A clique base node scheduling method for wireless sensor networks
Journal of Network and Computer Applications
Optimizing data collection path in sensor networks with mobile elements
International Journal of Automation and Computing
Energy-efficient sensor node control based on sensed data and energy monitoring
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Optimal wake-up scheduling of data gathering trees for wireless sensor networks
Journal of Parallel and Distributed Computing
Delay-bounded and energy-efficient data aggregation
Wireless Communications & Mobile Computing
Systematic selection of cluster heads for data collection
Journal of Network and Computer Applications
Delay-SRLG constrained, backup-shared path protection in WDM networks with sleep scheduling
Computer Communications
EDR: efficient data routing in wireless sensor networks
International Journal of Ad Hoc and Ubiquitous Computing
GMCA: a greedy multilevel clustering algorithm for data gathering in wireless sensor networks
International Journal of Communication Networks and Distributed Systems
International Journal of Communication Networks and Distributed Systems
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A sensor in wireless sensor networks (WSNs) periodically produces data as it monitors its vicinity. The basic operation in such a network is the systematic gathering (with or without in-network aggregation) and transmitting of sensed data to a base station for further processing. A key challenging question in WSNs is to schedule nodes' activities to reduce energy consumption. In this paper, we focus on designing energy-efficient protocols for low-data-rate WSNs, where sensors consume different energy in different radio states (transmitting, receiving, listening, sleeping, and being idle) and also consume energy for state transition. We use TDMA as the MAC layer protocol and schedule the sensor nodes with consecutive time slots at different radio states while reducing the number of state transitions. We prove that the energy consumption by our scheduling for homogeneous network is at most twice of the optimum and the timespan of our scheduling is at most a constant times of the optimum. The energy consumption by our scheduling for heterogeneous network is at most ?? (log Rmax/Rmin) times of the optimum. We also propose effective algorithms to construct data gathering tree such that the energy consumption and the network throughput is within a constant factor of the optimum. Extensive simulation studies show that our algorithms do considerably reduce energy consumption.