An Improved Expectation-Based Multi-attribute Multi-hop Routing (IEM2 R) in Underwater Acoustic Sensor Networks

Abstract

Underwater Acoustic Sensor Networks (UASNs) uses acoustic signals as a physical layer medium for communication underwater. The distinct characteristics of acoustic communication channel make reliable routing a challenging task in underwater applications. To handle this, an Expectation-Based Multi-Attribute Multi-Hop Routing (EM R) was proposed, which selects the best next-hop using an expectations-based multi-attribute ranking based on multiple attributes that are node’s residual energy and distance. However, in EM R node mobility was not considered, which is inevitable underwater. Also, fetching the attributes incurs communication overhead and is prone to attacks. Further, it is crucial to optimize the timing of executing expectation-based multi-attribute ranking in deciding the best next hop. To address these issues, this paper proposes an extension to the previous work called an Improved Expectation-Based Multi-Attribute Multi-Hop Routing (IEM R). The IEM R introduces node mobility and implements a prediction model which uses distance and predicted energy as attributes and predicts the best next hop. The proposed method implemented in the industry standard underwater network simulator UnetStack3 is described. Additionally, results show the predicted and actual next-hop selection, energy depletion, average end-to-end delay, and throughput. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.