1 research outputs found
Just-in-Time Adaptive Algorithm for Optimal Parameter Setting in 802.15.4 WSNs
Recent studies have shown that the IEEE 802.15.4 MAC protocol suffers from severe limitations, in terms
of reliability and energy efficiency, when the CSMA/CA parameter setting is not appropriate. However,
selecting the optimal setting that guarantees the application reliability requirements, with minimum
energy consumption, is not a trivial task in wireless sensor networks, especially when the operating
conditions change over time. In this paper we propose a Just-in-Time LEarning-based Adaptive Parameter
tuning (JIT-LEAP) algorithm that adapts the CSMA/CA parameter setting to the time-varying operating
conditions by also exploiting the past history to find the most appropriate setting for the current
conditions. Following the approach of active adaptive algorithms, the adaptation mechanism of JIT-LEAP
is triggered by a change detection test only when needed (i.e., in response to a change in the operating
conditions). Simulation results show that the proposed algorithm outperforms other similar algorithms,
both in stationary and dynamic scenarios