Research on Coverage Optimization Methods for Wireless Sensor Networks Based on an Improved Genetic Algorithm

2014 ◽  
Vol 644-650 ◽  
pp. 2116-2119
Author(s):  
Xiao Chun Lou ◽  
Xie Yu
Keyword(s):  
Genetic Algorithm ◽  
Quality Of Service ◽  
Wireless Sensor Network ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Improved Genetic Algorithm ◽  
Effective Coverage ◽  
Coverage Control ◽  
Coverage Optimization

Wireless sensor network coverage control is studied under conditions to ensure quality of service, in order to maximize network coverage, covering the use and application of the algorithm optimization strategy, contribute to the effective control of the network node energy and improve the perceived quality of service network lifetime extension of time. This paper presents an improved genetic algorithm to optimize the network effective coverage of the target, achieved through the coverage control algorithm crossover and mutation operation and a detailed analysis of the impact of sensing radius of coverage performance. Simulation results show that the algorithm is effective coverage reaches more than 85%, can effectively achieve wireless sensor network coverage optimization.

scholarly journals CMTN-SP: A Novel Coverage-Control Algorithm for Moving-Target Nodes Based on Sensing Probability Model in Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 257 ◽  
Author(s):  
Zeyu Sun ◽  
Xiaofei Xing ◽  
Ben Yan ◽  
Zhiguo Lv
Keyword(s):  
Sensor Networks ◽  
Control Algorithm ◽  
Probability Model ◽  
Communication Link ◽  
Moving Target ◽  
Network Coverage ◽  
Coverage Control ◽  
Redundant Data ◽  
Blind Area ◽  
Coverage Quality

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy.

VCHR: Virtual Cluster-Based Hybrid Routing Protocol

2011 ◽  
Vol 467-469 ◽  
pp. 2117-2122
Author(s):  
Zhen Wang ◽  
Lin Huang
Keyword(s):  
Routing Protocol ◽  
Base Station ◽  
Sensor Nodes ◽  
Network Dynamic ◽  
Network Coverage ◽  
Virtual Cluster ◽  
Hierarchical Routing ◽  
Shortest Path Routing ◽  
Hybrid Routing ◽  
Coverage Control

There are a couple of inherent shortcomings which are hard to be overcome in single topology network; thus we propose a novel routing protocol—VCHR, i.e., Virtual Cluster-based Hybrid Routing, which employs hybrid topology, bears the stamp of flat and hierarchical routing protocol. At stage of hierarchical routing, VCHR draws on the idea of the virtual cluster; base station controls clustering process based on network coverage control criteria in centralized model, and ensuring the reliability of virtual clusters by making use of the three-way handshake mechanism. Flat routing employs shortest path routing protocol to get the optimized routing path to base station. In context of low algorithm complexity, the protocol could realize full network coverage control, effectively balance energy load among sensor nodes and quickly respond to network dynamic changes.

scholarly journals Multiobjective Coverage Control Strategy for Energy-Efficient Wireless Sensor Networks

2012 ◽  
Vol 8 (4) ◽  
pp. 720734 ◽  
Author(s):  
Hui Zhou ◽  
Tian Liang ◽  
Chen Xu ◽  
Jing Xie
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Control Strategy ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Coverage Control ◽  
Free Search

A multiobjective optimization coverage control strategy is proposed for solving the contradictory problem among energy consumption, equilibrium of energy, and network coverage in wireless sensor networks. A new evolutionary algorithm named Multiobjective free search algorithm (MOFS) is designed for WSN optimization problem based on fitness functions and binary coding schemes. The proposed strategy is used to estimate the number of active nodes because individual nodes cannot have their working state information readily. Simulation shows that MOFS is effective to solve the typical combinatorial optimization problem, and the coverage control strategy can obtain high network coverage and reduce energy consumption effectively by the reasonable selecting parameters, while equilibrium of energy consumption is also considered.

scholarly journals Coverage Control Optimization Algorithm for Wireless Sensor Networks Based on Combinatorial Mathematics

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yongjie Wang ◽  
Maolin Li
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Completion Time ◽  
Particle Swarm ◽  
Wireless Sensor ◽  
Network Coverage ◽  
Convergence Problem ◽  
Swarm Optimization ◽  
Coverage Control ◽  
Control Optimization

The traditional wireless sensor network coverage control optimization algorithm has the problems of long completion time, high energy consumption, and low coverage. A new algorithm based on combinational mathematics for wireless sensor network coverage control is proposed. The particle swarm optimization (PSO) algorithm is used to optimize the coverage control process of wireless sensor networks. Then, the combined mathematics method is used to detect the local convergence problem. Finally, the quasi-physical forces of quasi-gravity and Coulomb force are used to integrate the quasi-physical force into the particle. In the process of velocity evolution, the speed correction process of particle swarm optimization is optimized, which can effectively avoid the local convergence problem of the particle swarm optimization algorithm, reduce the repeated coverage, and expand the coverage. The experimental results show that compared with the traditional algorithm, the proposed algorithm has short completion time, low energy consumption, and high coverage.

Study and improvement on coverage control algorithm in WSN

2010 ◽  
Vol 30 (6) ◽  
pp. 1459-1462
Author(s):  
Yang TAO ◽  
Xiao-ling ZENG ◽  
Wei LUO
Keyword(s):  
Control Algorithm ◽  
Coverage Control

Research on Coverage Control Algorithm of CDMA Bunched System

2011 ◽  
Vol 30 (6) ◽  
pp. 1437-1440
Author(s):  
Ying-xun Zhu ◽  
Rong Wang ◽  
Xiao-xin Yi
Keyword(s):  
Control Algorithm ◽  
Coverage Control

Performance analysis of various massive MIMO detection algorithms in 5G Wireless technologies

2019 ◽  
Vol 10 ◽  
Author(s):  
Shihab Jimaa ◽  
Jawahir Al-Ali
Keyword(s):  
Massive Mimo ◽  
Spectrum Efficiency ◽  
System Capacity ◽  
Network Coverage ◽  
Mimo Detection ◽  
Infinity Norm ◽  
Detection Algorithms ◽  
Alternating Direction ◽  
5G Systems ◽  
Efficient Power

Background: The 5G will lead to a great transformation in the mobile telecommunications sector. Objective: The huge challenges being faced by wireless communications such as the increased number of users have given a chance for 5G systems to be developed and considered as an alternative solution. The 5G technology will provide a higher data rate, reduced latency, more efficient power than the previous generations, higher system capacity, and more connected devices. Method: It will offer new different technologies and enhanced versions of the existing ones, as well as new features. 5G systems are going to use massive MIMO (mMIMO), which is a promising technology in the development of these systems. Furthermore, mMIMO will increase the wireless spectrum efficiency and improve the network coverage. Result: In this paper we present a brief survey on 5G and its technologies, discuss the mMIMO technology with its features and advantages, review the mMIMO capacity and energy efficiency and also presents the recent beamforming techniques. Conclusion: Finally, simulation of adopting different mMIMO detection algorithms are presented, which shows the alternating direction method of multipliers (ADMM)-based infinity-norm (ADMIN) detector has the best performance.

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