In wireless sensor networks (WSNs), the limited battery capacity restricts the lifetime of the sensor nodes and thus degrades the system performance. The energy harvesting and cooperation techniques are promising solutions to prolonging the battery life, by collecting energy from ambient environment and exchanging energy among sensor nodes. This paper studies the joint utility maximization problem for WSNs in consideration of energy harvesting and cooperation. We first derive an upper bound on the Lyapunov drift for the network stability, and then formulate the optimization as a stochastic optimization problem. Furthermore, we propose an energy harvesting and energy transfer, data transmission, power control, routing and scheduling (EDPR) online algorithm by combining Lyapunov optimization technique with drift-plus-penalty method and perturbation technique. It contributes to optimal utility in a distributed manner along with a balanced trade-off between network utility and queue backlog, with no need for any statistical information about dynamic systems and no concern of curse of dimensionality under large queue backlog. Simulation results also show the practicality of the proposed algorithm in real implementation since data transmission has a linear relationship with battery life.
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This work was supported in part by National Science and Technology Major Project of China (Grant No. 2018ZX03001008-002), in part by Natural Science Foundation of Jiangsu Province (Grant No. BK20180011), and in part by National Natural Science Foundation of China (Grant Nos. 61571120, 61871122).
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Zhu, P., Xu, B., Li, J. et al. Joint utility optimization for wireless sensor networks with energy harvesting and cooperation. Sci. China Inf. Sci. 63, 122302 (2020). https://doi.org/10.1007/s11432-019-9936-y
- energy management
- Lyapunov analysis
- utility optimization