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Wireless Sensor Networks in volatile environments may suffer damage, and connectivity must be restored. The repairing agent must discover surviving nodes and damage to the physical and radio environment as it moves around the sensor field to execute the repair. We compare two approaches, one which re-generates a full plan whenever it discovers new knowledge, and a second which attempts to minimise the required number of new radio nodes. We apply each approach with two different heuristics, one which attempts to minimise the cost of new radio nodes, and one which aims to minimise the travel distance. We conduct extensive simulation-based experiments, varying key parameters, including the level of damage suffered, and comparing directly with the published state-of-the-art. We quantify the relative performance of the different algorithms in achieving their objectives, and also measure the execution times to assess the impact on being able to make autonomous decisions in reasonable time

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Abstract. Wireless Sensor Networks can become partitioned due to node failure or damage, and must be repaired by deploying new sensors, relays or sink nodes to restore some quality of service. We formulate the task as a multi-objective problem over two graphs. The solution specifies additional nodes to reconnect a connectivity graph subject to network path-length constraints, and a path through a mobility graph to visit those locations. The objectives are to minimise both the cost of the additional nodes and the length of the mobility path. We propose two heuristic algorithms which prioritise the different objectives. We evaluate the two algorithms on randomly generated graphs, and compare their solutions to the optimal solutions for the individual objectives. Finally, we assess the total restoration time for different classes of agent, i.e. small robots and larger vehicles, which allows us to trade-off longer computation times for shorter mobility paths.

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Access to the full text of the published version may require a subscription. Abstract-This paper describes our demonstration of a network repair problem where a robot bridges a gap between two disconnected wireless nodes by searching for a good position and moving there to forward data between the two nodes. It serves to show the potential for our published solutions for automated network repair. A simple Adhoc network consists of two Intel Galileo Gen 2 nodes exchanging messages and an NXT Mindstorm robot with another Galileo on board healing the network connection between the two Galileos in the case the two get disconnected. The demo showcases a solution that employs mobile agents to serve as relays to bridge the connectivity gaps in the wireless network. Rights