Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Article number7387752
Pages (from-to)1795-1805
Journal / PublicationIEEE Transactions on Industrial Informatics
Volume12
Issue number5
Online published20 Jan 2016
Publication statusPublished - Oct 2016
Externally publishedYes

Abstract

Mobile sensor networks (MSNs) are often used for monitoring large areas of interest (AoI) in remote and hostile environments, which can be highly dynamic in nature. Due to the infrastructure cost, MSNs usually consist of a limited number of sensor nodes. In order to cover large AoI, the mobile nodes have to move in an environment while monitoring the area dynamically. MSNs that are controlled by most of the previously proposed dynamic coverage algorithms either lack adaptability to dynamic environments or display poor coverage performances due to considerable overlapping of sensing coverage. As a new class of emergent motion control algorithms for MSNs, antiflocking control algorithms enable MSNs to self-organize in an environment and provide impressive dynamic coverage performances. The antiflocking algorithms are inspired by the solitary behavior of some animals who try to separate from their species in most of daily activities in order to maximize their own gains. In this paper, we propose two distributed antiflocking algorithms for dynamic coverage of MSNs, one for obstacle-free environments and the other for obstacle-dense environments. Both are based on the sensing history and local interactions among sensor nodes.

Research Area(s)

  • Antiflocking, distributed control, dynamic coverage, information maps, mobile sensor networks (MSNs), obstacle avoidance

Citation Format(s)

Distributed Antiflocking Algorithms for Dynamic Coverage of Mobile Sensor Networks. / Ganganath, Nuwan; Cheng, Chi-Tsun; Tse, Chi K.

In: IEEE Transactions on Industrial Informatics, Vol. 12, No. 5, 7387752, 10.2016, p. 1795-1805.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review