Age Of Information In Wireless Power Transfer Mobile Edge Computing Networks

Mobile edge computing technology is widely regarded as a key technology to realize various visions of next-generation Internet by utilizing computing resources at the edge of the network to provide services to end devices.At the same time,the limited energy supply of end devices limits the performance improvement of the system,and wireless power transfer technology provides a good solution to this problem.Therefore,mobile edge computing with wireless power transfer has become an important research topic.In addition,since information timeliness is very important in the network,a performance metric named as age of information is introduced to measure the freshness of information in the considered system.Through literature research,it is found that existing research mainly focuses on studying the age of information in mobile edge computing networks,and there is a lack of in-depth research on the age of information in joint wireless power transfer-mobile edge computing(WPT-MEC)networks.Based on this,this thesis conducts a study on the age of information in WPT-MEC networks as follows:(1)In this thesis,we study the average age of information in the WPT-MEC network with different wireless power transferring time and offloading strategies.Specifically,the energy transmitter in the network provides energy to the sensor node by wireless power transfer,and using the collected energy,the sensor node can choose local computing strategy,partial offloading strategy,or complete offloading strategy to process the status updates.When the wireless power transferring time is constant,this thesis derives the closedform expressions of the average age of information under the local computing strategy and partial offloading strategy.When the wireless power transferring time is assumed to obey uniform distribution,the closed-form expressions of the average age of information are derived for the local computing strategy and the complete offloading strategy,respectively.The numerical simulation results show that when the wireless power transferring time is constant,a smaller average age of information can be obtained under the partial offloading strategy by setting a suitable offloading ratio.(2)This thesis introduces unmanned aerial vehicle(UAV)into the WPT-MEC networks and conducts research on the age of information in the proposed UAV-assisted WPTMEC network.Specifically,the UAV flies to each ground device,using the carried energy transmitter to perform wireless power transfer for ground devices and the carried mobile edge computing server to assist ground devices in processing status updates.The ground devices can directly process status updates locally using the collected energy or offload them to the mobile edge computing server at the UAV for processing.Based on this,this paper constructs a constrained optimization problem,that is,to minimize the average age of information by optimizing the flight trajectory of the UAV,the power for wireless power transfer,and the offloading decisions of ground devices while satisfying the energy consumption constraint of the UAV.The problem is transformed into a constrained Markov decision process,and an algorithm based on Safe Deep Q-Learning Network is designed.Through extensive simulation,the superiority of the proposed algorithm is verified.