A Hybrid Marine Predator Algorithm for Thermal-aware Routing Scheme in Wireless Body Area Networks

Thermal-aware routing protocols in WBANs consider temperature factors in the routing process for preventing overheating of the tissues surrounding the sensor nodes. However, providing an energy-efficient and thermal-aware routing in WBANs is a challenging issue. To deal with this problem, this article presents a novel temperature-aware routing protocol that applies Mamdani-based Fuzzy Logic Controllers (FLCs) for selecting the next forwarding node in routing data packets. These FLCs apply five important input factors such as the priority of the packet, and sensor node's remaining energy, temperature, distance, and link path loss. Also, a new hybrid version of the Marine Predator Algorithm (MPA), named MPAOA is presented by combining the exploration and exploitation phases of the MPA and Arithmetic Optimization Algorithm (AOA). This algorithm is effectively applied for selecting the best possible set of fuzzy rules for FLCs and tuning their fuzzy sets. Extensive experiments conducted in the Castalia simulator exhibit that the proposed temperature and priority-aware routing scheme can outperform other well-known routing schemes such as LATOR, TTRP, TAEO, ATAR, and EOCC-TARA in terms of metrics such as sensor nodes lifetime, the average temperature of the sensor nodes, and the percentage of the packets routed through non-overheated paths. Besides, it is shown that the MPAOA outperforms other algorithms such as Bat Algorithm (BA), Genetic Algorithm (GA), AOA, and MPA regarding the specified metrics.