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Issue No. 10 - Oct. (2013 vol. 62)
ISSN: 0018-9340
pp: 1932-1944
Pascal Schweitzer , Institut Mittag-Leffler, Djursholm
Zichuan Xu , Australian National University, Canberra
Weifa Liang , Australian National University, Canberra
ABSTRACT
To deploy a wireless sensor network for the purpose of large-scale monitoring, in this paper, we propose a heterogeneous and hierarchical wireless sensor network architecture. The architecture consists of sensor nodes, gateway nodes, and mobile sinks. The sensors transmit their sensing data to the gateway nodes for temporary storage through multihop relays, while the mobile sinks travel along predetermined trajectories to collect data from nearby gateway nodes. Under this paradigm of data gathering, we formulate a novel constrained optimization problem, namely, the capacitated minimum forest (CMF) problem, for the decision version of which we first show NP-completeness. We then devise approximation algorithms and provide upper bounds for their approximation ratios. We finally evaluate the performance of the proposed algorithms through experimental simulation. In our experiments, the approximation ratio delivered by the proposed algorithms is always less than 2. In the case of arbitrary gateway capacities, this contrasts our theoretical results which show that the approximation ratio is at most linear in the number of gateways. Our experiments thus indicate that for realistic inputs, our worst case analysis of the approximation ratio is very conservative. The proposed algorithms are the first approximation algorithms for the CMF problem, and our techniques may be applicable to other constrained optimization problems beyond wireless sensor networks.
INDEX TERMS
Logic gates, Mobile communication, Approximation methods, Approximation algorithms, Vegetation, Wireless sensor networks, Mobile computing, capacitated minimum forest problem, Wireless sensor networks, sink mobility, data gathering, constrained optimization problem
CITATION
Pascal Schweitzer, Zichuan Xu, Weifa Liang, "Approximation Algorithms for Capacitated Minimum Forest Problems in Wireless Sensor Networks with a Mobile Sink", IEEE Transactions on Computers, vol. 62, no. , pp. 1932-1944, Oct. 2013, doi:10.1109/TC.2012.124
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