Improve Energy Consumption and Signal Transmission Quality of Routings in Wireless Sensor Networks

被引:12
作者
Yeh, Wei-Chang [1 ]
Jiang, Yunzhi [2 ]
Huang, Chia-Ling [3 ]
Xiong, Neal N. [4 ]
Hu, Cheng-Feng [5 ]
Yeh, Yuan-Hui [6 ]
机构
[1] Natl Tsing Hua Univ, Dept Ind Engn & Engn Management, Integrat & Collaborat Lab, Hsinchu 300, Taiwan
[2] Guangdong Polytech Normal Univ, Sch Math & Syst Sci, Guangzhou 510665, Peoples R China
[3] KAINAN Univ, Dept Int Logist & Transportat Management, Taoyuan 338, Taiwan
[4] Northeastern State Univ, Dept Math & Comp Sci, Tahlequah, OK 74464 USA
[5] Natl Chiayi Univ, Dept Appl Math, Chiayi 600, Taiwan
[6] Univ New South Wales, Business Sch, Sch Law, Sydney, NSW 2052, Australia
关键词
Wireless sensor networks; Energy consumption; Wireless communication; Reliability; Particle swarm optimization; Erbium; Mathematics; Wireless sensor network; energy consumption; network reliability; routing; algorithms; RELIABILITY; SELECTION; PATH;
D O I
10.1109/ACCESS.2020.3030629
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wireless (smart) sensor networks (WSNs) comprise a myriad of embedded wireless smart sensors. They play a cardinal role in the functioning of many applications, such as the Internet of Things, smart grids, smart production systems, and smart homes, which ultimately render them paramount instruments in the modern age. Recent advances in WSNs have resulted in the rapid development of sensors. However, WSNs will only able to achieve better execution efficiencies if their energy consumption - owing to limited battery life and difficulty of recharging - can be better controlled. Moreover, signal transmission quality determines WSN performance. Hence, two main concerns - energy consumption and signal transmission quality - should be addressed to improve the performance of WSNs. Thus, a new bi-objective simplified swarm optimization algorithm (bSSO) is proposed by employing the concepts of simple routing, SSO, and crowd distance. The performance and applicability of the proposed bSSO using eight different parameter settings are demonstrated through an experiment involving ten WSN benchmarks ranging from 100 to 1000 sensors. The proposed algorithm is then compared with NSGA-II, which is an algorithm widely used to solve multi-objective problems. The results show that the proposed bSSO can successfully achieve the aim of this work.
引用
收藏
页码:198254 / 198264
页数:11
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