Accurate and Efficient Modeling of 802.15.4 Unslotted CSMA/CA through Event Chains Computation

TL;DR

This paper introduces Event Chains Computation (ECC), a novel method for accurately and efficiently modeling unslotted CSMA/CA in large-scale 802.15.4 WSNs, reducing complexity while maintaining accuracy.

Contribution

The paper presents ECC, a new event chain-based modeling approach that improves accuracy and computational efficiency for large-scale WSN performance analysis.

Findings

ECC reduces computation time significantly with minimal accuracy loss.

Parallel processing with multiple threads speeds up analysis linearly.

Model validation confirms accuracy through simulations and experiments.

Abstract

Many analytical models have been proposed for evaluating the performance of event-driven 802.15.4 Wireless Sensor Networks (WSNs), in Non-Beacon Enabled (NBE) mode. However, existing models do not provide accurate analysis of large-scale WSNs, due to tractability issues and/or simplifying assumptions. In this paper, we propose a new approach called Event Chains Computation (ECC) to model the unslotted CSMA/CA algorithm used for channel access in NBE mode. ECC relies on the idea that outcomes of the CSMA/CA algorithm can be represented as chains of events that subsequently occur in the network. Although ECC can generate all the possible outcomes, it only considers chains with a probability to occur greater than a pre-defined threshold to reduce complexity. Furthermore, ECC parallelizes the computation by managing different chains through different threads. Our results show that, by an appropriate threshold selection, the time to derive performance metrics can be drastically reduced, with negligible impact on accuracy. We also show that the computation time decreases almost linearly with the number of employed threads. We validate our model through simulations and testbed experiments, and use it to investigate the impact of different parameters on the WSN performance, in terms of delivery ratio, latency, and energy consumption.