A Void Avoidance Scheme for Grid-Based Multipath Routing in Underwater Wireless Sensor Networks

Thoraya Al- Subhi, Bassel Arafeh, Nasser Alzeidi, Khalid Day, Abderezak Touzene
2018 Wireless Sensor Network  
This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main components, the multipath routing scheme and the grid-based void avoidance (GVA) mechanism for handling routing holes. The multipath routing scheme adopts node-disjoint routes from the source to the sink in order to enhance network reliability and load balancing. While the GVA
more » ... anism handles the problem of holes in 3D virtual grid structure based on three techniques: Hole bypass, path diversion, and path backtracking. The performance evaluation of the VA-GMPR protocol was compared to a recently proposed grid-based routing protocol for UWSNs, called Energy-efficient Multipath Geographic Grid-based Routing (EMGGR). The results showed that the VA-GMPR protocol outperformed the EMGGR protocol in terms of packet delivery ratio, and end-to end-delay. However, the results also showed that the VA-GMPR protocol exhibited higher energy consumption compared to EMGGR. 132 Wireless Sensor Network of the world's population is found within 100 Km of the coastal areas [1]. The oceans, seas and rivers have not been only a major way of transportation throughout the history of human-kind, but they have been also a major supply of nourishment and natural resources (e.g., oil and gas). It is considered that less than 10% of the whole oceans' volume has been explored. The traditional methods for discovering the unexplored underwater regions are not suitable and feasible to human presence, due to the harsh underwater environment. Therefore, unmanned techniques are becoming vital to the exploration of deep-sea regions, such as using Autonomous Underwater Vehicles (AUVs) [2] , and under-
doi:10.4236/wsn.2018.107008 fatcat:7ndif4inrja6beinwj4l5mjjt4