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distributed Secret Dissemination Across a Network

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2015年第7期9卷 1206-1216页

作者： Shah, Nihar B. Rashmi, K. V. Ramchandran, Kannan Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

Shamir's (n, k) threshold secret sharing is an important component of several cryptographic protocols, such as those for secure multiparty-computation and key management. These protocols typically assume the presence of direct communication links from the dealer to all participants, in which case the dealer can directly pass the shares of the secret to each participant. In this paper, we consider the problem of secret sharing when the dealer does not have direct communication links to all the participants, and instead, the dealer and the participants form a general network. Existing methods are based on separate secure message transmissions from the dealer to each participant, requiring considerable coordination and communication in the network. We present a distributed algorithm for disseminating shares over a network, which we call the "SNEAK" algorithm, requiring each node to know only the identities of its one-hop neighbors. While SNEAK imposes a stronger condition on the network by requiring the dealer to be what we call k- propagating rather than k-connected as required by the existing solutions, we show that in addition to being distributed, it achieves significant reduction in the amount of communication and the randomness required. We also derive information-theoretic lower bounds on the amount of communication for secret sharing over networks, which may be of independent interest.

关键词： Secret sharing distributed algorithm networks

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distributed Kalman Filtering With Quantized Sensing State

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2015年第19期63卷 5180-5193页

作者： Li, Di Kar, Soummya Alsaadi, Fuad E. Dobaie, Abdullah M. Cui, Shuguang Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA King Abdulaziz Univ Dept Elect & Comp Engn Jeddah 22254 Saudi Arabia King Abdulaziz Univ Jeddah 22254 Saudi Arabia Chinese Univ Hong Kong Shenzhen Peoples R China

This paper studies a Quantized Gossip-based Interactive Kalman Filtering (QGIKF) algorithm implemented in a wireless sensor network, where the sensors exchange their quantized states with neighbors via inter-sensor communications. We show that, in the countable infinite quantization alphabet case, the network can still achieve weak consensus with the information loss due to quantization, i.e., the estimation error variance sequence at a randomly selected sensor can converge weakly (in distribution) to a unique invariant measure. To prove the weak convergence, we first interpret error variance sequences as interacting particles, then model each sequence evolution as a Random Dynamical System (RDS), and further prove its stochastically bounded nature. Moreover, based on the analysis for the countable infinite quantization alphabet case, we also prove that under certain conditions the network can also achieve weak consensus, when the quantization alphabet is finite, which is more restricted and practical.

关键词： distributed algorithm Kalman filter quantization consensus convergence wireless sensor network

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distributed Self Localization for Relative Position Sensing Networks in 2D Space

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2015年第14期63卷 3751-3761页

作者： Lin, Zhiyun Fu, Minyue Diao, Yingfei Zhejiang Univ Coll Elect Engn State Key Lab Ind Control Technol Hangzhou 310007 Zhejiang Peoples R China Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia Zhejiang Univ Dept Control Sci & Engn Hangzhou 310007 Zhejiang Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310007 Zhejiang Peoples R China Huawei Technol Co Ltd Huawei Shanghai R&D Ctr Shanghai 201206 Peoples R China

This paper studies the 2D localization problem of a sensor network given anchor node positions in a common global coordinate frame and relative position measurements in local coordinate frames between node pairs. It is assumed that the local coordinate frames of different sensors have different orientations and the orientation difference with respect to the global coordinate frame are not known. In terms of graph connectivity, a necessary and sufficient condition is obtained for self-localizability that leads to a fully distributed localization algorithm. Moreover, a distributed verification algorithm is developed to check the graph connectivity condition, which can terminate successfully when the sensor network is self-localizable. Finally, a fully distributed, linear, and iterative algorithm based on the complex-valued Laplacian associated with the sensor network is proposed, which converges globally and gives the correct localization result.

关键词： Sensor networks self localization localizability distributed algorithm

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distributed Mutual Exclusion algorithms for Intersection Traffic Control

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IEEE TRANSACTIONS ON PARALLEL AND distributed SYSTEMS 2015年第1期26卷 65-74页

作者： Wu, Weigang Zhang, Jiebin Luo, Aoxue Cao, Jiannong Sun Yat Sen Univ Dept Comp Sci Guangzhou 510006 Guangdong Peoples R China SYSU CMU Shunde Int Joint Res Inst Shunde Peoples R China Sun Yat Sen Univ Sch Software Guangzhou 510006 Guangdong Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China

Traffic control at intersections is a key issue and hot research topic in intelligent transportation systems. Existing approaches, including traffic light scheduling and trajectory maneuver, are either inaccurate and inflexible or complicated and costly. More importantly, due to the dynamics of traffic, it is really difficult to obtain the optimal solution in a real-time way. Inspired by the emergence of vehicular ad hoc network, we propose a novel approach to traffic control at intersections. Via vehicle to vehicle or vehicle to infrastructure communications, vehicles can compete for the privilege of passing the intersection, i.e., traffic is controlled via coordination among vehicles. Such an approach is flexible and efficient. To realize the coordination among vehicles, we first model the problem as a new variant of the classic mutual exclusion problem, and then design algorithms to solve new problem. Both centralized and distributed algorithms are. We conduct extensive simulations to evaluate the performance of our proposed algorithms. The results show that, our approach is efficient and outperforms a reference algorithm based on optimal traffic light scheduling. Moreover, our approach does not rely on traffic light or intersection controller facilities, which makes it flexible and applicable to various kinds of intersections.

关键词： Mutual exclusion intersection traffic control intelligent transportation system vehicular ad hoc network distributed algorithm

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Gradient-free method for nonsmooth distributed optimization

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JOURNAL OF GLOBAL OPTIMIZATION 2015年第2期61卷 325-340页

作者： Li, Jueyou Wu, Changzhi Wu, Zhiyou Long, Qiang Chongqing Normal Univ Sch Math Chongqing 400047 Peoples R China Federat Univ Australia Sch Sci Informat Technol & Engn Ballarat Vic 3353 Australia Curtin Univ Sch Built Environm Bentley WA 6102 Australia Southwest Univ Sci & Technol Sch Sci Mianyang 621010 Sichuan Peoples R China

In this paper, we consider a distributed nonsmooth optimization problem over a computational multi-agent network. We first extend the (centralized) Nesterov's random gradient-free algorithm and Gaussian smoothing technique to the distributed case. Then, the convergence of the algorithm is proved. Furthermore, an explicit convergence rate is given in terms of the network size and topology. Our proposed method is free of gradient, which may be preferred by practical engineers. Since only the cost function value is required, our method may suffer a factor up to (the dimension of the agent) in convergence rate over that of the distributed subgradient-based methods in theory. However, our numerical simulations show that for some nonsmooth problems, our method can even achieve better performance than that of subgradient-based methods, which may be caused by the slow convergence in the presence of subgradient.

关键词： distributed algorithm Gaussian smoothing Gradient-free method Convex optimization

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FINITE-TIME CLUSTER CONSENSUS FOR NETWORKS VIA distributed ITERATIONS

FINITE-TIME CLUSTER CONSENSUS FOR NETWORKS VIA DISTRIBUTED I...

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第十届动力学与控制学术会议

作者： SHANG Yilun Department of Mathematics Tongji University

This paper studies the finite-time cluster average consensus in bidirectional networks. By designing distributed linear iterations involving stochastic matrices consistent with a network topology, we show that cluster average consensus can always be achieved in finite time for bidirectional networks containing cluster-spanning trees. In particular, for a network with n nodes, the cluster average consensus can be achieved in less than n(n-1)/2 steps regardless of the number of different clusters. We develop a detailed algorithm to implement the proposed finite-time cluster average consensus. Numerical simulations on a realistic social network are presented to illustrate the availability of the obtained theoretical results. Moreover, we compare the current approach with the past asymptotical consensus protocols, including those involving external intra-cluster identical inputs. The advantage of finite-time consensus is prominent.

关键词： complex networks cluster consensus multi-agent systems distributed algorithm finite-time

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distributed and scalable embedding of virtual networks

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2015年 56卷 124-136页

作者： Beck, Michael Till Fischer, Andreas Felipe Botero, Juan Linnhoff-Popien, Claudia de Meer, Hermann Univ Munich D-81377 Munich Germany Univ Passau Passau Germany Univ Antioquia Antioquia Colombia

Network virtualization is widely regarded as a key technology for the Future Internet, enabling the deployment of new network protocols without changing dissimilar hardware devices. This leads to the problem of mapping virtual demands to physical resources, known as Virtual Network Embedding (VNE). Current VNE algorithms do not scale with respect to the substrate network size. Therefore, these algorithms are not applicable in large-scale scenarios where virtual networks have to be embedded in a timely manner. This paper discusses DPVNE, a distributed and Generic VNE framework: It runs cost-oriented centralized embedding algorithms in a distributed way, spreading workload across the substrate network instead of concentrating it on one single node (as centralized algorithms do). Several state-of-the-art algorithms were evaluated running inside the DPVNE framework. Results show that DPVNE leads to runtime improvements in large-scale scenarios and embedding results are kept comparable. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Virtual Network Embedding distributed algorithm Framework

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Fast distributed Page Rank computation

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THEORETICAL COMPUTER SCIENCE 2015年第PB期561卷 113-121页

作者： Das Sarma, Atish Molla, Anisur Rahaman Pandurangan, Gopal Upfal, Eli eBay Inc eBay Res Labs San Jose CA USA Nanyang Technol Univ Div Math Sci Singapore 637371 Singapore Brown Univ Dept Comp Sci Providence RI 02912 USA

Over the last decade, PageRank has gained importance in a wide range of applications and domains, ever since it first proved to be effective in determining node importance in large graphs (and was a pioneering idea behind Google's search engine). In distributed computing alone, PageRank vector, or more generally random walk based quantities have been used for several different applications ranging from determining important nodes, load balancing, search, and identifying connectivity structures. Surprisingly, however, there has been little work towards designing provably efficient fully-distributed algorithms for computing PageRank. The difficulty is that traditional matrix-vector multiplication style iterative methods may not always adapt well to the distributed setting owing to communication bandwidth restrictions and convergence rates. In this paper, we present fast random walk-based distributed algorithms for computing PageRanks in general graphs and prove strong bounds on the round complexity. We first present a distributed algorithm that takes O (log n/epsilon) rounds with high probability on any graph (directed or undirected), where n is the network size and E is the reset probability used in the PageRank computation (typically epsilon is a fixed constant). We then present a faster algorithm that takes O (root log n/epsilon) rounds in undirected graphs. Both of the above algorithms are scalable, as each node sends only small (polylog n) number of bits over each edge per round. To the best of our knowledge, these are the first fully distributed algorithms for computing PageRank vector with provably efficient running time. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Page Rank distributed algorithm Random walk Monte Carlo method

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distributed Channel Probing for Efficient Transmission Scheduling in Wireless Networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2015年第6期14卷 1176-1188页

作者： Li, Bin Eryilmaz, Atilla Univ Illinois Dept Elect & Comp Engn Champaign IL 61801 USA Univ Illinois Coordinated Sci Lab Champaign IL 61801 USA Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

It is energy-consuming and operationally cumbersome for all users to continuously estimate the channel quality before each transmission decision in opportunistic scheduling over wireless fading channels. This observation motivates us to understand whether and how opportunistic gains can still be achieved with significant reductions in channel probing requirements and without centralized coordination amongst the competing users. To that end, we first study a simple scenario that motivates us to consider the general setup and develop probing and transmission schemes that are amenable to distributed implementation. After characterizing the maximum achievable throughput region under the probing constraints, we provide an optimal probing algorithm. Noting the difficulties in the implementation of the centralized solution, we develop a novel Sequential Greedy Probing (SGP) algorithm, which is naturally well-suited for physical implementation and distributed operation. We show that the SGP algorithm is optimal in the important scenario of symmetric and independent ON-OFF fading channels. Then, we study a variant of the SGP algorithm in general fading channels to obtain its efficiency ratio as an explicit function of the channel statistics and rates, and note its tightness in the symmetric and independent ON-OFF fading scenario. We further discuss the distributed implementation of these greedy solutions by using the Fast-CSMA technique.

关键词： Opportunistic scheduling channel probing stochastic control distributed algorithm network stability

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distributed computation in dynamic networks via random walks

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THEORETICAL COMPUTER SCIENCE 2015年 581卷 45-66页

作者： Das Sarma, Atish Molla, Anisur Rahaman Pandurangan, Gopal eBay Inc eBay Res Labs San Jose CA USA Nanyang Technol Univ Div Math Sci Singapore 637371 Singapore Univ Houston Dept Comp Sci Houston TX 77204 USA

The paper investigates efficient distributed computation in dynamic networks in which the network topology changes (arbitrarily) from round to round. Random walks are a fundamental primitive in a wide variety of network applications;the local and lightweight nature of random walks is especially useful for providing uniform and efficient solutions to distributed control of dynamic networks. Given their applicability in dynamic networks, we focus on developing fast distributed algorithms for performing random walks in such networks. Our first contribution is a rigorous framework for the design and analysis of distributed random walk algorithms in dynamic networks. We then develop a fast distributed random-walk based algorithm that runs in (O) over tilde(root tau Phi) rounds(2) (with high probability), where tau is the dynamic mixing time and Phi is the dynamic diameter of the network, respectively, and returns a sample close to a suitably defined stationary distribution of the dynamic network. Our next contribution is a fast distributed algorithm for the fundamental problem of information dissemination (also called as gossip) in a dynamic network. In gossip, or more generally, k-gossip, there are k pieces of information (or tokens) that are initially present in some nodes and the problem is to disseminate the k tokens to all nodes. We present a random-walk based algorithm that runs in (O) over tilde (min{n(1/3)k(2/3)(tau Phi)(1/3),k Phi}) rounds (with high probability). This is the first o(k Phi))-time fully-distributed token forwarding algorithm (on certain graph families) that improves over the previous-best O(k Phi) round distributed algorithm (Kuhn et al. [24]), although in an oblivious adversary model. The random walk framework developed in this paper has also subsequently proved useful in developing efficient storage and search algorithms as well as developing fast byzantine agreement algorithms in dynamic networks. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Dynamic network distributed algorithm Random walks Random sampling Information dissemination Gossip

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