Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks
IEEE Transactions on Mobile Computing
An Efficient Tree Structure for Delay Sensitive Data Gathering in Wireless Sensor Networks
AINAW '08 Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops
Query Processing in Sensor Networks
IEEE Pervasive Computing
Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Parallel and Distributed Systems
Balancing Energy Consumption to Maximize Network Lifetime in Data-Gathering Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Tree structure based data gathering for maximum lifetime in wireless sensor networks
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
Energy efficient data gathering in multi-hop hierarchical wireless ad hoc networks
FOMC '11 Proceedings of the 7th ACM ACM SIGACT/SIGMOBILE International Workshop on Foundations of Mobile Computing
Network lifetime maximization for time-sensitive data gathering in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Lifetime Optimization by Load-Balanced and Energy Efficient Tree in Wireless Sensor Networks
Mobile Networks and Applications
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Data gathering is a broad research area in wireless sensor networks. The basic operation in sensor networks is the systematic gathering and transmission of sensed data to a sink for further processing. The lifetime of the network is defined as the time until the first node depletes its energy. A key challenge in data gathering without aggregation is to conserve the energy consumption among nodes so as to maximize the network lifetime. We formalize the problem of tackling the challenge as to construct a min-max-weight spanning tree, in which the bottleneck nodes have the least number of descendants according to their energy. However, the problem is NP-complete. A Ω(log n/log log n)- approximation algorithm MITT is proposed to solve the problem without location information. Simulation results show that MITT can achieve longer network lifetime than existing algorithms.