Title

Prediction Based Opportunistic Routing For Maritime Search And Rescue Wireless Sensor Network

Keywords

Complex network theory; Maritime search and rescue; Opportunistic routing protocol; Topology control; Wireless sensor network

Abstract

In recent years, maritime and air crashes occur frequently. The existing rescue measures rely only on board satellite communications equipment, which makes it difficult to confirm the accurate positioning information and vital signs of drowning people. Recently, wireless sensor networks (WSN) are introduced to Maritime Search and Rescue (MSR). WSNs feature quick expansion, self-organization, and self-adaptation to the marine environment. However, the constant changing nodes location and link reliability in marine search and rescue WSN makes the routing metrics between nodes highly dynamic. Traditional routing protocols such as AODV that establish a fixed single route based on static nodes information will provide poor packet delivery rate and take no consideration of the limited energy on the irreplaceable WSN nodes. We propose to employ opportunistic routing which can make best use of the broadcast property of radio propagation. The forwarding decisions in opportunistic routing are only based on its neighbor's information. No network-wide flooding is required to establish routes. In order to maintain the latest neighbor information and minimize the energy cost of collecting these information, we propose a light-weight time series based routing metric prediction method to deal with the high communication cost incurred by collecting the latest routing metrics between nodes. Results: Our implementation of opportunistic routing protocol achieved 30% more Packet Delivery Ratio compared to the traditional AODV protocol. Also opportunistic routing protocol with prediction performed slightly better than opportunistic routing protocol without prediction. Our approach generated 90% efficiency where as 60% efficiency was achieved using AODV protocol. In achieving this an additional 3% energy is consumed by the nodes. We feel additional 3% energy consumption to improve delivery greatly by 30% is a good tradeoff.

Publication Date

1-1-2018

Publication Title

Journal of Parallel and Distributed Computing

Volume

111

Number of Pages

56-64

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jpdc.2017.06.021

Socpus ID

85032349025 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85032349025

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