Self-Organized Hybrid Wireless Sensor Network for Finding Randomly Moving Target in Unknown Environment

TitleSelf-Organized Hybrid Wireless Sensor Network for Finding Randomly Moving Target in Unknown Environment
Publication TypeJournal Article
Year of Publication2018
AuthorsNighot, M., A. Ghatol, and V. Thakare
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueRegular Issue
Volume5
Number1
Date Published06/2018
Pagination16-28
Abstract

Unknown target search, in an unknown environment, is a complex problem in Wireless Sensor Network (WSN). It does not have a linear solution when target’s location and searching space is unknown. For the past few years, many researchers have invented novel techniques for finding a target using either Static Sensor Node (SSN) or Mobile Sensor Node (MSN) in WSN i.e. Hybrid WSN. But there is a lack of research to find a solution using hybrid WSN. In the current research, the problem has been addressed mostly using non-biological techniques. Due to its complexity and having a non-linear solution, Bio-inspired techniques are most suited to solve the problem.
This paper proposes a solution for searching of randomly moving target in unknown area using only Mobile sensor nodes and combination of both Static and Mobile sensor nodes. In proposed technique coverage area is determined and compared. To perform the work, novel algorithms like MSNs Movement Prediction Algorithm (MMPA), Leader Selection Algorithm (LSA), Leader’s Movement Prediction Algorithm (LMPA) and follower algorithm are implemented. Simulation results validate the effectiveness of proposed work. Through the result, it is shown that proposed hybrid WSN approach with less number of sensor nodes (combination of Static and Mobile sensor nodes) finds target faster than only MSN approach.

KeywordsParticle Swarm Optimization, Self-Organization, Target Finding, Wireless Sensor Networks
DOI10.9781/ijimai.2017.09.003
URLhttp://www.ijimai.org/journal/sites/default/files/files/2017/09/ijimai_5_1_2_pdf_19352.pdf
AttachmentSize
ijimai_5_1_2.pdf3.25 MB