A Generic Framework for Modeling MAC Protocols in Wireless Sensor Networks

• Published in: IEEE/ACM transactions on networking 2017-06, Vol.25 (3), p.1489-1500
• Main Authors: Ait Aoudia, Faycal, Gautier, Matthieu, Magno, Michele, Berder, Olivier, Benini, Luca
• Format: Article
• Language: English
• Subjects: Access control; Computer Science; Energy consumption; energy efficient communications; Engineering Sciences; Environmental monitoring; Hardware Architecture; IEEE 802.15 Standard; MAC protocols; Markov chains; Markov model; Markov processes; Media Access Protocol; Modelling; Parameters; Reliability; Remote sensors; Signal and Image processing; wake up receivers; Wireless sensor networks
• ISSN: 1063-6692; 1558-2566
• DOI: 10.1109/TNET.2016.2631642

Wireless sensor networks are employed in many applications, such as health care, environmental sensing, and industrial monitoring. An important research issue is the design of efficient medium access control (MAC) protocols, which have an essential role for the reliability, latency, throughput, and energy efficiency of communication, especially as communication is typically one of the most energy consuming tasks. Therefore, analytical models providing a clear understanding of the fundamental limitations of the different MAC schemes, as well as convenient way to investigate their performance and optimize their parameters, are required. In this paper, we propose a generic framework for modeling MAC protocols, which focuses on energy consumption, latency, and reliability. The framework is based on absorbing Markov chains, and can be used to compare different schemes and evaluate new approaches. The different steps required to model a specific MAC using the proposed framework are illustrated through a study case. Moreover, to exemplify how the proposed framework can be used to evaluate new MAC paradigms, evaluation of the novel pure-asynchronous approach, enabled by emerging ultra-low-power wake-up receivers, is done using the proposed framework. Experimental measurements on real hardware were performed to set framework parameters with accurate energy consumption and latency values, to validate the framework, and to support our results.