I PATH:I PATH INFERENCE IN WIRELESS SENSOR NETWORKS

Abstract

Recent wireless sensor networks (WSNs) are be-coming increasingly complex with
the growing network scale and the dynamic nature of wireless communications. Many
measurement and diagnostic approaches depend on per-packet routing paths for accurate and finegrained
analysis of the complex net-work behaviours. In this paper, we propose iPath, a novel
path inference approach to reconstructing the per-packet routing paths in dynamic and large-scale
networks. The basic idea of iPath is to exploit high path similarity to iteratively infer long paths
from short ones. IPath starts with an initial known set of paths and performs path inference
iteratively. iPath includes a novel design of a lightweight hash function for verification of the
inferred paths. In order to further improve the inference capability as well as the execution
efficiency, iPath includes a fast bootstrapping algorithm to reconstruct the initial set of paths. We
also implement iPath and evaluate its performance using traces from large- scale WSN
deployments as well as extensive simulations. Results show that iPath achieves much higher
reconstruction ratios under different network settings compared to other state-of- the-art
approaches.