Date of Award


Degree Name

Master of Science


Computer Science

First Advisor



In wireless sensor networks (WSNs), maintaining connectivity with the sink node is a crucial issue to collect data from sensors without any interruption. While sensors are typically deployed in abundance to tolerate possible node failures, a number of such failures within the same region simultaneously may result in losing the connectivity with the sink node which eventually reduces the quality and efficiency of the network operation. Given that WSNs are deployed in inhospitable environments, such multiple node failures are very likely due to storms, volcano eruptions, floods, etc. To recover from these multiple node failures, in this thesis, we first present a local partition detection algorithm which makes the sensors aware of the partitioning in the network. We then utilize this information to recover the paths by exploiting sensor mobility. The idea is to locate the failed nodes by keeping complete routing information from each sensor to the sink node and move some of the sensors to such locations to re-establish the routes with the sink node. When performing the recovery, we make sure that the least number of nodes will be moving so that total movement distance can be minimized to improve the lifetime of the WSN. Our proposed approach depends only on the local information to not only minimize the messaging overhead on the sensors but also to ensure the scalability when large-scale Failures and larger networks are considered. The effectiveness of the proposed route recovery approach is validated through simulation experiments.




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