| The intelligent coal mines put forward the construction goals of intelligent perception,intelligent decision-making,and automatic execution.As an extension of cloud computing,edge computing can solve the problems of network congestion,high latency,security and privacy in centralized cloud computing.It can provide data computing,storage and network services for coal mining systems at the edge close to terminal equipment.Edge-cloud collaborative work provides computing services to meet different needs for intelligent coal mine systems,improving the real-time and reliability of tasks related to intelligent coal mine systems.Compared with traditional industries,underground coal mines have a wide range of mining areas,a long strip topology roadway structure,many intelligent terminal devices in the system,complex types of data tasks,and high real-time requirements.This feature brings challenges to the research of edge computing.This article aims to improve the real-time performance of task processing in the intelligent coal mine system,reduce the energy consumption of task processing,and achieve load balancing of edge servers.It builds an edge computing framework based on the intelligent coal mine system and researches the deployment of edge servers and task allocation methods in the underground intelligent coal mine system.The main research contents are as follows:1.Deployment method of edge server in intelligent coal mineThe deployment of edge servers in underground coal mine systems is a prerequisite for edge computing.This article researches two aspects:choosing the location of edge servers and associating terminal devices with edge servers.For the edge server placement problem,the k-means clustering algorithm is used to select the edge server placement location.First,according to the distribution of underground intelligent terminal equipment and the characteristics of the underground roadway structure,the clustering.algorithm’s initial clustering centre selection method and distance measurement formula are improved.Then determine the final placement location of the edge server based on the location of the cluster centre,the location where the edge server can place in the roadway,and the number of tasks in each cluster.For the association between edge servers and end devices,the matching degree between devices measure according to the task characteristics of each end device and the distance to each edge server And based on the idea of load balancing,the end devices are associated with the edge servers with low load in the maximum communication delay range in order of matching degree,thus completing the deployment of edge servers.The simulation results show that the deployment strategy of edge servers in the intelligent coal mine proposed in this paper has better performance in a task processing delay and load balancing.2.Task allocation method of edge computing in intelligent coal mineDue to the uncertainty of terminal device tasks in the system,some edge servers are heavily loaded,and delay-sensitive tasks cannot process in time.So,An edge computing strategy based on dynamic priority and real-time bidding is proposed as a computing task allocation method.The method first dynamically generates priority queues according to the importance,urgency,and calculation amount of tasks.Secondly,a real-time bidding model for task assignment is established for the characteristics of the coal mine underground network covering a wide area,and the network in the tunnel has a ribbon topology with a long extension distance.This model determines the edge server’s offer for processing tasks based on four factors:edge server computing power,task processing time,energy consumption and waiting time.Request the server to transfer the task to the 2-hop server within and execute it on the edge server with the lowest price and meet the task requirements,thereby completing the task assignment.The simulation results show that the proposed edge computing task allocation method can effectively reduce the time delay and energy consumption of task processing in intelligent coal mines,improve the utilization of edge computing network resources and the total value of the edge computing layer to complete tasks.Figure[21]Table[3]Reference[62]... |
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