Research On Key Technology Of Energy Consumption In Internet Of Things

Since the 1990s,the Internet of Things(IOT)technology has been gradually integrated into our life and work.Wireless sensor nodes monitor the interest area all the time,and access the sensory data through the data center.As sensor node battery capacity is restricted to its volume and other factors,the network is hard to maintain work for a long time.Due to the massive amounts of sensory data,the electric power cost of data center is increasing rapidly.Hence,energy problem becomes an inevitable question of IoT.Currently,the main research in Wireless Sensor Networks(WSNs)is focus on balancing network energy consumption.For data center power management,technology as Dynamic Voltage And Frequency Scaling(D-VFS)is also a primary way to reduce electricity cost.However,as the requirements in network lifetime and electricity cost are increasing,these methods have unable to meet people's needs.This dissertation studied energy problem in two aspects,prolong network lifetime in WSNs and reducing data center electricity cost.For WSNs lifetime problem,this disserta-tion proposed a heterogeneous network node energy consumption scheduling algorithm.This dissertation studied maximizing lifetime of three-dimensional corona-based WSNs,three de-ployment strategies are proposed.Based on the oil pipeline monitoring system,a node energy balance strategy has been proposed.For optimizing data center electricity cost,proposed a workload redistribution scheduling algorithim for step tariff.The main contribution of this thesis can be summarized as follows:(1)This dissertation proposed a Heterogeneous Energy Harvesting uniform distributionWireless Sensor Networks(HEH-WSN)to maximize network lifetime by effective scheduling sensor node status whilst ensuring the coverage rate.Firstly,the issue of how to extend lifetime in HEH-WSN was separated into two simple problems,how to improve renewable energy utilization and how to determine sensor node status.A Heterogeneous Energy Harvesting Scheduling(HEHS)strategy was presented to solve the problems,respectively.For problem 1,HEHS first calculates the threshold value for each EHS.In order to improve renewable energy utilization,EHS has a higher priority to active status than BPS.When the remaining energy of EHS is lower than the threshold value,EHS goes to sleep for recharging energy.For problem 2,HEHS discusses the relationship between number of neighbor node and coverage rate by calculating the area of the overlapping sensor range.Based on HEHS,several judgment rules were concluded to judge node status by number of neighbor node.Our results shown HEHS has a longer network lifetime than similar algorithm developed for finite battery WSNs,and with the increasing of ?,network lifetime extends with a ladder shape.(2)This dissertation studied the life-time maximization problem of a three-dimensional corona based WSNs with uniformly distributed sensor nodes and data transmission workload.We first derived the optimal configuration of the first layer of the corona to maximize the lifetime of the network(doptimal),which is only related to system parameters and a.Then three strategies to configure nodes outside the first layer were proposed:the Equal Energy Strategy(EES)which minimizes the number of hops to transmit data from sensor nodes to the sink;the Optimal Total Energy consumption strategy(OTE)which has the optimal total energy consumption of the whole network;and the Optimal Equal Distance Strategy(OEDS)which is a simple deployment strategy but can reduce the total energy consumption.At last,two principles as the deployment guidelines to optimize the sensor network lifetime were proposed.(3)This dissertation studied how to indefinitely prolong oil pipeline monitoring network lifetime by reasonable selecting Energy Harvesting Device(EHD).Firstly,a general strategy WC-EBS(Worst Case-Energy Balance Strategy)was proposed,which defines WCEC(Worst Case Energy Consumption)as the maximum energy sensor node could expend for oil pipeline monitoring WSNs.When the energy collected by EHD is equal or greater than WCEC,network can have an unlimited lifetime.However,energy harvesting rate is proportional to the price of EHD,WC-EBS will cause high network cost.To reduce network cost,two optimization strategies were presented,OW-EBS(Optimization workload Energy Balance Strategy)and OF-EBS(Optimization first node Energy Balance Strategy).The main idea of OW-EBS is to cut down WCEC by reducing critical node transmission workload;OF-EBS confirms critical node by optimizing each sensor node transmission range,then we get the optimal energy harvesting rate in OF-EBS.The experimental results demonstrate that OFEBS can indefinitely extend network lifetime with lower cost than WC-EBS and OW-EBS,and energy harvesting rate P in each strategy satisfies POF-EBS ? POW-EBSdPWC-EBS.(4)This dissertation proposed an electricity cost model based on step tariff to solve the problem of how to reduce IDC's cost.The formulation of IDC's total cost was abstracted according to different parameters(e.g.power price,carbon emissions).Then an efficient Workload Redistribution Scheduling(WRS)for reducing total electricity cost was proposed.Experimental results show that,comparing with Direct Allocation Scheduling(DAS),WRS can minimize total electricity cost effectively.In summary,this dissertation studied WSNs lifetime issue,covering different network structures(battery powered WSNs,energy harvesting WSNs and heterogeneous WSNs).More-over,this dissertation explored the problem of IDC's high power cost.The results of this thesis serve as theoretical foundations as well as provides practical insights for the energy consump-tion issue of IoT.