Fault tolerant aggregation in heterogeneous sensor networks

Fault tolerance and scalability are important considerations in the design of sensor network applications. Data aggregation is an essential operation in sensor networks. Multiple techniques have been proposed recently to tackle the issues of scalability and fault tolerance of aggregation in sensor networks. In this article, we analyze the impact of using a few of the more reliable, though expensive, nodes–such as the Intel XScale–called microservers, in addition to the standard motes, on the fault tolerance and scalability of the aggregation algorithms in sensor networks. In particular, we propose a simple model that captures the essence of tree aggregation in such heterogeneous sensor networks. We validate this theoretical model with simulation results. We also study the effective impact on the sustainable probability of failure, and perform cost-benefit analysis. We also show how hybrid aggregation can be utilized instead of tree, to improve the performance of aggregation in heterogeneous sensor networks. We show that our work can be applied for effectively optimizing the use of expensive hardware while designing fault-tolerant, distributed sensor networks.