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9th International Conference on Frontier of Computer Science and Technology

作者： Mao, Yingchi Xu, Ziyang Ping, Ping Wang, Longbao Hohai Univ Coll Comp & Informat Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467392952

Clustering algorithm is applied to many fields, especially in the data mining. Due to the increasing number of the data, it's too hard for the clustering algorithm to afford the computation time in traditional computing model. When handling with big data, the corresponding algorithms of data mining have been transformed from the original single-core or single ported into the parallel and distributed processing. Parallel processing becomes the most popular way to improve the execution performance. This paper established a Hadoop distributed cluster based on the CloudStack and implemented the optimal distributed K-Means clustering algorithm based on MapReduce. The proposed optimal distributed K-Means clustering can obtain good quality of the clustering results and the efficiency of the execution time. The experiment results show that the optimal distributed K-Means cluster algorithm can have better performance for dealing with large-scale data set.

关键词： K-Means Clustering distributed algorithm CloudStack optimal distributed K-Means

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A Novel distributed Nonlinear MPC algorithm of Signaling Split in Urban Traffic System 34

A Novel Distributed Nonlinear MPC Algorithm of Signaling Spl...

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34th Chinese Control Conference (CCC)

作者： Zhou, Xuanhao Pan, Zaisheng Chen, Peng Liang, Shiwu Lu, Yongzai Zhejiang SUPCON Res CO LTD 309 Liuhe Rd Hangzhou 310053 Zhejiang Peoples R China Zhejiang Univ Inst Cyber Syst & Control Natl Lab Ind & Technol Yuquan Campus Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9789881563897

Based on the linear dynamic model (LDN) on urban traffic system proposed by Lucas Barcelos et al. in 2010, the MPC method has been successfully used in the signal splitting control area. In this paper, we extend the model to a nonlinear form employing the idea from S Lin et al. which is close to the real world, and the Gradient-based distributed dynamic optimization method (GBDDO) is introduced to distributively solving the large-scale problem. The simulation results show that our method can derive an approving solution.

关键词： Traffic network Model Predictive Control distributed algorithm Nonlinear GBDDO

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A Stable and distributed Community Detection algorithm Based on Maximal Cliques

A Stable and Distributed Community Detection Algorithm Based...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Gui, Feng Ma, Yunlong Zhang, Feng Liu, Min Yin, Rong Shen, Weiming Tongji Univ Sch Elect & Informat Engn Shanghai 200092 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Shanghai 200092 Peoples R China

ISBN: (纸本)9781479986965

In the research area of community detection which aims at detecting some highly cohesive vertex subsets in social network, there mainly exist some problems, such as the algorithms with comparatively excellent quality of the final partitioning usually have high time complexity and some other fast algorithms often result in low quality of partitioning or other disadvantages. Nowadays, the increasing demands for community detection in large-scale social networks necessitate the use of distributed and scalable methods to detect communities in an effective and efficient manner. Label propagation algorithm (LPA), whose time complexity is O(m) on a network with m edges, is a near linear time algorithm to detect community effectively. Besides, owing to having good scalability, the parallel version of LPA (DLPA) is suitable for community detection in large-scale social networks. However, DLPA synchronously updates the vertices labels, which usually brings about label oscillations and results in low quality of partitioning. In this paper, we analyze the drawbacks of DLPA and propose a novel method C-DLPA, which combines DLPA with the notion of maximal cliques and at the same time utilizes a new updating mechanism that updating each node' label by probability of its adjacent nodes, to make final partitioning become more accurate and to avoid oscillations effectively. The experimental results show that C-DLPA has better performance is not only low time cost by as much to avoid oscillations but its community detection accuracy compared with DLPA.

关键词： community detection label propagation algorithm maximal cliques synchronous distributed algorithm

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Modeling Dynamic Adaptive Streaming Over Information-Centric Networking

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IEEE ACCESS 2016年 4卷 8362-8374页

作者： Jia, Riheng Liu, Zhe Wang, Xiong Gan, Xiaoying Wang, Xinbing Xu, Jun (Jim) Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Georgia Inst Technol Coll Comp Atlanta GA 30332 USA

The dynamic adaptive streaming technique flexibly adapts the video bit-rate to link fluctuations, which can improve the quality of experience (QoE). In this paper, we present a systematic framework of video streaming in the context of information-centric networking, in order to facilitate the largescale deployment of the dynamic adaptive streaming technique. Specifically, we design the network as a two-layer coordinating structure, namely, the control layer and the transmission layer. The control layer employs the statistical data recorders to record the variations of the video popularity, link states, and user demands. On the other side, the network forwards user requests and caches data packets in the transmission layer, based on the statistical data which is obtained in the control layer. In addition, the network executes the real-time monitoring of link conditions in the transmission layer, and adjusts the video bit-rate accordingly. Under the above feedback circumstance, we first develop a distributed algorithm of joint dynamic forwarding and caching to theoretically maximize the total user demand rates within the network stability region. Then, we modify the distributed algorithm with a practical caching strategy to make the system applicable to real scenarios. Simulation results show the superior performance of the modified distributed algorithm in terms of low user delay and high QoE performance.

关键词： Information-centric networking (ICN) video streaming distributed algorithm

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A game-theoretic approach to computation offloading in mobile cloud computing

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MATHEMATICAL PROGRAMMING 2016年第2期157卷 421-449页

作者： Cardellini, Valeria Persone, Vittoria De Nitto Di Valerio, Valerio Facchinei, Francisco Grassi, Vincenzo Lo Presti, Francesco Piccialli, Veronica Univ Roma Tor Vergata Dept Civil Engn & Comp Sci Engn Rome Italy Univ Roma La Sapienza Dept Comp Sci Via Salaria 113 I-00198 Rome Italy Univ Roma La Sapienza Dept Comp Control & Management Engn Via Ariosto 25 I-00185 Rome Italy

We consider a three-tier architecture for mobile and pervasive computing scenarios, consisting of a local tier of mobile nodes, a middle tier (cloudlets) of nearby computing nodes, typically located at the mobile nodes access points but characterized by a limited amount of resources, and a remote tier of distant cloud servers, which have practically infinite resources. This architecture has been proposed to get the benefits of computation offloading from mobile nodes to external servers while limiting the use of distant servers whose higher latency could negatively impact the user experience. For this architecture, we consider a usage scenario where no central authority exists and multiple non-cooperative mobile users share the limited computing resources of a close-by cloudlet and can selfishly decide to send their computations to any of the three tiers. We define a model to capture the users interaction and to investigate the effects of computation offloading on the users' perceived performance. We formulate the problem as a generalized Nash equilibrium problem and show existence of an equilibrium. We present a distributed algorithm for the computation of an equilibrium which is tailored to the problem structure and is based on an in-depth analysis of the underlying equilibrium problem. Through numerical examples, we illustrate its behavior and the characteristics of the achieved equilibria.

关键词： Mobile cloud computing Generalized Nash equilibrium problem distributed algorithm

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Self-organising multiuser matching in cellular networks: a score-based mutually beneficial approach

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IET COMMUNICATIONS 2016年第15期10卷 1928-1937页

作者： Liu, Dianxiong Xu, Yitao Shen, Liang Xu, Yuhua PLA Univ Sci & Technol Coll Commun Engn Nanjing Jiangsu Peoples R China

In this study, the authors study the self-organising user assignment problem for the multi-user cooperation network. In the cellular network with user cooperation, idle users near the base station are seen as potential relay nodes, which can assist cell edge users to transmit data. Practically, the selfish nature of users is considered in the authors' model. They design a score-based system, where the strategies of relay assignment are affected by the historical behaviours of users. That means not only the transmission performance, but also the accumulative contributions of users are considered. The proposed score-based system sufficiently encourages idle users to assist active users. Furthermore, the multi-user assignment problem is formulated as a one-to-one matching game, in which idle users and active users rank one another individually based on their own preference. To address the issue, they propose a self-organising mutually beneficial matching algorithm, which is proven to converge to a stable matching. Simulation results show that the proposed distributed algorithm yields well matching performance between source users and relay users, which is close to the optimal centralised results.

关键词： cellular radio cooperative communication data communication relay networks (telecommunication) game theory distributed algorithms self-organising multiuser matching cellular networks score-based mutually beneficial approach self-organising user assignment problem multiuser cooperation network user cooperation base station relay nodes cell edge users data transmission score-based system design relay assignment transmission performance multiuser assignment problem one-to-one matching game idle users active users self-organising mutually beneficial matching algorithm distributed algorithm

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Energy-efficient power allocation algorithm in cognitive radio networks

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IET COMMUNICATIONS 2016年第17期10卷 2445-2451页

作者： Zhou, Mingyue Zhao, Xiaohui Changchun Univ Technol Coll Comp Sci & Engn Changchun Peoples R China Jilin Univ Coll Commun Engn Changchun Peoples R China

Most of traditional power allocation algorithms are often based on maximum capacity technology (MCT) in cognitive radio networks (CRNs) at the expense of higher energy consumption. The optimisation of energy efficiency power allocation schemes are important performance in green communication. This study investigates the energy efficient power allocation for orthogonal frequency division multiplexing based CRNs in underlay mode. The authors' scheme is obtained by optimising an objective function consisting of the users' performance degradation and the network interference, in the same time to track time-varying target of signal to inference plus noise ratio (SINR) under maximum transmit power for each cognitive user and interference power constraint from primary user. A convex optimisation problem is formulated where the tradeoff between energy consumption and transmission capacity is considered, and a distributed algorithm is developed to solve this problem. Simulation results show that the authors' proposed algorithm can guarantee an acceptable target SINR for all cognitive users and significantly improves energy efficiency compared with throughput per Joule and MCT schemes. Furthermore, the proposed algorithm with the introduced appropriate weight parameters can get higher transmission capacity.

关键词： cognitive radio radio networks energy conservation energy consumption telecommunication power management convex programming radiofrequency interference environmental factors distributed algorithms target tracking OFDM modulation distributed algorithm transmission capacity convex optimisation problem primary user interference power constraint cognitive user maximum transmit power SINR signal to inference plus noise ratio time-varying target tracking network interference performance degradation objective function optimisation underlay mode orthogonal frequency division multiplexing green communication energy consumption CRN cognitive radio networks energy-efficient power allocation algorithm

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A Bayesian Demand-Side Management Strategy for Smart Micro-Grid

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TECHNOLOGY AND ECONOMICS OF SMART GRIDS AND SUSTAINABLE ENERGY 2016年第1期1卷 1-15页

作者： Sola, Matteo Vitetta, Giorgio Matteo Univ Modena & Reggio Emilia Dept Engn Enzo Ferrari Via P Vivarelli 10 Modena MO Italy

In this manuscript a novel strategy for distributed and autonomous demand-side energy management among users of a low-voltage micro-grid is developed. Its derivation is based on: a) modelling the energy consumption scheduling of the shiftable loads that belong to a given user as a noncooperative two-player game of incomplete information, in which the user itself plays against an opponent collecting all the other users of the same micro-grid;b) assuming that each user is endowed with statistical information about its behavior and that of its opponent, so that it can choose actions maximising its expected utility. Numerical results evidence the efficacy of the proposed strategy when employed to manage the charging of electric vehicles in a micro-grid.

关键词： Demand-side management Game theory distributed algorithm Smart grid Plug-in hybrid electric vehicle

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Convergecast and Broadcast by Power-Aware Mobile Agents

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algorithmICA 2016年第1期74卷 117-155页

作者： Anaya, Julian Chalopin, Jeremie Czyzowicz, Jurek Labourel, Arnaud Pelc, Andrzej Vaxes, Yann Univ Quebec Outaouais Gatineau PQ J8X 3X7 Canada CNRS LIF F-13288 Marseille France Aix Marseille Univ F-13288 Marseille France

A set of identical, mobile agents is deployed in a weighted network. Each agent has a battery-a power source allowing it to move along network edges. An agent uses its battery proportionally to the distance traveled. We consider two tasks: convergecast, in which at the beginning, each agent has some initial piece of information, and information of all agents has to be collected by some agent;and broadcast in which information of one specified agent has to be made available to all other agents. In both tasks, the agents exchange the currently possessed information when they meet. The objective of this paper is to investigate what is the minimal value of power, initially available to all agents, so that convergecast or broadcast can be achieved. We study this question in the centralized and the distributed settings. In the centralized setting, there is a central monitor that schedules the moves of all agents. In the distributed setting every agent has to perform an algorithm being unaware of the network. In the centralized setting, we give a linear-time algorithm to compute the optimal battery power and the strategy using it, both for convergecast and for broadcast, when agents are on the line. We also show that finding the optimal battery power for convergecast or for broadcast is NP-hard for the class of trees. On the other hand, we give a polynomial algorithm that finds a 2-approximation for convergecast and a 4-approximation for broadcast, for arbitrary *** the distributed setting, we give a 2-competitive algorithm for convergecast in trees and a 4-competitive algorithm for broadcast in trees. The competitive ratio of 2 is proved to be the best for the problem of convergecast, even if we only consider line networks. Indeed, we show that there is no ()-competitive algorithm for convergecast or for broadcast in the class of lines, for any .

关键词： Convergecast Broadcast Mobile agent Power-aware Centralized algorithm distributed algorithm Competitive ratio Graph

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Structured triangulation in multi-robot systems: Coverage, patrolling, Voronoi partitions, and geodesic centers

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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2016年第10期35卷 1234-1260页

作者： Lee, Seoung Kyou Fekete, Sandor P. McLurkin, James Rice Univ Dept Comp Sci Houston TX 77251 USA TU Braunschweig Dept Comp Sci Muhlenpfordtstr 23 D-38106 Braunschweig Germany

We present a fundamental framework for organizing exploration, coverage, and surveillance by a swarm of robots with limited individual capabilities, based on triangulating an unknown environment with a multi-robot system. Locally, an individual triangle is easy for a single robot to manage and covers a small area;globally, the topology of the triangulation approximately captures the geometry of the entire environment. Combined, a multi-robot system can explore, map, navigate, and patrol. algorithms can store information in triangles that the robots can read and write as they run their algorithms. This creates a physical data structure ( PDS) that is both robust and versatile. We study distributed approaches to triangulating an unknown, two-dimensional Euclidean space using a multi-robot network. The resulting PDS is a compact representation of the workspace, contains distributed knowledge of each triangle, encodes the dual graph of the triangulation, and supports reads and writes of auxiliary data. The ability to store and process this auxiliary information enables the simple robots to solve complex problems. We develop distributed algorithms for dual-graph navigation, patrolling, construction of a topological Voronoi tessellation, and location of the geodesic centers in non-convex regions. We provide theoretical performance guarantees for the quality of constructed triangulation and the connectivity of a dual graph in the triangulation. In addition, we show that the path lengths of the physical navigation are within a constant factor of the shortest-path Euclidean distance. We validate these theoretical results with simulations and experiments with a dozen or more robots.

关键词： Multi-robot system distributed algorithm space coverage robotic network localization navigation

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