity, will attempt to present the current state of limited nondeterminism and limited resources for machines. Finally, we will briefly touch on some research topics which hopefully will be addressed in the not so distant future.
On the Complexity of the Evaluation of Transient Extensions of Boolean Functions
Venue: arXiv cs.CC 2010
Year: 2010

Transient algebra is a multi-valued algebra for hazard detection in gate circuits. Sequences of alternating 0's and 1's, called transients, represent signal values, and gates are modeled by extensions of boolean functions to transients. Formulas for computing the output transient of a gate from the input transients are known for NOT, AND, OR} and XOR gates and their complements, but, in general, even the problem of deciding whether the length of the output transient exceeds a given bound is NP-complete. We propose a method of evaluating extensions of general boolean functions. We introduce and study a class of functions with the following property: Instead of evaluating an extension of a boolean function on a given set of transients, it is possible to get the same value by using transients derived from the given ones, but having length at most 3. We prove that all functions of three variables, as well as certain other functions, have this property, and can be efficiently evaluated.
Minimization of Handoff latency by co-ordinate evaluation method using GPS based map
Venue: arXiv cs.NI 2010
Year: 2010

Handoff has become an essential criterion in mobile communication system, specially in urban areas, owing to the limited coverage area of Access Points (AP). Handover of calls between two Base Stations (BSs) is encountered frequently and it is essentially required to minimize the delay of the process. Many solutions attempting to improve this process have been proposed but only a few use geo-location systems in the management of the handover. Here we propose to minimize the handoff latency by minimizing the number of APs scanned by the Mobile Node (MN) during each handoff procedure. We consider the whole topographical area as a two dimensional plane. By GPS, we can note down the co-ordinates of the MN at any instant. The average rate of change of its latitudinal distance and longitudinal distance with a specific time period is evaluated at the end of the given time period. With the knowledge of the given parameter, it is possible to determine the latitude and longitude of the MN after a particular instant of time. Hence, the direction of motion of the MN can be determined, which in turns gives the AP towards which the MN is headings. This reduces the number of APs to be scanned. Thus, on an overall basis, the handoff latency can be reduced by almost half to one third of its value.
Understanding Space in Proof Complexity: Separations and Trade-offs via Substitutions
Venue: arXiv cs.CC 2010
Year: 2010

For current state-of-the-art DPLL SAT-solvers the two main bottlenecks are the amounts of time and memory used. In proof complexity, these resources correspond to the length and space of resolution proofs. There has been a long line of research investigating these proof complexity measures, but while strong results have been established for length, our understanding of space and how it relates to length has remained quite poor. In particular, the question whether resolution proofs can be optimized for length and space simultaneously, or whether there are trade-offs between these two measures, has remained essentially open. In this paper, we remedy this situation by proving a host of length-space trade-off results for resolution. Our collection of trade-offs cover almost the whole range of values for the space complexity of formulas, and most of the trade-offs are superpolynomial or even exponential and essentially tight. Using similar techniques, we show that these trade-offs in fact extend to the exponentially stronger k-DNF resolution proof systems, which operate with formulas in disjunctive normal form with terms of bounded arity k. We also answer the open question whether the k-DNF resolution systems form a strict hierarchy with respect to space in the affirmative. Our key technical contribution is the following, somewhat surprising, theorem: Any CNF formula F can be transformed by simple variable substitution into a new formula F' such that if F has the right properties, F' can be proven in essentially the same length as F, whereas on the other hand the minimal number of lines one needs to keep in memory simultaneously in any proof of F' is lower-bounded by the minimal number of variables needed simultaneously in any proof of F. Applying this theorem to so-called pebbling formulas defined in terms of pebble games on directed acyclic graphs, we obtain our results.
Breaking the Legend: Maxmin Fairness notion is no longer effective
Venue: arXiv cs.NI 2010
Year: 2010

In this paper we analytically propose an alternative approach to achieve better fairness in scheduling mechanisms which could provide better quality of service particularly for real time application. Our proposal oppose the allocation of the bandwidth which adopted by all previous scheduling mechanism. It rather adopt the opposition approach be proposing the notion of Maxmin-charge which fairly distribute the congestion. Furthermore, analytical proposition of novel mechanism named as Just Queueing is been demonstrated.
Mechanism Design via Correlation Gap
Venue: arXiv cs.GT 2010
Year: 2010

For revenue and welfare maximization in single-dimensional Bayesian settings, Chawla et al. (STOC10) recently showed that sequential posted-price mechanisms (SPMs), though simple in form, can perform surprisingly well compared to the optimal mechanisms. In this paper, we give a theoretical explanation of this fact, based on a connection to the notion of correlation gap. Loosely speaking, for auction environments with matroid constraints, we can relate the performance of a mechanism to the expectation of a monotone submodular function over a random set. This random set corresponds to the winner set for the optimal mechanism, which is highly correlated, and corresponds to certain demand set for SPMs, which is independent. The notion of correlation gap of Agrawal et al.\ (SODA10) quantifies how much we {}"lose" in the expectation of the function by ignoring correlation in the random set, and hence bounds our loss in using certain SPM instead of the optimal mechanism. Furthermore, the correlation gap of a monotone and submodular function is known to be small, and it follows that certain SPM can approximate the optimal mechanism by a good constant factor. Exploiting this connection, we give tight analysis of a greedy-based SPM of Chawla et al.\ for several environments. In particular, we show that it gives an $e/(e-1)$-approximation for matroid environments, gives asymptotically a $1/(1-1/\sqrt{2πk})$-approximation for the important sub-case of $k$-unit auctions, and gives a $(p+1)$-approximation for environments with $p$-independent set system constraints.
Guessing Revisited: A Large Deviations Approach
Venue: arXiv cs.IT 2010
Year: 2010

The problem of guessing a random string is revisited. A close relation between guessing and compression is first established. Then it is shown that if the sequence of distributions of the information spectrum satisfies the large deviation property with a certain rate function, then the limiting guessing exponent exists and is a scalar multiple of the Legendre-Fenchel dual of the rate function. Other sufficient conditions related to certain continuity properties of the information spectrum are briefly discussed. This approach highlights the importance of the information spectrum in determining the limiting guessing exponent. All known prior results are then re-derived as example applications of our unifying approach.
A Single-Instance Incremental SAT Formulation of Proof- and Counterexample-Based Abstraction
Venue: arXiv cs.LO 2010
Year: 2010

This paper presents an efficient, combined formulation of two widely used abstraction methods for bit-level verification: counterexample-based abstraction (CBA) and proof-based abstraction (PBA). Unlike previous work, this new method is formulated as a single, incremental SAT-problem, interleaving CBA and PBA to develop the abstraction in a bottom-up fashion. It is argued that the new method is simpler conceptually and implementation-wise than previous approaches. As an added bonus, proof-logging is not required for the PBA part, which allows for a wider set of SAT-solvers to be used.
Notes on Lattice-Reduction-Aided MMSE Equalization
Venue: arXiv cs.IT 2010
Year: 2010

Over the last years, novel low-complexity approaches to the equalization of MIMO channels have gained much attention. Thereby, methods based on lattice basis reduction are of special interest, as they achieve the optimum diversity order. In this paper, a tutorial overview on LRA equalization optimized according to the MMSE criterion is given. It is proven that applying the zero-forcing BLAST algorithm to a suitably augmented channel matrix (the inverse of the square root of the correlation matrix of the data symbols times the noise variance forms its lower part) results in the optimum solution. This fact is already widely used but lacks a formal proof. It turns out that it is more important to take the correlations of the data correctly into account than what type of lattice reduction actually is used.
Linear Precoding in Cooperative MIMO Cellular Networks with Limited Coordination Clusters
Venue: arXiv cs.IT 2010
Year: 2010

In a cooperative multiple-antenna downlink cellular network, maximization of a concave function of user rates is considered. A new linear precoding technique called soft interference nulling (SIN) is proposed, which performs at least as well as zero-forcing (ZF) beamforming. All base stations share channel state information, but each user's message is only routed to those that participate in the user's coordination cluster. SIN precoding is particularly useful when clusters of limited sizes overlap in the network, in which case traditional techniques such as dirty paper coding or ZF do not directly apply. The SIN precoder is computed by solving a sequence of convex optimization problems. SIN under partial network coordination can outperform ZF under full network coordination at moderate SNRs. Under overlapping coordination clusters, SIN precoding achieves considerably higher throughput compared to myopic ZF, especially when the clusters are large.
Patterns of Individual Shopping Behavior
Venue: arXiv cs.CY 2010
Year: 2010

Much of economic theory is built on observations of aggregate, rather than individual, behavior. Here, we present novel findings on human shopping patterns at the resolution of a single purchase. Our results suggest that much of our seemingly elective activity is actually driven by simple routines. While the interleaving of shopping events creates randomness at the small scale, on the whole consumer behavior is largely predictable. We also examine income-dependent differences in how people shop, and find that wealthy individuals are more likely to bundle shopping trips. These results validate previous work on mobility from cell phone data, while describing the unpredictability of behavior at higher resolution.
Cooperative Secret Communication with Artificial Noise in Symmetric Interference Channel
Venue: arXiv cs.IT 2010
Year: 2010

We consider the symmetric Gaussian interference channel where two users try to enhance their secrecy rates in a cooperative manner. Artificial noise is introduced along with useful information. We derive the power control and artificial noise parameter for two kinds of optimal points, max-min point and single user point. It is shown that there exists a critical value $P_c$ of the power constraint, below which the max-min point is an optimal point on the secrecy rate region, and above which time-sharing between single user points achieves larger secrecy rate pairs. It is also shown that artificial noise can help to enlarge the secrecy rate region, in particular on the single user point.
Asynchronous logic circuits and sheaf obstructions
Venue: arXiv cs.AR 2010
Year: 2010

This article exhibits a particular encoding of logic circuits into a sheaf formalism. The central result of this article is that there exists strictly more information available to a circuit designer in this setting than exists in static truth tables, but less than exists in event-level simulation. This information is related to the timing behavior of the logic circuits, and thereby provides a ``bridge'' between static logic analysis and detailed simulation.
Networked Computing in Wireless Sensor Networks for Structural Health Monitoring
Venue: arXiv cs.NI 2010
Year: 2010

This paper studies the problem of distributed computation over a network of wireless sensors. While this problem applies to many emerging applications, to keep our discussion concrete we will focus on sensor networks used for structural health monitoring. Within this context, the heaviest computation is to determine the singular value decomposition (SVD) to extract mode shapes (eigenvectors) of a structure. Compared to collecting raw vibration data and performing SVD at a central location, computing SVD within the network can result in significantly lower energy consumption and delay. Using recent results on decomposing SVD, a well-known centralized operation, into components, we seek to determine a near-optimal communication structure that enables the distribution of this computation and the reassembly of the final results, with the objective of minimizing energy consumption subject to a computational delay constraint. We show that this reduces to a generalized clustering problem; a cluster forms a unit on which a component of the overall computation is performed. We establish that this problem is NP-hard. By relaxing the delay constraint, we derive a lower bound to this problem. We then propose an integer linear program (ILP) to solve the constrained problem exactly as well as an approximate algorithm with a proven approximation ratio. We further present a distributed version of the approximate algorithm. We present both simulation and experimentation results to demonstrate the effectiveness of these algorithms.
A Cross-Layer Approach for Minimizing Interference and Latency of Medium Access in Wireless Sensor Networks
Venue: arXiv cs.NI 2010
Year: 2010

In low power wireless sensor networks, MAC protocols usually employ periodic sleep/wake schedule to reduce idle listening time. Even though this mechanism is simple and efficient, it results in high end-to-end latency and low throughput. On the other hand, the previously proposed CSMA/CA-based MAC protocols have tried to reduce inter-node interference at the cost of increased latency and lower network capacity. In this paper we propose IAMAC, a CSMA/CA sleep/wake MAC protocol that minimizes inter-node interference, while also reduces per-hop delay through cross-layer interactions with the network layer. Furthermore, we show that IAMAC can be integrated into the SP architecture to perform its inter-layer interactions. Through simulation, we have extensively evaluated the performance of IAMAC in terms of different performance metrics. Simulation results confirm that IAMAC reduces energy consumption per node and leads to higher network lifetime compared to S-MAC and Adaptive S-MAC, while it also provides lower latency than S-MAC. Throughout our evaluations we have considered IAMAC in conjunction with two error recovery methods, i.e., ARQ and Seda. It is shown that using Seda as the error recovery mechanism of IAMAC results in higher throughput and lifetime compared to ARQ.
Algebraic Signal Processing Theory: Cooley-Tukey Type Algorithms for Polynomial Transforms Based on Induction
Venue: arXiv cs.IT 2010
Year: 2010

A polynomial transform is the multiplication of an input vector $x\in\C^n$ by a matrix $\PT_{b,α}\in\C^{n\times n},$ whose $(k,\ell)$-th element is defined as $p_\ell(α_k)$ for polynomials $p_\ell(x)\in\C[x]$ from a list $b=\{p_0(x),\dots,p_{n-1}(x)\}$ and sample points $α_k\in\C$ from a list $α=\{α_0,\dots,α_{n-1}\}$. Such transforms find applications in the areas of signal processing, data compression, and function interpolation. Important examples include the discrete Fourier and cosine transforms. In this paper we introduce a novel technique to derive fast algorithms for polynomial transforms. The technique uses the relationship between polynomial transforms and the representation theory of polynomial algebras. Specifically, we derive algorithms by decomposing the regular modules of these algebras as a stepwise induction. As an application, we derive novel $O(n\log{n})$ general-radix algorithms for the discrete Fourier transform and the discrete cosine transform of type 4.
Sparsity-Cognizant Total Least-Squares for Perturbed Compressive Sampling
Venue: arXiv cs.IT 2010
Year: 2010

Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data vector as well as in the regression matrix. However, existing TLS approaches do not account for sparsity possibly present in the unknown vector of regression coefficients. On the other hand, sparsity is the key attribute exploited by modern compressive sampling and variable selection approaches to linear regression, which include noise in the data, but do not account for perturbations in the regression matrix. The present paper fills this gap by formulating and solving TLS optimization problems under sparsity constraints. Near-optimum and reduced-complexity suboptimum sparse (S-) TLS algorithms are developed to address the perturbed compressive sampling (and the related dictionary learning) challenge, when there is a mismatch between the true and adopted bases over which the unknown vector is sparse. The novel S-TLS schemes also allow for perturbations in the regression matrix of the least-absolute selection and shrinkage selection operator (Lasso), and endow TLS approaches with ability to cope with sparse, under-determined "errors-in-variables" models. Interesting generalizations can further exploit prior knowledge on the perturbations to obtain novel weighted and structured S-TLS solvers. Analysis and simulations demonstrate the practical impact of S-TLS in calibrating the mismatch effects of contemporary grid-based approaches to cognitive radio sensing, and robust direction-of-arrival estimation using antenna arrays.
On the Performance of Spectrum Sensing Algorithms using Multiple Antennas
Venue: arXiv cs.IT 2010
Year: 2010

In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue based detection (EBD), have attracted a lot of attention. In this paper, we are interested in deriving the asymptotic distributions of the test statistics of the EBD algorithms. Two EBD algorithms using sample covariance matrices are considered: maximum eigenvalue detection (MED) and condition number detection (CND). The earlier studies usually assume that the number of antennas (K) and the number of samples (N) are both large, thus random matrix theory (RMT) can be used to derive the asymptotic distributions of the maximum and minimum eigenvalues of the sample covariance matrices. While assuming the number of antennas being large simplifies the derivations, in practice, the number of antennas equipped at a single secondary user is usually small, say 2 or 3, and once designed, this antenna number is fixed. Thus in this paper, our objective is to derive the asymptotic distributions of the eigenvalues and condition numbers of the sample covariance matrices for any fixed K but large N, from which the probability of detection and probability of false alarm can be obtained. The proposed methodology can also be used to analyze the performance of other EBD algorithms. Finally, computer simulations are presented to validate the accuracy of the derived results.
Generalising tractable VCSPs defined by symmetric tournament pair multimorphisms
Venue: arXiv cs.CC 2010
Year: 2010

We study optimisation problems that can be formulated as valued constraint satisfaction problems (VCSP). A problem from VCSP is characterised by a \emph{constraint language}, a fixed set of cost functions taking finite and infinite costs over a finite domain. An instance of the problem is specified by a sum of cost functions from the language and the goal is to minimise the sum. We are interested in \emph{tractable} constraint languages; that is, languages that give rise to VCSP instances solvable in polynomial time. Cohen et al. (AIJ'06) have shown that constraint languages that admit the MJN multimorphism are tractable. Moreover, using a minimisation algorithm for submodular functions, Cohen et al. (TCS'08) have shown that constraint languages that admit an STP (symmetric tournament pair) multimorphism are tractable. We generalise these results by showing that languages admitting the MJN multimorphism on a subdomain and an STP multimorphisms on the complement of the subdomain are tractable. The algorithm is a reduction to the algorithm for languages admitting an STP multimorphism.
MIMO Precoding Using Rotating Codebooks
Venue: arXiv cs.IT 2010
Year: 2010

Next generation wireless communications rely on multiple input multiple output (MIMO) techniques to achieve high data rates. Feedback of channel information can be used in MIMO precoding to fully activate the strongest channel modes and improve MIMO performance. Unfortunately, the bandwidth of the control channel via which the feedback is conveyed is severely limited. An important issue is how to improve the MIMO precoding performance with minimal feedback. In this letter, we present a method that uses a rotating codebook technique to effectively improve the precoding performance without the need of increasing feedback overhead. The basic idea of the rotating codebook precoding is to expend the effective precoding codebook size via rotating multiple codebooks so that the number of feedback bits remains unchanged. Simulation results are presented to show the performance gain of the proposed rotating codebook precoding over the conventional precoding.