Discrete Mathematics - Topics on domination
A new polynomial-time algorithm for linear programming
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Optimizing the Placement of Internet TAPs in Wireless Neighborhood Networks
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
Optimal base station placement in wireless sensor networks
ACM Transactions on Sensor Networks (TOSN)
Efficient energy balancing aware multiple base station deployment for WSNs
EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
Optimal multi-sink positioning and energy-efficient routing in wireless sensor networks
ICOIN'05 Proceedings of the 2005 international conference on Information Networking: convergence in broadband and mobile networking
On energy provisioning and relay node placement for wireless sensor networks
IEEE Transactions on Wireless Communications
A 2-approximation algorithm for optimal deployment of k base stations in WSNs
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
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In WSNs (wireless sensor networks), sensor nodes are typically battery powered. The number of base stations and their locations have significant impacts on the lifetime of a WSN. We study two multiple base station deployment problems. The first problem is to deploy k static base stations in a WSN such that the lifetime of the WSN is maximised. The second problem is to deploy k mobile base stations in a WSN such that the lifetime of the WSN is maximised. We propose a unified heuristic for both problems. In the special case of one static base station, we propose an optimal, polynomial time algorithm. In the special case of one mobile base station, we present an efficient heuristic. We have simulated our optimal algorithm, our heuristics, and the MinDiff-RE heuristic proposed by Azad and Chockalingam. The simulation results show that our heuristic for a single mobile base station prolongs the lifetime of a WSN by 253% on average compared to our optimal algorithm for a single static base station, and our heuristic for multiple mobile base stations performs 40% better than the MinDiff-RE heuristic on average.