Adaptive correctness monitoring for wireless sensor networks using hierarchical distributed run-time invariant checking

  • Authors:

  • Douglas Herbert;Vinaitheerthan Sundaram;Yung-Hsiang Lu;Saurabh Bagchi;Zhiyuan Li

  • Affiliations:

  • Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN;Purdue University, West Lafayette, IN

  • Venue:
  • ACM Transactions on Autonomous and Adaptive Systems (TAAS)
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

This article presents a hierarchical approach for detecting faults in wireless sensor networks (WSNs) after they have been deployed. The developers of WSNs can specify “invariants” that must be satisfied by the WSNs. We present a framework, Hierarchical SEnsor Network Debugging (H-SEND), for lightweight checking of invariants. H-SEND is able to detect a large class of faults in data-gathering WSNs, and leverages the existing message flow in the network by buffering and piggybacking messages. H-SEND checks as closely to the source of a fault as possible, pinpointing the fault quickly and efficiently in terms of additional network traffic. Therefore, H-SEND is suited to bandwidth or communication energy constrained networks. A specification expression is provided for specifying invariants so that a protocol developer can write behavioral level invariants. We hypothesize that data from sensor nodes does not change dramatically, but rather changes gradually over time. We extend our framework for the invariants that includes values determined at run-time in order to detect data trends. The value range can be based on information local to a single node or the surrounding nodes' values. Using our system, developers can write invariants to detect data trends without prior knowledge of correct values. Automatic value detection can be used to detect anomalies that cannot be detected in existing WSNs. To demonstrate the benefits of run-time range detection and fault checking, we construct a prototype WSN using CO2 and temperature sensors coupled to Mica2 motes. We show that our method can detect sudden changes of the environments with little overhead in communication, computation, and storage.