A Novel Optimized Resource Allocation Algorithm using GWO Optimization Technique for WBAN

Abstract

Wireless Body Area Networks have severe challenges in energy management to enhance the longevity of the system. Specifically, for a WBAN system that operates by ambient energy sources. The system combines energy scavenging modules integrated into the sensors carried by patients, enabling data transmission to a personal device. Our approach does not rely on previous information as the characteristics of the scavenged and consumed energy are stochastic. To optimize user utility, a formulation of an optimization problem by employing the Grey Wolf Optimization technique (GWO) compared to previous works that used different optimization techniques, to decompose it into three sub-problems: battery management, collecting rate control, and transmission power allocation. To achieve our goals, we apply the GWO to the introduced online resource allocation algorithm that serves two primary purposes: (1) balancing energy scavenging and consumption of network nodes to ensure system stability, and (2) maximizing user utility. Through simulation results, we validate the effectiveness and optimization capabilities of the algorithm while applying a different optimization technique from the previous works maintained.