Investigated 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.
In this project, we mainly concentrate on harvesting the energy in WSN. 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 shows the effectiveness of the proposed method.
Keywords: Energy Harvesting, Resource Allocation, Energy Efficiency, Wireless Sensor Networks, WEHSN.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Software & Hardware Requirements:
Software: Matlab 2018a or above
Hardware:
Operating Systems:
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended a full installation of all Math Works products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB