The Impact of Data Aggregation in Wireless Sensor Networks
ICDCSW '02 Proceedings of the 22nd International Conference on Distributed Computing Systems
Parametric probabilistic sensor network routing
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
A survey of energy-efficient scheduling mechanisms in sensor networks
Mobile Networks and Applications
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks
IEEE Transactions on Mobile Computing
Load balancing over heterogeneous networks with gossip-based algorithms
ACC'09 Proceedings of the 2009 conference on American Control Conference
Minimum Hop Routing Wireless Sensor Networks Based on Ensuring of Data Link Reliability
MSN '09 Proceedings of the 2009 Fifth International Conference on Mobile Ad-hoc and Sensor Networks
Near-lifetime-optimal data collection in wireless sensor networks via spatio-temporal load balancing
ACM Transactions on Sensor Networks (TOSN)
Load balance based on path energy and self-maintenance routing protocol in wireless sensor networks
APNOMS'09 Proceedings of the 12th Asia-Pacific network operations and management conference on Management enabling the future internet for changing business and new computing services
Probability based dynamic load-balancing tree algorithm for wireless sensor networks
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
Optimal data gathering paths and energy balance mechanisms in wireless networks
DCOSS'10 Proceedings of the 6th IEEE international conference on Distributed Computing in Sensor Systems
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Network lifetime maximization is a critical problem for longterm data collection in wireless sensor networks. For large-scale networks, distributed and self-adaptive solutions are highly desired. In this paper, we investigate how to optimize the network lifetime by a localized method. Specifically, the network lifetime maximization problem is converted to a localized cost-balancing problem with an appropriately designed local cost function. A distributed algorithm, LocalWiser, which adopts the idea of adaptive probabilistic routing, is proposed to construct a localized and self-adaptive optimal solution to maximize the network lifetime. We analyze LocalWiser in both static and dynamic networks. In static networks, it is formally proved that 1) LocalWiser can reach a stable status; 2) the stable status is optimal for maximizing the network lifetime. In dynamic networks, our extensive simulations illustrate that LocalWiser can converge to the optimal status rapidly for the network topology and flow dynamics.