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distributed and scalable embedding of virtual networks

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PartB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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distributed Online Optimal Energy Management for Smart Grids

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2015年第3期11卷 717-727页

作者： Zhang, Wei Xu, Yinliang Liu, Wenxin Zang, Chuanzhi Yu, Haibin Harbin Inst Technol Dept Elect Engn Harbin 150001 Peoples R China Sun Yat Sen Univ Sun Yat Sen Univ Carnegie Mellon Univ Joint Inst Guangzhou 510275 Guangdong Peoples R China Lehigh Univ Dept Elect & Comp Engn Bethlehem PA 18015 USA Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Peoples R China

Traditionally, economic dispatch and demand response (DR) are considered separately, or implemented sequentially, which may degrade the energy efficiency of the power grids. One important goal of optimal energy management (OEM) is to maximize the social welfare through the coordination of the suppliers' generations and customers' demands. Thus, it is desirable to consider the interactive operation of economic dispatch and DR, and solve them in an integrated way. This paper proposes a fully distributed online OEM solution for smart grids. The proposed solution considers the economic dispatch of conventional generators, DR of users, and operating conditions of renewable generators all together. The proposed distributed solution is developed based on a market-based self-interests motivation model since this model can realize the global social welfare maximization among system participants. The proposed solution can be implemented with multiagent system with each system participant assigned with an energy management agent. Based on the designed distributed algorithms for price updating and supply-demand mismatch discovery, the OEM among agents can be achieved in a distributed way. Simulation results demonstrate the effectiveness of the proposed solution.

关键词： distributed algorithm multiagent system (MAS) optimal energy management (OEM) smart grids

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Geometric Programming Based distributed Resource Allocation in Ultra Dense Hetnets

Geometric Programming Based Distributed Resource Allocation ...

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IEEE Vehicular Technology Conference

作者： Haiyan Liu Shaoyi Xu Kyung Sup Kwak School of Electronics and Information Engineering Beijing Jiaotong University UWB-ITRC Inha University

ISBN: (纸本)9781509016990

In this paper a novel Geometric Programming based distributed approach is proposed which enables small cell users to optimize their downlink performance by exploiting distributed joint allocation of transmission power and subchannels. The problem is formulated to maximize the system sum capacity, specifically, the time delay is taken into as a constraint to guarantee the quality of service. Consequently, the original problem is modeled as a non-convex NP-hard problem. To solve this problem, Geometric Programming is used to convert the original optimization problem into a convex one, which is further solved to obtain the global optimal solution. What's more, Simulation results show that the proposed approach yields significant performance gains.

关键词： Ultra Dense Hetnets Resource Allocation distributed algorithm Geometric Programming GEOMETRIC PROGRAMMING Resource utilization distributed algorithms power transmission management of resources

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distributed Identification of the Most Critical Node for Average Consensus

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2015年第16期63卷 4315-4328页

作者： Liu, Hao Cao, Xianghui He, Jianping Cheng, Peng Li, Chunguang Chen, Jiming Sun, Youxian Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Innovat Joint Res Ctr Ind Cyber Phys Syst Hangzhou 310027 Zhejiang Peoples R China Southeast Univ Sch Automat Nanjing 210096 Jiangsu Peoples R China Zhejiang Univ Dept Informat Sci & Elect Engn Hangzhou 310027 Zhejiang Peoples R China

In communication networks, cyber attacks, such as resource depleting attacks, can cause failure of nodes and can damage or significantly slow down the convergence of the average consensus algorithm. In particular, if the network topology information is learned, an intelligent adversary can attack the most critical node in the sense that deactivating it causes the largest destruction, among all the network nodes, to the convergence speed of the average consensus algorithm. Although a centralized method can undoubtedly identify such a critical node, it requires global information and is computationally intensive and, hence, is not scalable. In this paper, we aim to identify the most critical node in a distributed manner. The network algebraic connectivity is used to assess the destruction caused by node removal and further the importance of a node. We propose three low-complexity algorithms to estimate the descent of the algebraic connectivity due to node removal and theoretically analyze the corresponding estimation errors. Based on these estimation algorithms, distributed power iteration, and maximum-consensus, we propose a fully distributed algorithm for the nodes to iteratively find the most critical one. Extensive simulation results demonstrate the effectiveness of the proposed methods.

关键词： Consensus critical node identification algebraic connectivity Fiedler vector distributed algorithm

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Target coverage through distributed clustering in directional sensor networks

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2015年第1期000卷 1-18页

作者： Islam, Md. Mofijul Ahasanuzzaman, Md. Razzaque, Md. Abdur Hassan, Mohammad Mehedi Alelaiwi, Abdulhameed Xiang, Yang Univ Dhaka Dept Comp Sci & Engn Green Networking Res Grp Dhaka 1000 Bangladesh King Saud Univ Coll Comp & Informat Sci Informat Syst Dept Riyadh 11543 Saudi Arabia Deakin Univ Sch Informat Technol Burwood Vic 3125 Australia

Maximum target coverage with minimum number of sensor nodes, known as an MCMS problem, is an important problem in directional sensor networks (DSNs). For guaranteed coverage and event reporting, the underlying mechanism must ensure that all targets are covered by the sensors and the resulting network is connected. Existing solutions allow individual sensor nodes to determine the sensing direction for maximum target coverage which produces sensing coverage redundancy and much overhead. Gathering nodes into clusters might provide a better solution to this problem. In this paper, we have designed distributed clustering and target coverage algorithms to address the problem in an energy-efficient way. To the best of our knowledge, this is the first work that exploits cluster heads to determine the active sensing nodes and their directions for solving target coverage problems in DSNs. Our extensive simulation study shows that our system outperforms a number of state-of-the-art approaches.

关键词： Directional sensor networks Target coverage distributed algorithm Network lifetime Cluster

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Efficient distributed computation of distance sketches in networks

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distributed COMPUTING 2015年第5期28卷 309-320页

作者： Das Sarma, Atish Dinitz, Michael Pandurangan, Gopal eBay Res Labs San Jose CA USA Johns Hopkins Univ Baltimore MD USA Univ Houston Dept Comp Sci Houston TX 77204 USA

Distance computation (e.g., computing shortest paths) is one of the most fundamental primitives used in communication networks. The cost of effectively and accurately computing pairwise network distances can become prohibitive in large-scale networks such as the Internet and Peer-to-Peer (P2P) networks. The idea behind distance sketches is to preprocess the graph and store a small amount of information (called as sketch or distance label) such that whenever a query for any pairwise distance is issued, the distance can be well approximated (i.e., with small stretch) very quickly in an online fashion. Specifically, the pre-processing (usually) involves storing this sketch with each node, such that at query time only the sketches of the concerned nodes need to be looked up to compute the approximate distance. In this paper, we present the first theoretical study of distance sketches derived from distance oracles in a distributed network. We first present a fast distributed algorithm for computing approximate distance sketches, based on a distributed implementation of the distance oracle scheme of (Thorup and Zwick, J ACM 52(1):1-24, 2005). We also show how to modify this basic construction to achieve different tradeoffs between the number of pairs for which the distance estimate is accurate, the size of the sketches, and the time and message complexity necessary to compute them. These tradeoffs can then be combined to give an efficient construction of small sketches with provable average-case as well as worst-case performance. Our algorithms use only small-sized messages and hence are suitable for bandwidth-constrained networks, and can be used in various networking applications such as topology discovery and construction, token management, load balancing, monitoring overlays, and several other problems in distributed algorithms.

关键词： distributed network Shortest paths Distance labeling distributed algorithm

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Fully distributed multi-area economic dispatch method for active distribution networks

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第12期9卷 1341-1351页

作者： Zheng, Weiye Wu, Wenchuan Zhang, Boming Li, Zhigang Liu, Yibing Tsinghua Univ Dept Elect Engn Beijing Peoples R China

distributed generators can be integrated in geographically distributed areas and microgrids of active distribution networks (ADNs), and can operate independently. On the basis of the alternating direction method of multipliers, the authors describe an efficient fully distributed algorithm to solve multi-area economic dispatch problems in ADNs without requiring a central coordinator. The physical interpretation of the distributed algorithm and a proof for its convergence are both given. Network losses are taken into account by exploiting the features of ADNs. Two other popular distributed algorithms, including Lagrangian relaxation and auxiliary problem principle, are also implemented and compared with numerical tests. They discuss numerical results that demonstrate the effectiveness and efficiency of the algorithm.

关键词： power distribution economics load dispatching distributed power generation relaxation theory fully distributed multiarea economic dispatch method active distribution network distributed generator microgrid ADN distributed algorithm network loss Lagrangian relaxation auxiliary problem principle numerical testing

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