Energy efficient wireless body area networks: proximity-based clustering in medical implants

The rapid development in the field of low power circuits and biosensors has created a new area in Wireless Sensor Networks (WSNs), called Wireless Body Area Networks (WBANs). Medical implants are an integral part of a WBAN to measure, monitor, and control various medical conditions. These implants are generally injected inside the human body through an invasive surgical procedure with very limited energy resources available. In case the battery is depleted, the patient potentially needs to go for another surgery to replace the implant. Subsequently, it becomes imperative to propose energy efficient protocols to save energy in the implants. This work proposes a clustering mechanism in medical implants wherein the implants in the immediate proximity form clusters. In particular, the performance of the customized version of Low-Energy Adaptive Clustering Hierarchy (LEACH), modified for the implants' network, is analyzed. The results are compared with the contention-based Medium Access Control (MAC) layer protocol such as pure ALOHA. In addition, a mathematical model to capture the energy consumption details of an implant network is presented. The simulation results demonstrate that a significant amount of energy can be saved using the proposed model. More precisely, the customized LEACH protocol consumes around 10 times less energy as compared to pure ALOHA.