Joint utility optimization for wireless sensor networks with energy harvesting and cooperation

Abstract

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.

Optimization of the energy efficiency in Smart Internet of Vehicles assisted by MEC

“…Recently, with the evolution from the fifth and beyond fifth generation mobile communication (5G/beyond 5G) [1,2] to the sixth generation mobile communication (6G) [3], some novel technologies, such as mobile edge computing (MEC) [4,5], satellite communication [6] and spatial multiplexing [7], have been proposed to promote the development of wireless sensor network (WSN) [8,9], IoT [10] and other novel applications [11][12][13], so as to realize the interconnection of all things. IoV as a special application of IoT attracts extensive attention in terms of road safety, smart transportation and information service [14].…”

Online Monitoring of Ship Block Construction Equipment Based on the Internet of Things and Public Cloud: Take the Intelligent Tire Frame as an Example

“…Mancuso et al [13] deployed wireless sensor network in the tomato greenhouse, and used RTD module to collect the environmental factors of the tomato in the greenhouse from realizing the microclimate monitoring in the greenhouse. Considering that battery capacity will limit the life of sensor nodes, Zhu et al [14] investigated the joint utility maximization of wireless sensor networks combining energy collection and collaboration. In order to solve the problem of energy-saving data collection in the monitoring system, Li et al [15] proposed a data collection scheme based on the key technology of WSN-noise reduction autoencoder.…”