Cross-Layer Analysis of the End-to-End Delay Distribution in Wireless Sensor Networks

Abstract

Emerging applications of wireless sensor networks (WSNs) require real-time quality-of-service (QoS) guarantees to be provided by the network. Due to the nondeterministic impacts of the wireless channel and queuing mechanisms, probabilistic analysis of QoS is essential. One important metric of QoS in WSNs is the probability distribution of the end-to-end delay. Compared to other widely used delay performance metrics such as the mean delay, delay variance, and worst-case delay, the delay distribution can be used to obtain the probability to meet a specific deadline for QoS-based communication in WSNs. To investigate the end-to-end delay distribution, in this paper, a comprehensive cross-layer analysis framework, which employs a stochastic queueing model in realistic channel environments, is developed. This framework is generic and can be parameterized for a wide variety of MAC protocols and routing protocols. Case studies with the CSMA/CA MAC protocol and an anycast protocol are conducted to illustrate how the developed framework can analytically predict the distribution of the end-to-end delay. Extensive test-bed experiments and simulations are performed to validate the accuracy of the framework for both deterministic and random deployments. Moreover, the effects of various network parameters on the distribution of end-to-end delay are investigated through the developed framework. To the best of our knowledge, this is the first work that provides a generic, probabilistic cross-layer analysis of end-to-end delay in WSNs.