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Faulttolerant and 3Dimensional Distributed Topology Control Algorithms in Wireless Multihop Networks
 in Proceedings of the 11th IEEE International Conference on Computer Communications and Networks (ICCCN
, 2002
"... We can control the topology of a multihop wireless network by varying the transmission power at each node. The lifetime of such networks depends on battery power at each node. This paper presents a distributed faulttolerant topology control algorithm for minimum energy consumption in these net ..."
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Cited by 63 (10 self)
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We can control the topology of a multihop wireless network by varying the transmission power at each node. The lifetime of such networks depends on battery power at each node. This paper presents a distributed faulttolerant topology control algorithm for minimum energy consumption in these networks. More precisely, we present algorithms which preserve the connectivity of a network upon failing of, at most, k nodes (k is constant) and simultaneously minimize the transmission power at each node to some extent. In addition, we present simulations to support the effectiveness of our algorithm. We also demonstrate some optimizations to further minimize the power at each node. Finally, we show how our algorithms can be extended to 3dimensions.
Resisting Structural Reidentification in Anonymized Social Networks
, 2008
"... We identify privacy risks associated with releasing network data sets and provide an algorithm that mitigates those risks. A network consists of entities connected by links representing relations such as friendship, communication, or shared activity. Maintaining privacy when publishing networked dat ..."
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Cited by 60 (7 self)
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We identify privacy risks associated with releasing network data sets and provide an algorithm that mitigates those risks. A network consists of entities connected by links representing relations such as friendship, communication, or shared activity. Maintaining privacy when publishing networked data is uniquely challenging because an individual’s network context can be used to identify them even if other identifying information is removed. In this paper, we quantify the privacy risks associated with three classes of attacks on the privacy of individuals in networks, based on the knowledge used by the adversary. We show that the risks of these attacks vary greatly based on network structure and size. We propose a novel approach to anonymizing network data that models aggregate network structure and then allows samples to be drawn from that model. The approach guarantees anonymity for network entities while preserving the ability to estimate a wide variety of network measures with relatively little bias.
TOEPLITZSTRUCTURED COMPRESSED SENSING MATRICES
"... The problem of recovering a sparse signal x ∈ R n from a relatively small number of its observations of the form y = Ax ∈ R k, where A is a known matrix and k ≪ n, has recently received a lot of attention under the rubric of compressed sensing (CS) and has applications in many areas of signal proces ..."
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Cited by 58 (5 self)
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The problem of recovering a sparse signal x ∈ R n from a relatively small number of its observations of the form y = Ax ∈ R k, where A is a known matrix and k ≪ n, has recently received a lot of attention under the rubric of compressed sensing (CS) and has applications in many areas of signal processing such as data compression, image processing, dimensionality reduction, etc. Recent work has established that if A is a random matrix with entries drawn independently from certain probability distributions then exact recovery of x from these observations can be guaranteed with high probability. In this paper, we show that Toeplitzstructured matrices with entries drawn independently from the same distributions are also sufficient to recover x from y with high probability, and we compare the performance of such matrices with that of fully independent and identically distributed ones. The use of Toeplitz matrices in CS applications has several potential advantages: (i) they require the generation of only O(n) independent random variables; (ii) multiplication with Toeplitz matrices can be efficiently implemented using fast Fourier transform, resulting in faster acquisition and reconstruction algorithms; and (iii) Toeplitzstructured matrices arise naturally in certain application areas such as system identification. Index Terms — Compressed sensing, restricted isometry property, system identification, Toeplitz matrices, underdetermined systems of linear equations 1.1. Background 1.
Clock Distribution Networks in Synchronous Digital Integrated Circuits
 Proc. IEEE
, 2001
"... this paper, bears separate focus. The paper is organized as follows. In Section II, an overview of the operation of a synchronous system is provided. In Section III, fundamental definitions and the timing characteristics of clock skew are discussed. The timing relationships between a local data path ..."
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Cited by 57 (5 self)
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this paper, bears separate focus. The paper is organized as follows. In Section II, an overview of the operation of a synchronous system is provided. In Section III, fundamental definitions and the timing characteristics of clock skew are discussed. The timing relationships between a local data path and the clock skew of that path are described in Section IV. The interplay among the aforementioned three subsystems making up a synchronous digital system is described in Section V; particularly, how the timing characteristics of the memory and logic elements constrain the design and synthesis of clock distribution networks. Different forms of clock distribution networks, such as buffered trees and Htrees, are discussed. The automated layout and synthesis of clock distribution networks are described in Section VI. Techniques for making clock distribution networks less sensitive to process parameter variations are discussed in Section VII. Localized scheduling of the clock delays is useful in optimizing the performance of highspeed synchronous circuits. The process for determining the optimal timing characteristics of a clock distribution network is reviewed in Section VIII. The application of clock distribution networks to highspeed circuits has existed for many years. The design of the clock distribution network of certain important VLSIbased systems has been described in the literature, and some examples of these circuits are described in Section IX. In an effort to provide some insight into future and evolving areas of research relevant to highperformance clock distribution networks, some potentially important topics for future research are discussed in Section X. Finally, a summary of this paper with some concluding remarks is provided in Section XI
A NonIterative Greedy Algorithm for Multiframe Point Correspondence
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2003
"... This paper presents a framework for finding point correspondences in monocular image sequences over multiple frames. The general problem of multiframe point correspondence is NP Hard for three or more frames. A polynomial time algorithm for a restriction of this problem is presented and is used a ..."
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Cited by 55 (7 self)
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This paper presents a framework for finding point correspondences in monocular image sequences over multiple frames. The general problem of multiframe point correspondence is NP Hard for three or more frames. A polynomial time algorithm for a restriction of this problem is presented and is used as the basis of the proposed greedy algorithm for the general problem. The greedy nature of the proposed algorithm allows it to be used in real time systems for tracking and surveillance etc. In addition, the proposed algorithm deals with the problems of occlusion, missed detections and false positives by using a single noniterative greedy optimization scheme, and hence reduces the complexity of the overall algorithm as compared to most existing approaches where multiple heuristics are used for the same purpose. While most greedy algorithms for point tracking do not allow for entry and exit of the points from the scene, this is not a limitation for the proposed algorithm. Experiments with real and synthetic data over a wide range of scenarios and system parameters are presented to validate the claims about the performance of the proposed algorithm.
On the Maximum Stable Throughput Problem in Random Networks with Directional Antennas
 IN PROC. ACM MOBIHOC
, 2003
"... We consider the problem of determining rates of growth for the maximum stable throughput achievable in dense wireless networks. We formulate this problem as one of finding maximum flows on random unitdisk graphs. Equipped with the maxflow/mincut theorem as our basic analysis tool, we obtain rates ..."
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Cited by 51 (8 self)
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We consider the problem of determining rates of growth for the maximum stable throughput achievable in dense wireless networks. We formulate this problem as one of finding maximum flows on random unitdisk graphs. Equipped with the maxflow/mincut theorem as our basic analysis tool, we obtain rates of growth under three models of communication: (a) omnidirectional transmissions; (b) "simple" directional transmissions, in which sending nodes generate a single beam aimed at a particular receiver; and (c) "complex " directional transmissions, in which sending nodes generate multiple beams aimed at multiple receivers. Our main finding is that an increase of 54 54 in maximum stable throughput is all that can be achieved by allowing arbitrarily complex signal processing (in the form of generation of directed beams) at the transmitters and receivers. We conclude therefore that neither directional antennas, nor the ability to communicate simultaneously with multiple nodes, can be expected in practice to effectively circumvent the constriction on capacity in dense networks that results from the geometric layout of nodes in space.
New outer bounds on the marginal polytope
 In Advances in Neural Information Processing Systems
, 2007
"... We give a new class of outer bounds on the marginal polytope, and propose a cuttingplane algorithm for efficiently optimizing over these constraints. When combined with a concave upper bound on the entropy, this gives a new variational inference algorithm for probabilistic inference in discrete Mar ..."
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Cited by 46 (4 self)
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We give a new class of outer bounds on the marginal polytope, and propose a cuttingplane algorithm for efficiently optimizing over these constraints. When combined with a concave upper bound on the entropy, this gives a new variational inference algorithm for probabilistic inference in discrete Markov Random Fields (MRFs). Valid constraints on the marginal polytope are derived through a series of projections onto the cut polytope. As a result, we obtain tighter upper bounds on the logpartition function. We also show empirically that the approximations of the marginals are significantly more accurate when using the tighter outer bounds. Finally, we demonstrate the advantage of the new constraints for finding the MAP assignment in protein structure prediction. 1
Combinatorial Optimization: Packing and Covering
, 2000
"... The integer programming models known as set packing and set covering have a wide range of applications, such as pattern recognition, plant location and airline crew scheduling. Sometimes, due to the special structure of the constraint matrix, the natural linear programming relaxation yields an optim ..."
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Cited by 40 (1 self)
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The integer programming models known as set packing and set covering have a wide range of applications, such as pattern recognition, plant location and airline crew scheduling. Sometimes, due to the special structure of the constraint matrix, the natural linear programming relaxation yields an optimal solution that is integer, thus solving the problem. Sometimes, both the linear programming relaxation and its dual have integer optimal solutions. Under which conditions do such integrality properties hold? This question is of both theoretical and practical interest. Minmax theorems, polyhedral combinatorics and graph theory all come together in this rich area of discrete mathematics. In addition to minmax and polyhedral results, some of the deepest results in this area come in two flavors: “excluded minor” results and “decomposition ” results. In these notes, we present several of these beautiful results. Three chapters cover minmax and polyhedral results. The next four cover excluded minor results. In the last three, we
Edge Disjoint Paths Revisited
 In Proceedings of the 14th ACMSIAM Symposium on Discrete Algorithms
, 2003
"... The approximability of the maximum edge disjoint paths problem (EDP) in directed graphs was seemingly settled by the )hardness result of Guruswami et al. [10] and the O( m) approximation achievable via both the natural LP relaxation [19] and the greedy algorithm [11, 12]. Here m is the numb ..."
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Cited by 39 (5 self)
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The approximability of the maximum edge disjoint paths problem (EDP) in directed graphs was seemingly settled by the )hardness result of Guruswami et al. [10] and the O( m) approximation achievable via both the natural LP relaxation [19] and the greedy algorithm [11, 12]. Here m is the number of edges in the graph. However, we observe that the hardness of approximation shown in [10] applies to sparse graphs and hence when expressed as a function of n, the number of vertices, only an \Omega\Gamma n )hardness follows. On the other hand, the O( m)approximation algorithms do not guarantee a sublinear (in terms of n) approximation algorithm for dense graphs. We note that a similar gap exists in the known results on the integrality gap of the natural LP relaxation: an \Omega\Gamma n) lower bound and an O( m) upper bound. Motivated by this discrepancy in the upper and lower bounds we study algorithms for the EDP in directed and undirected graphs obtaining improved approximation ratios. We show that the greedy algorithm has an approximation ratio of O(min(n m)) in undirected graphs and a ratio of O(min(n m)) in directed graphs. For ayclic graphs we give an O( n log n) approximation via LP rounding. These are the first sublinear approximation ratios for EDP. Our results also extend to EDP with weights and to the unsplittable flow problem with uniform edge capacities.