DESLR: Energy-efficient and secure layered routing based on channel-aware trust model for UASNs

Abstract

Underwater acoustic sensor networks (UASNs) have garnered significant interest and have found widespread applications in smart ocean applications and auxiliary navigation. Nevertheless, UASNs encounter a multitude of challenges due to the constraints of the underwater environment, such as high energy consumption, secure transmission, and dynamic network topology in uncertain conditions. In this paper, we propose an energy-efficient and secure layered routing method (DESLR) for UASNs to enhance energy efficiency and improve transmission reliability. The DESLR establishes a channel-based trust model which considers factors of direct trust and indirect trust to describe the behaviors of nodes. In order to effectively identify malicious nodes, great consideration is given to the state of the acoustic channel’s reliability, as varying channel conditions can significantly impact packet transmission. An improved Ant Colony Optimization Algorithm (ACOA) is introduced to discover energy-efficient and low-latency routing paths by balancing energy consumption and routing distance. Additionally, DESLR utilizes a Layered Clustering method to group nodes into clusters and a two-layer fuzzy logic approach to select cluster heads (CH) that avoid hotspots and ensure uniform energy distribution. Simulation results demonstrate that DESLR can effectively detect defective nodes by analyzing anomalous behaviors and outperforms other related work in terms of energy consumption, average end-to-end delay, and packet loss.