| In global digitization,Internet of Things(IoT)technology has become the core technology that it leads the development of the worldwide digital economy.With the rapid development and implementation of IoT,the number of IoT Devices(IoTDs)in the world has shown a blowout growth.It has been predicted that by 2030,the number of IoTDs will reach 75.44 billion.In the era of digitalization,IoTDs are widely used in emerging fields(such as modern agriculture,smart city and smart logistics).However,the residual energy of the battery is the key factor for keeping an IoTD working properly.There are a large number of IoTDs deployed in mountains,forests,uninhabited areas and modern cities,the traditional wired charging and the replacement of the rechargeable battery for IoTDs waste tremendous manpower and material resources.At the same time,the traditional charging method also has certain risks and hidden dangers.At present,IoTDs will become the largest energy consumer of information and communication,there are four main methods to solve the energy issue of IoTDs,e.g.,energy saving,battery replacement,energy harvesting and wireless power transmission.Wireless power transmission for IoTDs is becoming the most promising energy solution for IoTDs in recent years.In this thesis,the technical solution of far-field wireless charging is used to charge the remote IoTDs.The far-field wireless charging method generally uses electromagnetic radiation technology to provide energy supplement for IoTDs.The charging distance between the transmitter and the receiver is more than 90 cm.In order to save grid power,the thesis uses the Green Static Base Station(GSBS)as the transmitter.GSBSs can harvest the green energy by the solar panels and wind generators,and GSBSs can use multiple input and multiple output(MIMO)technology to beam green energy to the receivers.In the far-field wireless charging process,the wireless energy loss will increase with the increase of the propagation distance;according to the distance between the GSBSs and IoTDs,this thesis first determines the ownership of IoTDs,that is,IoTD-GSBS association.In each IoTD-GSBS association,IoTDs have different distribution density and categories.After that,according to the energy consumption and energy required of IoTDs,this thesis classify the IoTDs in each IoTD-GSBS,i.e.,security equipment,monitoring equipment,public equipment,entertainment equipment and other equipment.For each category,we propose the dual-threshold charging model to reduce the percentage of the required energy of IoTDs,i.e.,the alarming threshold and the working threshold.Then,we propose the Dual-Threshold Orderly Charging(DTOC)based on the dual-threshold charging model to efficiently charge the surrounding IoTDs.For each IoTD-GSBS association,in the charging sequence,some IoTDs will be died because of the long waiting time of IoTDs or the short residual lifetime(its high working power).Moreover,the location of GSBSs is relatively fixed.A amount of energy loss may be incurred when the GSBSs wirelessly charge remote IoTDs.Therefore,in order to reduce the mortality of IoTDs during the charging cycle,the standard charging time and the average charging time of IoTDs were defined in the thesis to reduce the waiting time of IoTDs according to the residual lifetime and the charging time of IoTDs.In each association,according to the average charging time and the waiting time of IoTDs,we can get the IoTDs that have not completed charging tasks.Then,this thesis uses the Mobile Base Station(MBS)to charge the IoTDs.The size of the MBSs is limited,that is,the battery capacity is small.Therefore,we select the IoTDs with the smallest standard charging time from each IoTD-GSBS,and then the IoTDs can form a new charging sequence.According to the charging time,remaining lifetime and waiting time of IoTDs,the MBSs can plan the traveling path.Finally,we propose the Jointing Charging of Multiple GSBS and Multiple MBS(MSMS)algorithm.Thus,in a certain charging cycle,the IoTDs have the minimum mortality. |
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