Energy efficient optimal parent selection with Chameleon Swarm algorithm and non-overlapping backoff algorithm based dynamic slot allocation in wireless body area network

• Published in: Wireless networks 2024-05, Vol.30 (4), p.2219-2234
• Main Authors: Sankara Srinivasa Rao, Illapu, Rajalakshmi, N. R.
• Format: Article
• Language: English
• Subjects: Access control; Algorithms; Blood pressure; Body area networks; Communications Engineering; Computer Communication Networks; Controllers; Electrical Engineering; Electrocardiography; Energy consumption; Engineering; Internet of Things; IT in Business; Monitoring; Network latency; Networks; Original Paper; Packet transmission; Performance measurement; Real time; Sensors; Slot allocation; Telemedicine; Wireless networks
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-023-03621-0

Wireless body area networks (WBANs) become prevalent in the realm of medical and non-medical fields with the development of networking, information, and communication technologies. Applications for real-time patient monitoring rapidly create the periodic data. The data may be erratic in applications that are life-critical. As a result, the system requires a trustworthy, low-latency communication method that is also energy efficient. In this circumstance, the fixed time slot assignment leads to poor system performance in medium access control standards. Therefore, an Energy Efficient Optimal Parent Selection with Chameleon Swarm Algorithm and Non-overlapping Backoff algorithm based Dynamic Slot Allocation is proposed in this manuscript for enhancing the efficiency of packet transmission in WBAN using IEEE 802.15.6 standards. Normally, fog-based WBAN involves certain layers: sensor, body controller, central coordinator for real-time patient monitoring scheme. In this, the input data is attained by sensor devices in the sensor layer that gather vital signs of the body, like blood glucose, blood pressure, temperature, electrocardiogram, electroencephalography. Also, body controller layer collects the data from sensor layer and stores in fog layer, which is transmitted to central coordinator layer. Central coordinator layer selects prioritized data using Energy efficient optimal parent selection by utilising Chameleon Swarm Algorithm (EEOPS-CSA). The simulation of the proposed WBAN-EEOPS-CSA-NBDSA technique is activated in Network Simulator-2 and the performance metrics, like end-to-end delay, average energy consumption, latency, packet loss, network lifetime, packet delivery ratio, and overhead is analyzed. From the simulation, the proposed WBAN-EEOPS-CSA-NBDSA method attains 18.82, 25% lower end-to-end delay, 10.53, 18.87% higher packet delivery ratio, 22.22, 43.02% lower packet loss ratio, 30.89, 48.78% lower energy consumption when compared to the existing methods, such as Demand-Based Dynamic Slot Allocation for Effective Super frame Utilization in Wireless Body Area Network (WBAN-DDSA) and A bonded channel in cognitive wireless body area network based on IEEE 802.15. 6 and internet of things respectively.