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Maximizing connected coverage via controlled actor relocation in wireless sensor and actor networks
Affiliation:1. Dept. of Industrial Eng., Bo?aziçi University, 34342 ?stanbul, Turkey;2. Dept. of Computer Eng., Bo?aziçi University, 34342 ?stanbul, Turkey;1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;1. DISC Laboratory, Institut FEMTO-ST, UMR CNRS, Université de Franche-Comté, France;2. LIRIS Laboratory, UMR CNRS, Université de Lyon, F-69003, France;3. Université Claude Bernard Lyon 1, F-69622, France;1. Dept. of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, China;2. Towson University, Towson, MD 21252, USA;3. University of Massachusetts Lowell, Lowell, MA 01854, USA
Abstract:Wireless sensor and actor networks (WSANs) have recently emerged with the idea of combining wireless sensor networks (WSNs) and mobile ad hoc networks (MANETs). In addition to resource constrained sensors, resource rich and mobile actor nodes are employed in WSANs. These actors can collect data from the sensors and perform appropriate actions as a result of processing such data. To perform the actions at all parts of the region in a timely manner, the actors should be deployed in such a way that they might be able to communicate with each other and cover the whole monitored area. This requires that the actors should be placed carefully prior to network operation in order to maximize the coverage and maintain the inter-actor connectivity. In this paper, we propose a distributed actor deployment algorithm that strives to maximize the coverage of actors without violating the connectivity requirement. The approach applies repelling forces between neighboring actors and from the sensors that sit on the boundaries in order to spread them in the region. The spreading of the nodes is done using a tree of actors which can provide more freedom for the movement of the nodes but at the same time maintain the required connectivity among the nodes. We present two techniques for creation of such an actor tree which are based on local pruning of the actor links and spanning tree of the inter-actor network. The performance of our approach is validated both analytically and experimentally.
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