ETXRE: Energy and delay efficient routing metric for RPL protocol and wireless sensor networks

Aiman Nait Abbou*, Jukka Manner

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

59 Lataukset (Pure)


Internet of Things is an emerging paradigm based on interconnecting physical and virtual objects with each other and to the Internet. Most connected things fall into the category of constrained devices, with restricted resources (processing power, memory, and energy). These low-power and lossy networks (LLNs) are known for their instability, high loss rates and low data rates, which makes routing one of the most challenging problems in low-cost communications. A routing protocol for low-power and lossy networks (RPL) is a proactive dynamic routing protocol based on IPv6. This protocol defines an objective function (OF) that utilises a set of metrics to select the best possible path to the destination. Minimum rank hysteresis objective function (MRHOF) and objective function zero (OF0) are the most basic OFs, where the first one selects the path to the sink based on the expected transmission count (ETX) metric, and OF0 is based on the hop count (HC). These two metrics prioritise either brute performance (i.e. ETX) or simplicity (i.e. HC). Therefore, using a single metric with an OF can either limit the performance or have an inefficient impact on load management and energy consumption. To overcome these challenges, a routing metric based on MRHOF OF which takes into consideration the link-based routing metric (i.e. ETX) and node-based metric (i.e. remaining energy) for route selection is provided. Expected transmission count remaining energy (ETXRE) is evaluated through 36 scenarios with different parameters. Preliminary results show that ETXRE outperforms ETX and RE in terms of end-to-end delay by an average of at least 17%, packet delay by 13% and consumes 10% less energy.

Varhainen verkossa julkaisun päivämäärä6 jouluk. 2023
DOI - pysyväislinkit
TilaJulkaistu - jouluk. 2023
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä


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