In this paper we performed a tradeoff analysis of energy consumption vs. QoS gain in reliability, timeliness, and security for redundancy management of clustered heterogeneous wireless sensor networks utilizing multipath routing to answer user queries. We developed a novel probability model to analyze the best redundancy level in terms of path redundancy (mp ) and source redundancy (ms ), as well as the best intrusion detection settings in terms of the number of voters (m) and the intrusion invocation interval (TIDS ) under which the lifetime of a heterogeneous wireless sensor network is maximized while satisfying the reliability, timeliness and security requirements of query processing applications in the presence of unreliable wireless communication and malicious nodes. Finally, we applied our analysis results to the design of a dynamic redundancy management algorithm to identify and apply the best design parameter settings at runtime in response to environment changes to prolong the system lifetime. For future work, we plan to explore more extensive malicious attacks in addition to packet dropping and bad mouthing attacks, each with different implications to energy, security and reliability, and investigate intrusion detection and multipath routing based tolerance protocols to react to these attacks. Another direction is to consider smart and insidious attackers which can perform more targeted attacks, capture certain strategic nodes with higher probability, alternate between benign and malicious behavior and collude with other attackers to avoid intrusion detection. Lastly, we plan to investigate the use of trust/reputation management [33], [36], [37] to strengthen intrusion detection through “weighted voting” leveraging knowledge of trust/reputation of neighbor nodes, as well as to tackle the “what paths to use” problem in multipath routing decision making for intrusion tolerance in WSNs. In situations where concurrent query traffic is heavy, we plan to explore trust-based admission control [38]–[40] to optimize application performance.
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