Maximum flow-life curve for a wireless ad hoc network
MobiHoc '01 Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Topology control for wireless sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
Rate allocation in wireless sensor networks with network lifetime requirement
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
On deriving the upper bound of α-lifetime for large sensor networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Capacity bounds for three classes of wireless networks: asymmetric, cluster, and hybrid
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
On the connectivity analysis over large-scale hybrid wireless networks
INFOCOM'10 Proceedings of the 29th conference on Information communications
Data transmission and base-station placement for optimizing network lifetime
Proceedings of the 6th International Workshop on Foundations of Mobile Computing
Evolutionary algorithms for base station placement in mobile networks
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
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Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design (1 -- ε) approximation algorithms for base station placement problems under any desired small error bound ε 0. It offers a general framework to transform infinite search space to a finite-element search space with performance guarantee. We apply this procedure to solve two practical problems. In the first problem where the objective is to maximize network lifetime, an approximation algorithm designed through this procedure offers 1 / ε2 complexity reduction when compared to a state-of-the-art algorithm. This represents the best known result to this problem. In the second problem, we apply the design procedure to address base station placement problem for maximizing network capacity. Our (1 -- ε) approximation algorithm is the first theoretical result on this problem.