Using mobile data collectors to federate clusters of disjoint sensor network segments

Wireless Sensor Networks (WSN) operating unattended in harsh environments have the higher probability of suffering from large scale damage, where many nodes fail simultaneously and the network gets partitioned into several disjoint segments. Restoring connectivity of structurally damaged WSN's segments may be very urgent considering that they are employed to assist in risky missions. A similar scenario is when multiple standalone networks are to be federated to serve an emerging event such as an earthquake and conduct search-and-rescue. To deal with these scenarios, Mobile Data Mules (MDMs) are employed to establish intermittent links by moving around and carrying data from one segment to another. To limit data delivery latency and minimize the motion overhead, the travel path of the MDM should be shortened. When the availability of MDMs is not an issue, a minimum spanning tree of the segment is formed and one MDM is assigned to serve each link on the tree, i.e., a total of (N-1) mules are involved where N is the number of segments. In this thesis, we study a constrained version of the federation problem when the number of MDM's "k" is less than (N-1), which makes the problem more challenging. We present a novel algorithm that groups the segments into k overlapping clusters based on the inter-segment proximity. Each cluster is assigned a distinct MDM to tour its segments. A segment that belongs to two clusters serves as a gateway that enables data transfer across clusters. Our algorithm minimizes the tour length for each MDM and sets the speed of the individual MDMs to rendezvous at the gateway nodes so that buffering space and time for inter-cluster traffic are minimized. The simulation results confirm the effectiveness of our algorithm.