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.
Just-in-Time Adaptive Algorithm for Optimal Parameter Setting in 802.15.4 WSNs
BRIENZA, SIMONE;DE GUGLIELMO, DOMENICO;ANASTASI, GIUSEPPE
In corso di stampa
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
