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Generalized Global Bandit and Its Application in Cellular coverage optimization

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2018年第1期12卷 218-232页

作者： Shen, Cong Zhou, Ruida Tekin, Cem van der Schaar, Mihaela Univ Sci & Technol China Sch Informat Sci & Technol Hefei 230027 Anhui Peoples R China Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey Univ Oxford Oxford Man Inst Quantitat Finance OMI Oxford OX1 2JD England Univ Oxford Dept Engn Sci Oxford OX1 2JD England Univ Calif Los Angeles Elect Engn Dept Los Angeles CA 90095 USA

Motivated by the engineering problem of cellular coverage optimization, we propose a novel multiarmed bandit model called generalized global bandit. We develop a series of greedy algorithms that have the capability to handle nonmonotonic but decomposable reward functions, multidimensional global parameters, and switching costs. The proposed algorithms are rigorously analyzed under the multiarmed bandit framework, where we show that they achieve bounded regret, and hence, they are guaranteed to converge to the optimal arm infinite time. The algorithms are then applied to the cellular coverage optimization problem to achieve the optimal tradeoff between sufficient small cell coverage and limited macroleakage without prior knowledge of the deployment environment. The performance advantage of the new algorithms over existing bandits solutions is revealed analytically and further confirmed via numerical simulations. The key element behind the performance improvement is a more efficient "trial and error" mechanism, in which any trial will help improve the knowledge of all candidate power levels.

关键词： Multi-armed bandit online learning regret analysis coverage optimization

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An Energy Efficient Autonomous Method for coverage optimization in Wireless Multimedia Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2018年第2期99卷 717-736页

作者： Pournazari, Jaber Alaei, Mohammad Yazdanpanah, Fahimeh Shahid Bahonar Univ Kerman Dept Comp Engn Fac Engn Kerman Iran Vali E Asr Univ Rafsanjan Dept Comp Engn Fac Engn Rafsanjan Iran

In this paper, a distributed method for coverage optimization of random deployed WMSNs utilizing motility and mobility capabilities of nodes, is proposed. The aims followed by the method are first, maximizing the coverage ratio by minimizing both the covered overlapping areas, and the coverage holes after random deployment, and second, enhancing energy efficiency of the coverage optimization procedure, by minimizing the needed rotations and specially movements, comparing with the previous schemes. To these aims, the most appropriate location and orientation of the nodes are calculated round by round considering all the possible nested compositions of rotation and movement. But, rotating and moving the nodes are performed after terminating the algorithm rounds and achieving the decisive results. So, the proposed method does not impose the overhead of trial and error of rotation or relocation on the network nodes. The performance of the proposed approach has been compared with the previous works for different network configurations;simulation results show that the proposed approach outperforms the previous schemes in terms of both coverage ratio and energy efficiency.

关键词： Wireless multimedia sensor networks coverage optimization Energy efficiency Motility Mobility

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A Virtual Force Algorithm-Levy-Embedded Grey Wolf optimization Algorithm for Wireless Sensor Network coverage optimization

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SENSORS 2019年第12期19卷 2735.-2735.页

作者： Wang, Shipeng Yang, Xiaoping Wang, Xingqiao Qian, Zhihong Jilin Univ Coll Commun Engn Changchun 130012 Jilin Peoples R China

The random placement of a large-scale sensor network in an outdoor environment often causes low coverage. In order to effectively improve the coverage of a wireless sensor network in the monitoring area, a coverage optimization algorithm for wireless sensor networks with a Virtual Force-Levy-embedded Grey Wolf optimization (VFLGWO) algorithm is proposed. The simulation results show that the VFLGWO algorithm has a better optimization effect on the coverage rate, uniformity, and average moving distance of sensor nodes than a wireless sensor network coverage optimization algorithm using Levy-embedded Grey Wolf Optimizer, Cuckoo Search algorithm, and Chaotic Particle Swarm optimization. The VFLGWO algorithm has good adaptability with respect to changes of the number of sensor nodes and the size of the monitoring area.

关键词： wireless sensor network Levy-embedded Grey Wolf optimization algorithm Virtual Force algorithm coverage optimization

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Node coverage optimization algorithm for wireless sensor networks based on improved grey wolf optimizer

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JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY 2019年第13期13卷 -页

作者： Wang, Zhendong Xie, Huamao Hu, Zhongdong Li, Dahai Wang, Junling Liang, Wen Jiangxi Univ Sci & Technol Coll Informat Engn Ganzhou 341000 Jiangxi Peoples R China

Aiming at the problem of wireless sensor network node coverage optimization with obstacles in the monitoring area, based on the grey wolf optimizer algorithm, this paper proposes an improved grey wolf optimizer (IGWO) algorithm to improve the shortcomings of slow convergence, low search precision, and easy to fall into local optimum. Firstly, the nonlinear convergence factor is designed to balance the relationship between global search and local search. The elite strategy is introduced to protect the excellent individuals from being destroyed as the iteration proceeds. The original weighting strategy is improved, so that the leading wolf can guide the remaining grey wolves to prey in a more reasonable way. The design of the grey wolf's boundary position strategy and the introduction of dynamic variation strategy enrich the population diversity and enhance the ability of the algorithm to jump out of local optimum. Then, the benchmark function is used to test the convergence performance of genetic algorithm, particle swarm optimization, grey wolf optimizer, and IGWO algorithm, which proves that the convergence performance of IGWO algorithm is better than the other three algorithms. Finally, the IGWO algorithm is applied to the deployment of wireless sensor networks with obstacles (rectangular obstacle, trapezoidal obstacle and triangular obstacles). Simulation results show that compared with GWO algorithm, IGWO algorithm can effectively improve the coverage of wireless sensor network nodes and obtain higher coverage rate with fewer nodes, thereby reducing the cost of deploying the network.

关键词： Wireless sensor network coverage optimization improved grey wolf algorithm coverage

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coverage optimization of VLC in smart homes based on improved cuckoo search algorithm

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COMPUTER NETWORKS 2017年第Apr.7期116卷 63-78页

作者： Sun, Geng Liu, Yanheng Yang, Ming Wang, Aimin Liang, Shuang Zhang, Ying Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Coll Software Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA

Light-emitting diodes (LEDs) are often placed on the ceiling in smart homes for visible light communications. However, the layout of LEDs will lead to the uneven distribution of the received optical power and signal-to-noise ratio (SNR) on the same receiving plane, which cannot guarantee fairness of communication. To solve this problem, we used an LED source array and introduced a power adjustment factor to determine a set of optimal power regulators to improve the power distribution on the same receiving plane. We proposed an improved cuckoo search (ICS) algorithm based on chaos theory and dimension cells to solve the normal CS algorithm convergence problem. The chaos mechanism will optimize the random distribution of the initial solution for chaotic distribution, and it can achieve an improved quality of the initial solutions. Moreover, we divided the multidimensional solutions into several dimension cells to avoid interference between dimensions. Simulation results show that the accuracy and the convergence rate of the ICS algorithm is better than that of CS, particle swarm optimization, and evolutionary algorithm. Furthermore, the fairness of the received optical power and SNR on the same receiving plane can be clearly improved. (C) 2017 Elsevier B.V. All rights reserved.

关键词： coverage optimization Cuckoo search Smart home Visible light communication

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coverage optimization for UAV-Aided Internet of Things with Partial Channel Knowledge

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Journal of Communications and Information Networks 2018年第4期3卷 55-63页

作者： Xuanxuan Wang Wei Feng Yunfei Chen Ning Ge Beijing National Research Center for Infor-mation Science and Technology(BNRist) Department of Electronic Engi-neeringTsinghua UniversityBeijing 100084China School of Engineering the University of WarwickCoventryCV47ALUK

Due to the high maneuverability of unmanned aerial vehicles(UAVs),they have been widely deployed to boost the performance of Internet of Things(IoT).In this paper,to promote the coverage performance of UAV-aided IoT communications,we maximize the minimum average rate of the IoT devices by jointly optimizing the resource allocation strategy and the UAV ***,to depict the practical propagation environment,we take the composite channel model including both the small-scale and the large-scale channel fading into *** to the difficulty in acquiring the random small-scale channel fading,we assume that only the large-scale channel sate information is *** this basis,we formulate an optimization problem,which is not convex and challenging to ***,an efficient iterative algorithm is proposed using block coordinate descent and successive convex optimization ***,simulation results are presented to demonstrate the significant performance gain of the proposed scheme over existing ones.

关键词： block coordinate descent coverage optimization IoT UAVs

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A Novel Framework for coverage optimization of Sensor Network 11th

A Novel Framework for Coverage Optimization of Sensor Networ...

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11th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Xu, Rui Chai, Li Chen, Xi Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Hubei Peoples R China Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Measurement Technol Wuhan 430081 Hubei Peoples R China

ISBN: (纸本)9783319975863;9783319975856

In this paper, the coverage optimization of a circular sector sensor network in a region is considered. We propose a new framework to solve this problem, in which a so-called optimization matrix is constructed to addresses the coverage strength of every sensor to all sampling points, and the overlap coverage strength of every two sensors. Then, the coverage optimization of sensor network is equivalent to maximize the coverage strength of all sensors to all points in the target space subject to each overlap coverage strength of every two sensors is smaller than a threshold. This framework is general and can be applied to any networked sensors with different coverage models or geometries. Moreover, a simulation example is provided to illustrate the effectiveness of the proposed method.

关键词： Sensor network coverage optimization

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Wireless Sensor Network coverage optimization Based on Fruit Fly Algorithm

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INTERNATIONAL JOURNAL OF ONLINE ENGINEERING 2018年第6期14卷 58-70页

作者： Song, Ren Xu, Zhichao Liu, Yang Jilin Univ Finance & Econ Jilin Jilin Peoples R China

To solve the defect of traditional node deployment strategy, the improved fruit fly algorithm was combined with wireless sensor network. The optimization of network coverage was implemented. Based on a new type of intelligent algorithm, the change step of fruit fly optimization algorithm (CSFOA) was proposed. At the same time, the mathematical modeling of two network models was carried out respectively. The grid coverage model was used. The network coverage and redundancy were transformed into corresponding mathematical variables by means of grid partition. Among them, the maximum effective radius of sensor nodes was fixed in mobile node wireless sensor network. The location of nodes was randomly cast. The location of sensor nodes was placed in fixed position nodes. The effective radius of nodes can be changed dynamically. Finally, combined with the corresponding network model, the improved algorithm was applied to wireless sensor network. The combination of the optimal solution of the node position and the perceptual radius was found through the algorithm. The maximum network coverage was achieved. The two models were simulated and verified. The results showed that the improved algorithm was effective and superior to the coverage optimization of wireless sensor networks.

关键词： wireless sensor networks coverage optimization sensor nodes

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coverage optimization Algorithms Based on Voronoi Diagram in Software-Defined Sensor Networks 8

Coverage Optimization Algorithms Based on Voronoi Diagram in...

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8th International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Tang, Min Yan, Feng Deng, Shuguang Shen, Lianfeng Kuang, Sufeng Xing, Song Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Jiangsu Peoples R China Hunan City Univ Coll Commun & Elect Engn Yiyang 413000 Peoples R China Calif State Univ Los Angeles Dept Informat Syst Los Angeles CA 90032 USA

ISBN: (纸本)9781509028603

In this paper, two coverage optimization algorithms based on Voronoi diagram are proposed to reduce the energy consumption of software-defined sensor networks (SDSNs). In the first algorithm named Minimax Radius Algorithm (MRA), we try to reduce the sensing radii of nodes as much as possible while preserving the original network coverage. In the second algorithm named Sleeping-based Algorithm (SLA), we try to set as many nodes as possible into sleep mode without generating new coverage holes. Simulation results show that both algorithms can reduce the energy consumption significantly and the energy reduction rate increases with no des' sensing radius and the number of nodes.

关键词： software-defined sensor networks Voronoi diagram coverage optimization

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coverage optimization for Wireless Sensor Networks by Evolutionary Algorithm 7th

Coverage Optimization for Wireless Sensor Networks by Evolut...

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7th International Symposium on Intelligence Computation and Applications (ISICA)

作者： Li, Kangshun Wen, Zhichao Li, Shen South China Agr Univ Coll Math & Informat Guangzhou 510642 Guangdong Peoples R China

ISBN: (纸本)9789811003561;9789811003554

Wireless sensor network consists of a large number of tiny sensor nodes owned capable of perception in monitoring region by self-organized wireless communication, has been widely applied in military and civil fields. From the perspective of resource-saving, under the condition of the network's connectivity and specific coverage, the number of sensor nodes is assumed to be opened as few as possible. So, computing the sensor nodes collection which meeting the requirements is called the problem of network coverage optimization for Wireless Sensor Network;also called the problem of minimum connected covering node set. The innovation point of the article is: Firstly, it analyzed the deficiencies of traditional evolution algorithm fitness function, put forward an improved fitness function design scheme, and has been proved that it has advantage of solving problem on wireless sensor networks coverage optimization;Secondly, it applied the method of control variables, comparison and analysis of the influence on the various operations and parameters selection in evolution algorithm on the optimization results and performance, and then point out how to design algorithm to manage to the best optimize effect and performance.

关键词： Wireless sensor network Evolutionary algorithm coverage optimization

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