The objective of this research study on "Energy Efficient Resource Allocation in Wireless Energy Harvesting Sensor Networks" is to develop novel and optimized resource allocation algorithms and protocols that maximize the energy efficiency and overall system performance of wireless sensor networks powered by energy harvesting techniques.
Extending the sensor life time is one of the most important issues in widespread use of Wireless Sensor Networks (WSNs). The Energy Harvesting (EH) sensors have been proposed to overcome the mentioned problem in recent years. These sensors can harvest their required energy from environment in different methods, resulting in longer life time. We consider a TDMA based Wireless Energy Harvesting Sensor Network (WEHSN) in which the time slot consists of two-time intervals; the first one is utilized to absorb energy whereas the second one is used to transmit the sensors’ data. We investigate the energy efficient resource allocation in WEHSN with constraints on time scheduling parameters and transmission power consumption, where an EH sensor is allowed to transmit its data if the amount of its harvested energy is more than the consumption power. We derive the closed form expression for the optimization problem, corresponding to the energy efficiency and convert it to a parametric form, using Dinkelbach method. Then, we solve the new problem using Karush-Kuhn-Tucker (KKT) conditions. The numerical results show the effectiveness of the proposed method.
Keywords: Energy Harvesting, Resource Allocation, Energy Efficiency, Wireless Sensor Networks
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Software: Matlab 2020a or above
Hardware:
Operating Systems:
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Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
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Recommended: 8 GB
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