Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Energy-efficient broadcast and multicast trees in wireless networks
Mobile Networks and Applications
Energy-efficient broadcast and multicast trees in wireless networks
Mobile Networks and Applications
Efficient algorithms for maximum lifetime data gathering and aggregation in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
An adaptive energy-efficient MAC protocol for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Optimal Energy-Efficient Routing for Wireless Sensor Networks
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1
Wireless Communications & Mobile Computing - Advances in Resource-Constrained Device Networking
IEEE Communications Magazine
Performance analysis of the IEEE 802.11 distributed coordination function
IEEE Journal on Selected Areas in Communications
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Well-scheduled communications, in conjunction with the aggregation of data reduce the energy waste on idle listening and redundant transmissions. In addition, the adjustable radii and the number of retransmissions are considered to reduce the energy consumption. Thus, to see that the total energy consumption is minimized, we propose a mathematical model that constructs a data aggregation tree and schedules the activities of all sensors under adjustable radii and collision avoidance conditions. As the data aggregation tree has been proven to be a NP-complete problem, we adopt a LR method to determine a near-optimal solution and furthermore verify whether the proposed LR-based algorithm, LRA, achieves energy efficiency and ensures the latency within a reasonable range. The experiments show the proposed algorithm outperforms other general routing algorithms, such as SPT, CNS, and GIT algorithms. It improves energy conservation, which it does up to 9.1% over GIT. More specifically, it also improves energy conservation up to 65% over scheduling algorithms, such as S-MAC and T-MAC