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Adaptive Transmission Design for Rechargeable Wireless Sensor Network With a Mobile Sink

IEEE INTERNET OF THINGS JOURNAL 2020年第9期7卷 9011-9025页

作者： Lan, Xiaolong Zhang, Yongmin Cai, Lin Chen, Qingchun Sichuan Univ Coll Cybersecur Chengdu 610065 Peoples R China Cent South Univ Dept Comp Sci Changsha 410083 Peoples R China Univ Victoria Dept Elect & Comp Engn Victoria BC V8W 3P6 Canada Guangzhou Univ Res Ctr Intelligent Commun Engn Guangzhou 510006 Peoples R China

In this article, we aim at maximizing the data gathering performance of the rechargeable wireless sensor network, where a mobile sink moves along the predefined path to charge sensor nodes through a wireless energy transfer technique and gather data from them. First, we show how to transform the original time-average optimization problem into a queue stability one by using the Lyapunov optimization framework, then we show how to decompose it into multiple subproblems by using the optimization decomposition. A distributed speed control and routing algorithm was proposed to reduce the computing load of the mobile sink and to obtain the near-optimal solution for data collection. Our analysis shows that there is an inherent tradeoff between the network utility and the average data queuing size, and the proposed adaptive transmission scheme can achieve the near-optimal network utility when a certain queueing delay can be tolerated.

关键词： Wireless sensor networks Energy exchange Wireless communication Routing Radio frequency Array signal processing Velocity control distributed algorithm mobile sink network utility rechargeable wireless sensor networks wireless energy transfer

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Local approximation of the Maximum Cut in regular graphs

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THEORETICAL COMPUTER SCIENCE 2020年 820卷 45-59页

作者： Bamas, Etienne Esperet, Louis Ecole Polytech Fed Lausanne Sch Comp & Commun Sci Lausanne Switzerland Univ Grenoble Alpes CNRS Lab G SCOP Grenoble France

This paper is devoted to the distributed complexity of finding an approximation of the maximum cut (MAXCUT) in graphs. A classical algorithm consists in letting each vertex choose its side of the cut uniformly at random. This does not require any communication and achieves an approximation ratio of at least 1/2 in expectation. When the graph is d-regular and triangle-free, a slightly better approximation ratio can be achieved with a randomized algorithm running in a single round. Here, we investigate the round complexity of deterministic distributed algorithms for MAXCUT in regular graphs. We first prove that if G is d-regular, with d even and fixed, no deterministic algorithm running in a constant number of rounds can achieve a constant approximation ratio. We then give a simple one-round deterministic algorithm achieving an approximation ratio of 1/d for d-regular graphs when d is odd. We show that this is best possible in several ways, and in particular no deterministic algorithm with approximation ratio 1/d + epsilon (with epsilon > 0) can run in a constant number of rounds. We also prove results of a similar flavor for the MAXDICUT problem in regular oriented graphs, where we want to maximize the number of arcs oriented from the left part to the right part of the cut. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Maximum Cut Approximation algorithm distributed algorithm Regular graphs

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Fault-Tolerant Covering Points by UAVs 21

Fault-Tolerant Covering Points by UAVs

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8th International Conference on Networking, Systems and Security, NSysS 2021

作者： Samanta, Supravat Pramanick, Subhajit Mandal, Partha Sarathi Department of Mathematics Indian Institute of Technology Guwahati India

ISBN: (纸本)9781450387378

Unmanned Aerial vehicles (UAVs) or Drones crash due to power failure, communication failure, mechanical malfunction, or Cyber-Physical attacks. This paper aims to study fault-tolerant covering by UAVs, i.e., in case of failure of some UAVs, other existing non-faulty UAVs cover up the job for the faulty UAVs. We consider two communication techniques to replace the faulty UAVs: (a) with local knowledge, i.e., non-faulty neighbors of the faulty UAVs communicate between themselves to find a suitable replacement and (b) with global knowledge, where the rest of the non-faulty UAVs communicate themselves via a satellite to find a suitable replacement. Here the objective of a suitable replacement is to minimize the cost of replacement. Let P be a set of n non-negative weighted points (ground users such as fire fighters or soldiers). Using a given set of m UAVs with equal covering capacities, the objective of the covering problem is to cover a subset of points on the 2D plane such that the total weight of the covered points is maximized. The objective of our fault-tolerant covering problem is to maximize the total weight covered by the UAVs in the presence of failure and replacement of UAVs at any point of time under the two communication techniques mentioned above. In the case of globally connected, we are using a variation of Hungarian algorithm for assignment problem while in locally connected, we are using a variation of Depth-First Search. We implement both the techniques and compare the performance of the two methods through a simulation study. © 2021 ACM.

关键词： UAV Surveillance Fault tolerance distributed algorithm Coverage

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JA-BE-JA: A distributed algorithm for Balanced Graph Partitioning

JA-BE-JA: A Distributed Algorithm for Balanced Graph Partiti...

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IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

作者： Rahimian, Fatemeh Payberah, Amir H. Girdzijauskas, Sarunas Jelasity, Mark Haridi, Seif KTH Royal Inst Technol Stockholm Sweden Univ Szeged Hungarian Acad Sci Szeged Hungary

ISBN: (纸本)9780769551296

Balanced graph partitioning is a well known NP-complete problem with a wide range of applications. These applications include many large-scale distributed problems including the optimal storage of large sets of graph-structured data over several hosts-a key problem in today's Cloud infrastructure. However, in very large-scale distributed scenarios, state-of-the-art algorithms are not directly applicable, because they typically involve frequent global operations over the entire graph. In this paper, we propose a fully distributed algorithm, called JA-BE-JA, that uses local search and simulated annealing techniques for graph partitioning. The algorithm is massively parallel: there is no central coordination, each node is processed independently, and only the direct neighbors of the node, and a small subset of random nodes in the graph need to be known locally. Strict synchronization is not required. These features allow JA-BE-JA to be easily adapted to any distributed graph-processing system from data centers to fully distributed networks. We perform a thorough experimental analysis, which shows that the minimal edge-cut value achieved by JA-BE-JA is comparable to state-of-the-art centralized algorithms such as METIS. In particular, on large social networks JA-BE-JA outperforms METIS, which makes JA-BE-JA-a bottom-up, self-organizing algorithm-a highly competitive practical solution for graph partitioning.

关键词： graph partitioning distributed algorithm load balancing simulated annealing

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A Game-Based Computation Offloading Method in Vehicular Multiaccess Edge Computing Networks

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IEEE INTERNET OF THINGS JOURNAL 2020年第6期7卷 4987-4996页

作者： Wang, Yunpeng Lang, Ping Tian, Daxin Zhou, Jianshan Duan, Xuting Cao, Yue Zhao, Dezong Beihang Univ Beijing Adv Innovat Ctr Big Data & Brain Comp Sch Transportat Sci & Engn Beijing Key Lab Cooperat Vehicle Infrastruct Syst Beijing 100191 Peoples R China Loughborough Univ Dept Aeronaut & Automot Engn Loughborough LE11 3TU Leics England

Multiaccess edge computing (MEC) is a new paradigm to meet the requirements for low latency and high reliability of applications in vehicular networking. More computation-intensive and delay-sensitive applications can be realized through computation offloading of vehicles in vehicular MEC networks. However, the resources of a MEC server are not unlimited. Vehicles need to determine their task offloading strategies in real time under a dynamic-network environment to achieve optimal performance. In this article, we propose a multiuser noncooperative computation offloading game to adjust the offloading probability of each vehicle in vehicular MEC networks and design the payoff function considering the distance between the vehicle and MEC access point, application and communication model, and multivehicle competition for MEC resources. Moreover, we construct a distributed best response algorithm based on the computation offloading game model to maximize the utility of each vehicle and demonstrate that the strategy in this algorithm can converge to a unique and stable equilibrium under certain conditions. Furthermore, we conduct a series of experiments and comparisons with other offloading methods to analyze the effectiveness and performance of the proposed algorithms. The fast convergence and the improved performance of this algorithm are verified by numerical results.

关键词： Games Task analysis Computational modeling Servers Mobile handsets Computer architecture Cloud computing Computation offloading distributed algorithm game theory multiaccess edge computing (MEC)

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Adaptive algorithms for synchronization, consensus of multi-agents and anti-synchronization of direct complex networks

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NEUROCOMPUTING 2020年 414卷 365-370页

作者： Lu, Wenlian Liu, Xiwei Chen, Tianping Fudan Univ Sch Math Sci Shanghai 200433 Peoples R China Fudan Univ Inst Sci & Technol Brain Inspired Intelligence Shanghai 200433 Peoples R China Fudan Univ Shanghai Key Lab Contemporary Appl Math Shanghai 200433 Peoples R China Fudan Univ Lab Math Nonlinear Sci Shanghai 200433 Peoples R China Fudan Univ Shanghai Ctr Math Sci Shanghai 200433 Peoples R China Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

In this paper, we discuss distributed adaptive algorithms for synchronization of complex networks, consensus of multi-agents with or without pinning controller. The dynamics of individual node is governed by generalized QUAD condition. We design new algorithms, which can keep the left eigenvector of the adaptive coupling matrix corresponding to the zero eigenvalue invariant. Based on this invariance, various distributive adaptive synchronization, consensus, anti-synchronization models are given. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Adaptive distributed algorithm Consensus Synchronization Anti-synchronization

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Random Gradient-Free Optimization for Multiagent Systems With Communication Noises Under a Time-Varying Weight Balanced Digraph

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2020年第1期50卷 281-289页

作者： Wang, Dong Zhou, Jun Wang, Zehua Wang, Wei Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China

In this paper, we focus on a constrained convex optimization problem of multiagent systems under a time-varying topology. In such topology, it is not only B-strongly connected, but the communication noises are also existent. Each agent has access to its local cost function, which is a nonsmooth function. A gradient-free random protocol is come up with minimizing a sum of cost functions of all agents, which are projected to local constraint sets. First, considering the stochastic disturbances in the communication channels among agents, the upper bounds of disagreement estimate of agents' states are obtained. Second, a sufficient condition on choosing step sizes and smoothing parameters is derived to guarantee that all agents almost surely converge to the stationary optimal point. At last, a numerical example and a comparison are provided to illustrate the feasibility of the random gradient-free algorithm.

关键词： Cost function Multi-agent systems Stochastic processes Topology Smoothing methods Protocols Communication noises constrained optimization distributed algorithm random gradient-free algorithm

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Personalized Federated Learning With Differential Privacy

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IEEE INTERNET OF THINGS JOURNAL 2020年第10期7卷 9530-9539页

作者： Hu, Rui Guo, Yuanxiong Li, Hongning Pei, Qingqi Gong, Yanmin Univ Texas San Antonio Dept Elect & Comp Engn San Antonio TX 78249 USA Univ Texas San Antonio Dept Informat Syst & Cyber Secur San Antonio TX 78249 USA Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China

To provide intelligent and personalized services on smart devices, machine learning techniques have been widely used to learn from data, identify patterns, and make automated decisions. Machine learning processes typically require a large amount of representative data that are often collected through crowdsourcing from end users. However, user data could be sensitive in nature, and training machine learning models on these data may expose sensitive information of users, violating their privacy. Moreover, to meet the increasing demand of personalized services, these learned models should capture their individual characteristics. This article proposes a privacy-preserving approach for learning effective personalized models on distributed user data while guaranteeing the differential privacy of user data. Practical issues in a distributed learning system such as user heterogeneity are considered in the proposed approach. In addition, the convergence property and privacy guarantee of the proposed approach are rigorously analyzed. The experimental results on realistic mobile sensing data demonstrate that the proposed approach is robust to user heterogeneity and offers a good tradeoff between accuracy and privacy.

关键词： Privacy Data models Servers Gold Training Differential privacy Data privacy distributed algorithm machine learning

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Non-cooperative game-based multilateral contract transactions in power-heating integrated systems

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APPLIED ENERGY 2020年 268卷 114930-114930页

作者： Wang, Lu Gu, Wei Wu, Zhi Qiu, Haifeng Pan, Guangsheng Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China

The distributed trading mechanism has gained substantial popularity in protecting the privacy of the agents and reducing the computation burden. The existing studies focus on the distributed transaction mechanism applied in the power market, but the distributed multilateral transaction in the integrated energy system has not been explored. This paper proposes a novel power-heating multilateral contract transaction mechanism considering spot market prices. A multi-leader multi-follower (MLMF) Stackelberg game model is formulated to describe the multilateral contract transactions between the integrated energy service providers (IESPs) and the load aggregators (LAs). In this model, the IESPs play the role of leaders to select discriminate prices for different LAs while the LAs play the role of followers to determine the energy purchases. The competition among IESPs is formulated as a non-cooperative Nash game, where each stakeholder seeks to maximize its own profit. Then, the existence of the Nash equilibrium is proved. Besides, a distributed algorithm is developed to derive the equilibrium of the proposed hierarchical decision model, through which the optimal strategies for each player can be obtained. Two case studies with different scales demonstrate the effectiveness of the proposed contract transaction mechanism and the distributed solution algorithm.

关键词： Non-cooperative game distributed algorithm Multilateral contract transaction Multi-energy system Price discrimination

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Periodic event-triggered control of flywheel energy storage matrix systems for wind farms

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IET CONTROL THEORY AND APPLICATIONS 2020年第11期14卷 1467-1477页

作者： Sun, Yizhuo Hu, Jiangping Liu, Jianxing Harbin Inst Technol Sch Astronaut Harbin 150001 Peoples R China Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China

Flywheel energy storage plays a significant role in improving the reliability and efficiency of wind farm operations, in recent years. In order to reduce the communication burden, this study proposes a distributed algorithm based on the event triggered to coordinate the operation of wind farm and flywheel energy storage matrix system (FESMS). Different from the traditional sampling mechanism, a periodic sampling-based event-triggered condition, which is based on the disagreement vector and the measurement error, is proposed for the FESMS dispatch problem. Furthermore, a self-triggered method is also studied as well considering the periodic sampling case. The algorithm achieves ratio consensus in a balanced directed graph topology. By simulation, the effectiveness of the proposed algorithm is verified.

关键词： flywheels distributed control directed graphs graph theory wind power plants energy storage topology distributed algorithms wind farm operations distributed algorithm traditional sampling mechanism periodic sampling-based event-triggered condition self-triggered method periodic sampling case periodic event-triggered control flywheel energy storage matrix systems reliability

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