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distributed trigger counting algorithms for arbitrary network topology

WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2016年第16期16卷 2463-2476页

作者： Chang, Che-Cheng Tsai, Jichiang Natl Chung Hsing Univ Dept Elect Engn Taichung 40227 Taiwan Natl Chung Hsing Univ Grad Inst Commun Engn Taichung Taiwan

The distributed trigger counting (DTC) problem is a fundamental block for many distributed applications. Particularly, such a problem is to raise an alert while the number of triggers received by the whole system reaches a pre-defined amount. There have been a few algorithms proposed to solve the DTC problem in the literature. However, these existing algorithms are all under the assumption that each process knows what kind of network topology the whole system forms as well as playing distinct kind of role in the system. The foregoing assumption is not practical for wireless sensor networks because the network topology of a wireless sensor network cannot be obtained in advance, and the roles of all processes are basically identical during the computation. In this paper, we propose a novel distributed algorithm to solve the DTC problem, free of any aforementioned global assumption. Moreover, in order to reduce the message complexity of our algorithm, we further propose a more message-efficient version, only with one extra requirement that all processes have learned ahead the number of processes in the system. Copyright (C) 2016 John Wiley & Sons, Ltd.

关键词： distributed trigger counting wireless sensor networks distributed algorithms

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A distributed multi-path routing algorithm to balance energy consumption in wireless sensor networks

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AD HOC NETWORKS 2017年 64卷 53-64页

作者： Laouid, Abdelkader Dahmani, Abdelnasser Bounceur, Ahcene Euler, Reinhardt Lalem, Farid Tari, Abdelkamel Univ Bejaia Targa Ouzemmour LIMED Lab Bejaia Algeria Univ Bretagne Occidentale CNRS UMR 6285 Lab STICC 20 Ave Le Gorgeu F-29238 Brest France Univ Ctr Tamanrasset Tamanrasset Algeria

A large use of applications of Wireless Sensor Networks (WSNs) pushes researchers to design and improve protocols and algorithms against the encountered challenges. One of the main goals is data gathering and routing to the base station (through the sink nodes) with lack of acknowledgement and where each node has no information about the network. Unbalanced energy consumption during the data routing process is an inherent problem in WSNs due to the limited energy capacity of the sensor nodes. In fact, WSNs require load balancing algorithms that make judicious use of the limited energy resource to route the gathered data to the sink node. In this paper, we propose a balanced multi-path routing algorithm by focusing on the residual energy and the hop count of each node to discover the best routes and to insert them into the routing table. The main idea of this algorithm comes from Ant Colony Optimization (ACO) and automata network modelization. Hence, the potential performance of the proposed algorithm relies on the best route to be selected which should have the minimum number of hops, the maximum energy and weighted energy between participating nodes to extend the lifetime of the network. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Wireless sensor networks Route discovering algorithms Balancing resource consumption Lifetime maximization distributed algorithms

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A distributed Consensus-Based Clock Synchronization Protocol for Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2017年第4期95卷 4579-4600页

作者： Aissaoua, Habib Aliouat, Makhlouf Bounceur, Ahcene Euler, Reinhardt Univ Abderrahmane Mira Dept Comp Sci Bejaia Algeria Univ Ferhat Abbas Setif 1 Dept Comp Sci Setif Algeria Univ Western Brittany Lab STICC CNRS Lab Brest France

The birth of computer networks and distributed systems has led to the appearance of the clock synchronization problem. This issue has gained increasing importance with the emergence of new resource constrained networks such as wireless sensor networks. In this paper, we propose a new distributed clock synchronization algorithm, referred to as Weighted Consensus Clock Synchronization (WCCS), whose objective is to achieve a consensus clock among network nodes. In this distributed approach and in contrast to centralized schemes, each node periodically exchanges the local clock reading with its immediate neighbor nodes. Then, each node employs these time informations to calculate its relative offset and skew with respect to its neighbor nodes using a weighted average consensus based technique. The effectiveness of WCCS is proved through both simulations and an experimental study on TelosB mote using TinyOS.

关键词： Consensus algorithm Convergence Clock drift Wireless sensor networks distributed algorithms

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Large graph visualizations using a distributed computing platform

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INFORMATION SCIENCES 2017年 381卷 124-141页

作者： Arleo, Alessio Didimo, Walter Liotta, Giuseppe Montecchiani, Fabrizio Univ Perugia Dipartimento Ingn I-06100 Perugia Italy

Big Data analytics is recognized as one of the major issues in our current information society, and raises several challenges and opportunities in many fields, including economy and finance, e-commerce, public health and administration, national security, and scientific research. The use of visualization techniques to make sense of large volumes of information is an essential ingredient, especially for the analysis of complex interrelated data, which are represented as graphs. The growing availability of powerful and inexpensive cloud computing services naturally motivates the study of distributed graph visualization algorithms, able to scale to the size of large graphs. We study the problem of designing a distributed visualization algorithm that must be simple to implement and whose computing infrastructure does not require major hardware or software investments. We design, implement, and experiment a force-directed algorithm in Giraph, a popular open source framework for distributed computing, based on a vertex-centric design paradigm. The algorithm is tested both on real and artificial graphs with up to one million edges. The experiments show the scalability and effectiveness of our technique when compared to a centralized implementation of the same force-directed model. Graphs with about one million edges can be drawn in a few minutes, by spending about 1 USD per drawing with a cloud computing infrastructure of Amazon. (C) 2016 Published by Elsevier Inc.

关键词： Large graphs Network visualization Force-directed techniques distributed algorithms Giraph Big data Cloud computing

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distributed Finite-Time Average-Consensus With Limited Computational and Storage Capability

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2017年第2期4卷 380-391页

作者： Oliva, Gabriele Setola, Roberto Hadjicostis, Christoforos N. Univ Campus Biomed Roma Dept Engn Unit Automat I-00128 Rome Italy Univ Cyprus Dept Elect & Comp Engn CY-1678 Nicosia Cyprus

Consensus is a fundamental feature of distributed systems, and it is the prerequisite for several complex tasks, such as flocking of mobile robots, localization in wireless-sensor networks, or decentralized control of smart grids. Average consensus, in particular, is quite challenging, because it is typically obtained asymptotically, while few finite-time algorithms are available. In this paper, we provide a methodology to achieve distributed average consensus in finite time, while maintaining low computational and memory requirements, and small completion times. The provided solution, namely, finite-time average-consensus by iterated max-consensus (FAIM) is based on several runs of the max-consensus algorithm, and has low memory requirements for each node. Compared to existing Flooding approaches, the proposed algorithm requires less memory, at the cost of a slight increase in the number of steps required for termination. The FAIM algorithm assumes that the nodes are aware of an upper bound on the network diameter. To relax this assumption, we complement this paper with a novel distributed algorithm that, in the case of undirected graphs, provides an upper bound on the network diameter which, in the worst case, is twice the actual diameter. A comparison of the proposed finite-time algorithm against the state of the art concludes this paper.

关键词： distributed algorithms finite-time average consensus max consensus

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distributed Nash equilibrium seeking for aggregative games with coupled constraints

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AUTOMATICA 2017年 85卷 179-185页

作者： Liang, Shu Yi, Peng Hong, Yiguang Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Univ Toronto Dept Elect & Comp Engn Toronto ON Canada Chinese Acad Sci Key Lab Syst & Control Acad Math & Syst Sci Beijing 100190 Peoples R China

In this paper, we study a distributed continuous-time design for aggregative games with coupled constraints in order to seek the generalized Nash equilibrium by a group of agents via simple local information exchange. To solve the problem, we propose a distributed algorithm based on projected dynamics and non-smooth tracking dynamics, even for the case when the interaction topology of the multi-agent network is time-varying. Moreover, we prove the convergence of the non-smooth algorithm for the distributed game by taking advantage of its special structure and also combining the techniques of the variational inequality and Lyapunov function. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： distributed algorithms Aggregative games Generalized Nash equilibrium Projected dynamics Coupled constraints

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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2017年 77卷 139-148页

作者： Tahir, Mohammad Habaebi, Mohamed Hadi Islam, Md. Rafiqul Int Islamic Univ Malaysia Dept Elect & Comp Engn Gombak Malaysia

In this paper, we propose a novel algorithm for improving spectrum sensing in cognitive radio networks by forming coalitions among cognitive radio users in a fading channel environment. We use concepts from matching theory, specifically the stable marriage problem, to formulate the interactions among the cognitive radio users as a matching game for collaborative distributed spectrum sensing under target detection probability constraint. The utility function is defined as the average probability of false alarm per cognitive radio user. The advantage of stable marriage is that it always converges to a stable matching and is Pareto optimal when the preferences of cognitive radios are strict. In the proposed model, we extend the stable matching problem to propose a novel algorithm to form coalitions of varying sizes for improving the utility of cognitive radios (false alarm and throughput). The coalitions formed using the algorithm are stable and do not deviate from the final matching. We show using simulations that the proposed algorithm leads to stable coalitions and returns significant improvement in term of reduced probability of false alarm and improved throughput per cognitive radio user as compared to the noncooperative scenario. (C) 2017 Elsevier GmbH. All rights reserved.

关键词： Cognitive radio Spectrum sensing distributed algorithms Stable matching Gale-Shapley algorithm

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Decentralized Stochastic Optimal Power Flow in Radial Networks With distributed Generation

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IEEE TRANSACTIONS ON SMART GRID 2017年第2期8卷 787-801页

作者： Bazrafshan, Mohammadhafez Gatsis, Nikolaos Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA

This paper develops a power management scheme that jointly optimizes the real power consumption of programmable loads and reactive power outputs of photovoltaic (PV) inverters in distribution networks. The premise is to determine the optimal demand response schedule that accounts for the stochastic availability of solar power, as well as to control the reactive power generation or consumption of PV inverters adaptively to the real power injections of all PV units. These uncertain real power injections by PV units are modeled as random variables taking values from a finite number of possible scenarios. Through the use of second order cone relaxation of the power flow equations, a convex stochastic program is formulated. The objectives are to minimize the negative user utility, cost of power provision, and thermal losses, while constraining voltages to remain within specified levels. To find the global optimum point, a decentralized algorithm is developed via the alternating direction method of multipliers that results in closed-form updates per node and per scenario, rendering it suitable to implement in distribution networks with a large number of scenarios. Numerical tests and comparisons with an alternative deterministic approach are provided for typical residential distribution networks that confirm the efficiency of the algorithm.

关键词： Optimal power flow distribution networks photovoltaic inverters stochastic optimization alternating direction method of multipliers distributed algorithms

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D-LPCN: A distributed least polar-angle connected node algorithm for finding the boundary of a wireless sensor network

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AD HOC NETWORKS 2017年 56卷 56-71页

作者： Saoudi, Massinissa Lalem, Farid Bounceur, Ahcene Euler, Reinhardt Kechadi, M-Tahar Laouid, Abdelkader Bezoui, Madani Sevaux, Marc Lab STICC UMR CNRS 6285 Lorient France Univ Boumerdes Dept Math Boumerdes Algeria Univ Coll Dublin Lab CASL Lab Dublin 4 Ireland Univ Bejaia LIMED Lab Bejaia 06000 Algeria Ctr Rech BP 92116 F-56321 Lorient France Univ Bretagne Occidentale 20 Ave Victor Le Gorgeu F-29238 Brest France

A boundary of wireless sensor networks (WSNs) can be used in many fields, for example, to monitor a frontier or a secure place of strategic sensitive sites like oil fields or frontiers of a country. This situation is modeled as the problem of finding a polygon hull in a connected Euclidean graph, which represents a minimal set of connected boundary nodes. In this paper we propose a new algorithm called D-LPCN (distributed Least Polar -angle Connected Node) which represents the distributed version of the LPCN algorithm introduced in [1]. In each iteration, any boundary node, except the first one, chooses its nearest polar angle node among its neighbors with respect to the node found in the previous iteration. The first starting node can be automatically determined using the Minimum Finding algorithm, which has two main advantages. The first one is that the algorithm works with any type of a connected network, given as planar or not. Furthermore, it takes into account any blocking situation and contains the necessary elements to avoid them. The second advantage is that the algorithm can determine all the boundaries of the different connected parts of the network. The proposed algorithm is validated using the Cup Carbon, Tossim and Contiki simulators. It has also been implemented using real sensor nodes based on the TeloSB and Arduino/XBee platforms. We have estimated the energy consumption of each node and we have found that the consumption of the network depends on the number of the boundary nodes and their neighbors. The simulation results show that the proposed algorithm is less energy consuming than the existing algorithms and its distributed version is less energy consuming than the centralized version. (C) 2016 Elsevier B.V. All rights reserved.

关键词： distributed algorithms Wireless sensor networks Boundary detection Energy consumption Polygon hull

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Consensus plus Innovations distributed Kalman Filter With Optimized Gains

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2017年第2期65卷 467-481页

作者： Das, Subhro Moura, Jose M. F. IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

In this paper, we address the distributed filtering and prediction of time-varying random fields represented by linear time-invariant (LTI) dynamical systems. The field is observed by a sparsely connected network of agents/sensors collaborating among themselves. We develop a Kalman filter type consensus+innovations distributed linear estimator of the dynamic field termed as Consensus+Innovations Kalman Filter. We analyze the convergence properties of this distributed estimator. We prove that the mean-squared error of the estimator asymptotically converges if the degree of instability of the field dynamics is within a prespecified threshold defined as tracking capacity of the estimator. The tracking capacity is a function of the local observation models and the agent communication network. We design the optimal consensus and innovation gain matrices yielding distributed estimates with minimized mean-squared error. Through numerical evaluations, we show that the distributed estimator with optimal gains converges faster and with approximately 3dB bettermean-squared error performance than previous distributed estimators.

关键词： Kalman filter distributed estimation multi-agent networks distributed algorithms consensus

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