A Heuristic Self-Adaptive Medium Access Control for Resource-Constrained WBAN Systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Access Année : 2016

A Heuristic Self-Adaptive Medium Access Control for Resource-Constrained WBAN Systems

Résumé

This paper presents a heuristic-based approach to self-adapt and reconfigures the wake-up schedule of the nodes in wireless body area networks (WBANs). A latency-energy-optimized traffic-aware dynamic medium access control protocol is presented. The protocol is based on an adaptive algorithm that allows the sensor nodes to adapt their wake-up and sleep patterns efficiently in static and dynamic traffic variations. The heuristic approach helps to characterize the algorithmic parameters with an objective to investigate the behavior of the convergence patterns of the WBAN nodes in a non-linear system. An open-loop form is developed by keeping the wake-up interval (Iwu) fixed followed by the closed-loop adaptive system which updates Iwu on every wake-up instant. An exhaustive search is conducted for different initial wake-up interval values which show that (on average) the algorithm parameters behave monotonically in open-loop systems, whereas a decaying function in the closed-loop form. Various performance metrics, such as energy consumption, packet delay, packet delivery ratio, and convergence speed (for reaching a steady state), are evaluated. It is observed that the convergence time varies from 8 to 72 s under fixed packet transmission rate, whereas the algorithm re-converges (within 8 s) whenever the transmission rate changes.
Fichier non déposé

Dates et versions

hal-01396104 , version 1 (13-11-2016)

Identifiants

  • HAL Id : hal-01396104 , version 1

Citer

Muhammad Mahtab Alam, Elyes Ben Hamida, Olivier Berder, Olivier Sentieys, Daniel Menard. A Heuristic Self-Adaptive Medium Access Control for Resource-Constrained WBAN Systems. IEEE Access, 2016, 4, pp.1287-1300. ⟨hal-01396104⟩
342 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More