Research On Charging Strategies For Wireless Rechargeable Sensor Networks

As one of the core technologies in the applications of the Internet of Things,wireless sensor networks have been widely applied in the smart home,industry,agriculture,and other fields.Due to the development of wireless sensor networks,more requirements on their network lifetime and deployment scale emerge.Benefit from the recent breakthrough in wireless power transfer technology,the emergence of wireless rechargeable sensor networks(WRSNs)provides a promising platform for many applications of wireless sensor networks.Generally,two core problems exist in the WRSNs: 1)Conventional methods that charge each sensor node to its full capacity take long time,resulting in a reduction in network survival rate,which may lead to severe consequences.2)Most studies are based on omnidirectional charging strategy which leads to low energy efficiency.Moreover,most works ignore the anisotropic energy receiving property of rechargeable sensors,resulting in energy wastage.To solve the above problems,partial charge is applied to avoid the first aforementioned problem.Nevertheless,partial charge may lead to heavier charging burdens.We mix partial charge and full charge to save more nodes and meanwhile relieve the heavy traveling cost burden.Besides,in order to solve the second problem,we reformulate the energy transfer equation according to the antenna theory.Experimental results validate the anisotropic property.Due to the influence factors of the received energy,we mainly study the sojourn planning problem to reduce the network charging delay while maintaining the network operation.The charging power discretization and merging method are proposed to minimize the network charging delay.Finally,we will perform a series of comparative simulations for different charging strategies under different network and charging architectures.Through various performance comparisons,it is demonstrated that our mixed charging strategy can achieve about 13% higher survival rate compared with full charge,and it can achieve shorter traveling cost compared with partial charge.Besides,it is proved that the discretizing solution can reduce the computational complexity.