Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Dynamic Power Management in Wireless Sensor Networks
IEEE Design & Test
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Optimal information extraction in energy-limited wireless sensor networks
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Stream data gathering in wireless sensor networks within expected lifetime
Proceedings of the 3rd international conference on Mobile multimedia communications
Proceedings of the fifth international workshop on Foundations of mobile computing
Mobile Networks and Applications
Integer Maximum Flow in Wireless Sensor Networks with Energy Constraint
SWAT '08 Proceedings of the 11th Scandinavian workshop on Algorithm Theory
The network balance realized by routing organization system
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Improved approximation algorithms for maximum lifetime problems in wireless networks
Theoretical Computer Science
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We focus on data gathering problems in energy constrained networked sensor systems. The system operates in rounds where a subset of the sensors generate a certain number of data packets during each round. All the data packets need to be transferred to the base station. The goal is to maximize the system lifetime in terms of the number of rounds the system can operate. We show that the above problem reduces to a restricted flow problem with quota constraint, flow conservation requirement, and edge capacity constraint. We further develop a strongly polynomial time algorithm for this problem, which is guaranteed to find an optimal solution. We then study the performance of a distributed shortest path heuristic for the problem. This heuristic is based on self-stabilizing spanning tree construction and shortest path routing methods. In this heuristic, every node determines its sensing activities and data transfers based on locally available information. No global synchronization is needed. Although the heuristic cannot guarantee optimality, simulations show that the heuristic has good average case performance over randomly generated deployment of sensors. We also derive bounds for the worst case performance of the heuristic.