Fast Approximate Algorithms for Maximum Lifetime Routing in Wireless Ad-hoc Networks
NETWORKING '00 Proceedings of the IFIP-TC6 / European Commission International Conference on Broadband Communications, High Performance Networking, and Performance of Communication Networks
Energy-Efficient Communication Protocol for Wireless Microsensor Networks
HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Impact of Network Density on Data Aggregation in Wireless Sensor Networks
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
The design of an acquisitional query processor for sensor networks
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Information-directed routing in ad hoc sensor networks
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Balancing energy efficiency and quality of aggregate data in sensor networks
The VLDB Journal — The International Journal on Very Large Data Bases
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Sensor networks, consisting of sensor devices equipped with energy-limited batteries, have been widely used for surveillance and monitoring environments. Data collected by the sensor devices needs to be extracted and aggregated for a wide variety of purposes. Due to the serious energy constraint imposed on such a network, it is a great challenge to perform aggregate queries efficiently. This paper considers the aggregate query evaluation in a sensor network database with the objective to prolong the network lifetime. We first propose an algorithm by introducing a node capability concept that balances the residual energy and the energy consumption at each node so that the network lifetime is prolonged. We then present an improved algorithm to reduce the total network energy consumption for a query by allowing group aggregation. We finally evaluate the performance of the two proposed algorithms against the existing algorithms through simulations. The experimental results show that the proposed algorithms outperform the existing algorithms significantly in terms of the network lifetime.