Optimising energy in distributed phenomena detection for mobile WSN. (1st February 2020)

• Record Type: Journal Article
• Authors: Abu Safia, Amany; Kamel, Ibrahim; Al Aghbari, Zaher
• Is Part Of: IET wireless sensor systems. Volume 10:Number 1(2020)
• Page Start: 13
• Page End: 22
• Publication Date: 2020-02-01
• Subjects: wireless sensor networks -- mobile radio -- optimisation; global phenomena -- optimisation strategies -- RPP -- short communication path -- wireless sensor network -- slow sensor speed -- distributed phenomena detection -- mobile WSN -- energy‐aware distributed scheme -- mobile sensors -- group heads -- group membership -- geographical boundaries -- battery power overhead -- lazy window update -- reporting by partial participation -- reporting by Z‐order -- RZO -- NS2 network simulator; Wireless sensor networks -- Periodicals; 681.2
• DOI: 10.1049/iet-wss.2018.5161
• Languages: English
• ISSNs: 2043-6386

Abstract

Abstract : We propose an energy‐aware distributed scheme, general phenomena detection, to detect phenomena in data gathered from mobile sensors. In the proposed algorithm, mobile sensors self‐organise themselves into groups and elect group heads (GHs) based on the location of the phenomena. To better share, the extra battery power overhead, GHs and subsequently group membership are updated periodically (every window). Each GH gathers readings from sensors within its group and processes the data to detect possible phenomena within its geographical boundaries. Then, GHs communicate with each other to discover and report global phenomena. To further reduce the energy cost, the study proposes three optimisation strategies: the first strategy, reporting by partial participation (RPP), limits the number of participating GHs in reporting the phenomena. RPP achieved a saving in the energy cost of around 50%. The second strategy, reporting by Z‐order (RZO), provides an overall short communication path between GHs by using Z‐order. RZO achieved a saving of more than 35% of the required energy. The study also proposes a lazy window update strategy that is suitable for a wireless sensor network (WSN) with slow sensor speed. The proposed solutions are validated via comprehensive experiments performed on an NS2 network simulator.