Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Computer Methods for Mathematical Computations
Computer Methods for Mathematical Computations
Energy-efficient collision-free medium access control for wireless sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
A bit-map-assisted energy-efficient MAC scheme for wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Linear Programming and Network Flows
Linear Programming and Network Flows
DRAND: distributed randomized TDMA scheduling for wireless ad-hoc networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Z-MAC: a hybrid MAC for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks
IEEE Transactions on Wireless Communications
Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks
IEEE Transactions on Wireless Communications
Proceedings of the 2009 International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly
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This paper studies time division multiple access (TDMA) scheduling with both energy efficiency and optimized delay in clustered wireless sensor networks (WSNs). To achieve this goal, we first build a cross-layer optimization model for attaining network wide efficient energy consumption. We solve this model by transforming it into simpler sub-problems that can be solved using conventional methods. We then propose a TDMA scheduling algorithm based on the input derived from the cross-layer optimization model. The proposed algorithm utilizes the slot reuse concept, which significantly reduces the end-to-end latency in WSNs, while retaining the feature of energy efficiency. In addition, the proposed solution in this paper is applied to clustered WSNs. This feature facilitates the application of our approach in large size WSNs.