Research On Node Location Technology And Computing Offloading Technology Of Internet Of Things Based On Evolutionary Algorithm

With the rapid development of information science and technology,the Internet of Things(IoT)has gradually spread in various fields of human society and played an important role in the process of social and economic development and social construction.In the IoT where monitoring is the main goal,wireless sensor networks(WSN)are deployed in large quantities to sense and collect information from objects in real time,and then aggregate the information into the IoT data center,then the IoT central control system make various analysis and decision.In the IoT which aims to provide application services,mobile edge computing technology(MEC)has been introduced to solve the problem that device resources are limited and cannot satisfy IoT applications.Devices can offload tasks to edge servers through computing offload technology to reduce latency and energy consumption.In the wireless sensor networks,node location technology is a vital part of deploying wireless sensor networks,and it is also a prerequisite for implementing many functions of wireless sensor networks.However,the currently widely used node positioning technology DVHop(Distance Vector-Hop)algorithm has the disadvantages of low positioning accuracy and unstable effects.Such shortcomings make the function of the wireless sensor network extremely limited.In the mobile edge computing,the computing offload technology can provide more resources for smart terminals to reduce the latency and energy consumption of performing tasks.Unfortunately,the priority between latency and energy consumption is different for different types of tasks and different user needs.How to balance the response latency and energy consumption of tasks becomes a problem that must be considered.In this paper,the main purposes are improving the positioning accuracy of node positioning technology and obtaining a more balanced offloading decision.The main work of this paper is summarized as follows:(1)A new high-precision WSN node localization algorithm DECHDV-Hop(DE and Continuous Hop-count DV-Hop)is proposed.Firstly,this paper analyzes the reason of large distance estimation error in DV-Hop algorithm from principles,and proposes a new method of distance measurement between nodes.Then,we formalize the positioning problem into optimization problem.And solved it by the DE algorithm.The experimental results show that our algorithm is not only better than other algorithms of the same type,but also improves the positioning accuracy by up to 70% compared to the DV-Hop algorithm.(2)The contradiction between latency and energy consumption in the computing offloading technique is solved by the multi-objective optimization algorithm.First,we established an IoT model consisting of mobile intelligent terminals and a mobile edge computing server,taking into account the problem of computing offloading in the case of limited terminal resources;then,the problem is formalized into a multi-objective optimization problem,the purpose is looking for the balance between response latency and energy consumption of the terminal computing tasks;finally,we have improved the NSGA-II algorithm and applied it to the optimization problem.Experiments show that the improved NSGA-II algorithm can effectively find the balance between latency and energy consumption.