Local matching dynamics in social networks
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
Biconnecting a network of mobile robots using virtual angular forces
Computer Communications
Local matching dynamics in social networks
Information and Computation
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In most of the wireless sensor and actor network applications, it is desirable to have an autonomous process for positioning the actors in order to eliminate human intervention as much as possible. For this purpose, sensors and actors deployed in an area of interest can collaborate in a distributed manner. Typically, sensors can instruct actors for their positioning in the area by considering the application level interests. This instruction is based on selecting representative sensor locations. One of the most common ways of selecting such representative locations is to cluster the network and determine cluster heads (CHs) as representatives. The actors can then move to such CH locations by talking to nearby sensors/actors. Such movement, however, should be done wisely in order to minimise the movement distance of actors so that their lifetimes can be extended. Nevertheless, this may not be possible since not all the actor and CH locations will be known by each actor. In this paper, we propose an actor-CH location matching algorithm which assigns the actors to appropriate CH locations in a distributed manner with minimised travel distance on actors and message overhead on sensors. We adapt the Gale-Shapley (GS) stable matching algorithm from stable matching theory. In this matching algorithm, actors are regarded as men and CHs are regarded as women. For distributed execution of the algorithm, sub-networks of actors and CHs are determined. Each sub-network elects a leader that performs the matching in the sub-network based on GS algorithm. If there are unmatched actors after this process, either a separate search is used to detect such nodes or leaders talk to each other to share this information so that further matching can be performed. We have evaluated the performance of our approach through simulation and shown that our approach can produce travel distance results that are very close to the brute-force approach with minimal messaging overhead.