Energy-Efficient Asynchronous QoS MAC Protocol for Wireless Sensor Networks

• Main Authors: Sarang, S., StojanoviÄ�, G.M., Stankovski, S., Trpovski, Ž., Drieberg, M.
• Format: Article
• Published: Hindawi Limited 2020
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092654473&doi=10.1155%2f2020%2f8860371&partnerID=40&md5=b568ddf795198943d0b35b8c7d0dae77; http://eprints.utp.edu.my/23181/

In recent years, wireless sensor networks (WSNs) have gained significant attention in both industry and academia. In WSNs, each sensor node is normally equipped with a small-size battery with finite capacity. Hence, energy-efficient communication is considered a key factor for the extension of network lifetime. Formerly, a large number of medium access control (MAC) protocols have been proposed to improve energy efficiency to prolong the network lifetime. There are applications that generate different types of data packets and require quality of service (QoS) without any disruption in network operation. Therefore, these applications need an energy-efficient QoS MAC protocol that can support QoS by considering energy efficiency as the primary goal to avoid any failure in the network. This article proposes an energy-efficient asynchronous QoS (AQSen) MAC protocol, called AQSen-MAC. The AQSen-MAC considers different types of data packets and uses two novel techniques: self-adaptation and scheduling to enhance energy efficiency, packet delivery ratio, and network throughput. Furthermore, in the protocol, the receiver adjusts its duty cycle according to the remaining energy to prolong the network operation. Finally, the performance of the AQSen-MAC protocol has been evaluated through detailed simulation using Castalia and compared with MPQ-MAC, PMME-MAC, and QAEE-MAC protocols. The simulation results indicate that the AQSen-MAC protocol significantly reduces the energy consumption at the receiver of up to 13.4, consumption per bit of up to 3 and improves the packet delivery ratio and network throughput of up to 12 in the network. © 2020 Sohail Sarang et al.