TY - GEN
T1 - Energy efficient wireless body area networks: proximity-based clustering in medical implants
AU - Usman, Muhammad
AU - Qaraqe, Marwa
AU - Asghar, Muhammad Rizwan
AU - Ansari, Imran Shafique
PY - 2021/1/11
Y1 - 2021/1/11
N2 - 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.
AB - 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.
KW - wireless body area networks (WBANs)
KW - medical implants
KW - energy efficiency
KW - clustering
KW - wireless sensor networks (WSNs)
KW - medium access control (MAC)
KW - remote healthcare
KW - Wireless Sensor Networks (WSNs)
KW - Wireless Body Area Networks (WBANs)
KW - Clustering
KW - Medical implants
KW - Medium Access Control (MAC)
KW - Energy efficiency
KW - Remote healthcare
U2 - 10.1109/ComNet47917.2020.9306075
DO - 10.1109/ComNet47917.2020.9306075
M3 - Conference contribution
SN - 9781728153216
BT - 2020 IEEE Eighth International Conference on Communications and Networking (ComNet)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Eighth International Conference on Communications and Networking
Y2 - 27 October 2020 through 30 October 2020
ER -