An Analytic Model for Cluster-Based Wireless Sensor Networks

Abstract

An analytic model for cluster-based wireless sensor network (WSN) is developed for traffic flow analysis and network performance evaluation in this paper. The traffic flow path is modeled by a number of tandem linked parallel-queues with single-server and finite capacity, where channels of control data and message data are distinguished. Traffic of the tandem-cluster path is analyzed by dividing it into individual clusters. Through development of a stochastic model for this model, the explicit results of several important quality-of-service (QoS) metrics, such as the data blocking probability (DBP), successful data delivery rate (DDR), network throughput, source-to-destination delay (SDD) for both control and message traffic flows, and the network lifetime, of the proposed WSN are derived. A dynamic traffic allocation algorithm aiming to maintain the QoS of the whole WSN and two energy/consumption distribution schemes aiming to optimize the WSN’s energy utilization are further proposed, respectively. The accuracy of the analytic model and QoS evaluation, as well as the effectiveness of the proposed algorithm and schemes are also validated through numerical analysis and simulation.

Keywords:

• Wireless sensor networks
• cluster-based model
• quality of service
• stochastic traffic analysis

Acknowledgements

The authors appreciate the valuable comments from the reviewers and the editor and acknowledge that this research was partially supported by National Science Foundation Grant NSF-1137732 and NSF-1241626. The work of Jinting Wang was partially funded by the National Natural Science Foundation of China (11171019 and 71390334), and Program for New Century Excellent Talents in University (NCET-11-0568)