Abstract

Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the ‘hot spots’ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy and coverage rate etc., it is still very important to schedule a reasonable moving trajectory for the mobile sink. In this paper, a novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs. An improved particle swarm optimization (PSO) combined with mutation operator is introduced to search the parking positions with optimal coverage rate. Then the genetic algorithm (GA) is adopted to schedule the moving trajectory for multiple mobile sinks. Extensive simulations are performed to validate the performance of our proposed method.

Highlights

  • Sink mobility as a significant optimization method has been widely used in different types of routing protocols for wireless sensor networks (WSNs) [Wang, Wu, Tseng et al (2012); Gao, Wang, Wu et al (2019); Wang, Cao, Li et al (2019); Srilakshmi and Sangaiah (2019)]

  • Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring

  • A novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs

Read more

Summary

Introduction

Sink mobility as a significant optimization method has been widely used in different types of routing protocols for wireless sensor networks (WSNs) [Wang, Wu, Tseng et al (2012); Gao, Wang, Wu et al (2019); Wang, Cao, Li et al (2019); Srilakshmi and Sangaiah (2019)]. Sink mobility helps alleviate the limited energy problem of sensors [Ren, Zhang, Zhang et al (2015); Wang, Gao, Liu et al (2019)]. One of the significant problems for the mobile sink technology is the moving trajectory scheduling [Wang, Gao, Liu et al (2019); Pan, Kong, Sung et al (2018); Liu and Zhao (2019); Wang, Gao, Wang et al (2019)]. In rendezvous-based schema, a set of parking positions are firstly selected and the mobile sink only stops at park positions for data gathering.

Related work
System model
Energy model
Coverage problem transformation
Park positions selection using PSO
Network parameters
Comparison of energy consumption
Comparison of network delay
Discussion of coverage and overlapped coverage rate
Findings
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call