Stochastic Modeling of Delay, Energy Consumption, and Lifetime

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 non-deterministic impacts of the wireless channel and queuing state, probabilistic analysis of QoS is essential. For most WSNs applications, the end-to-end delay for packet delivery and the energy consumption are the most important QoS metrics. In this chapter, a comprehensive cross-layer probabilistic analysis framework is presented to investigate the probabilistic evaluation of QoS performance provided by WSNs. In particular, the QoS performance is evaluated in two levels. In the node level, using a Discrete-Time Markov queueing model, the distribution of single-hop delay and single-node energy consumption and lifetime are analyzed. In the network level, based on the node level analysis, the distributions of end-to-end delay, the network lifetime, and the event detection delay are then analyzed. Fluid models are utilized in the network level analysis. The framework also considers a realistic channel environments. Compared to the first-order QoS statistics, such as the mean and the variance, the distribution of QoS metrics reveals the relationship between the performance and reliability with QoS-based operations in WSNs. Using the framework, effective network development can be performed.