In case of a disaster, the communication infrastructure may be partially or totally destroyed, or scarce because of the high data traffic. Even so, it is necessary to provide connectivity between the rescue teams and the command center. Therefore, temporary communication solutions are crucial until the infrastructure is restored. In this thesis, we focus on the deployment of a communication solution in such a context called substitution networks. Thus, we propose a self-deployment algorithm to allow mobile routers that compose a substitution network to be spread out to cover the target area. Our algorithm monitors the network conditions to decide whether the router should move or not, adjusting its position based on one-hop information by means of active measurement, i.e., probe packets. Such probe packets allow the algorithm to monitor the channel and its eventual changes over time. If the probe transmission rate is high enough, the insights obtained will be accurate, however, the overhead will increase proportionally consuming network resources. Hence, we propose to use surrogate data obtained by means of an autoregressive estimator to reduce the overhead without impacting our deployment algorithm. We show by simulation the efficiency of both algorithms and their performance in terms of deployment time, delay, jitter, and throughput.
Adaptive self-deployment algorithms for mobile wireless substitution networks