Research On Adaptive Supervision Platform For Communication Power Supply And Computer Room Environment Based On Edge Computing

The coordinated development of 5G and edge computing has accelerated the application of Io T technology in many industries.The adaptive supervision platform for Communication Power Supply and Computer Room Environment is a typical Io T application system.It can effectively ensure the efficient and stable operation of the data center computer room.On the one hand,the dynamic environment monitoring platform can collect the energy consumption status of server equipment through various monitoring equipment,and use intelligent scheduling strategies to reasonably control the operating status of various monitoring equipment in the computer room,so that the central computer room can achieve a more energy-saving and environmentally friendly operation;On the other hand,the dynamic environment monitoring platform can also collect and analyze the operation status of various monitoring equipment in the data center computer room in real time,so as to realize the maintenance and management of various monitoring equipment in the data center computer room.In summary,the dynamic environment monitoring platform can not only reduce the operating cost of the data center computer room,but also extend the service life of various monitoring equipment in the data center computer room.At present,the dynamic environment supervision platform can cover 90% of the equipment in the data center computer room,and has a large number of applications in the data center computer room in the fields of communications,power,energy,railway and other industries.However,in the actual application process,the traditional architecture of the dynamic environment supervision platform is not suitable for multi-level business,government and scientific research and other big data centers due to its limitations.Such big data centers are composed of a large number of sub-data centers at multiple levels,which presents the characteristics of geographical dispersion and logical integration.In response to the above problems,this paper adopts the edge computing technology framework,combined with the cloud-native technology system,and proposes a dynamic-loop supervision platform for the cloud-edge-end micro-service architecture,but the existing technical framework is not enough to provide the ability of service adaptation.Service-adaptive orchestration cannot be automatically adjusted in response to changing needs or large changes in the number of sensors.Therefore,this paper also introduces service adaptation technology and its core service orchestration optimization algorithm,which effectively solves the shortcomings of the cloud-edge-terminal dynamic loop supervision platform in service adaptation.Firstly,the cloud-native technology system is used to develop and deploy the dynamic environment supervision platform,and its CI/CD process greatly reduces the pressure on platform administrators.When a new device is connected,it can automatically inject the drive service mirror into the adaptive supervision platform for Communication Power Supply and Computer Room Environment,which increases the scalability of the system.In order to enable the adaptive supervision platform for Communication Power Supply and Computer Room Environment based on edge computing to have better concurrent processing capability,stronger reliability and scalability,and to assist platform administrators in more convenient operation and maintenance.The main research contents of this thesis include:First of all,in order to solve the problem that the traditional architecture of the supervision platform for Communication Power Supply and Computer Room Environment cannot meet the supervision requirements of the new multi-level big data center,this paper designs the dynamic environment supervision platform of the cloudedge-end micro-service architecture based on the cloud-native technology system.CI/CD(Continuous Integration/Continuous Deploy)and other technologies not only greatly reduce the pressure on platform administrators,but also automatically inject driver service images into the dynamic monitoring platform when new devices are connected,increasing the scalability of the system.Secondly,in order to cope with the abnormal situation such as the violent fluctuation of service resource requirements during the supervision process,this paper adds a custom microservice adaptation layer to the supervision platform for Communication Power Supply and Computer Room Environment of the cloud-edgeend microservice architecture,and gives the structure to Implementation details at the technical level.When the business management function triggers the necessary adaptive behavior,the system will monitor and count the deployment situation at that time to make service adaptive processing.The adaptive behavior greatly improves the processing ability of the supervision platform for Communication Power Supply and Computer Room Environment to deal with changes in the service resource demand of edge devices,and increases the reliability of the system.Thirdly,we found that generating an adaptive redeployment scheme is a typical constrained optimization problem.To this end,we introduce a swarm intelligence optimization algorithm to calculate all feasible redeployment schemes by designing an improved ant colony algorithm,and calculate all possible redeployment schemes from the current The time it takes for the deployment scheme to change to the new candidate redeployment scheme.Based on this constraint,the most suitable new redeployment scheme is selected and deployed to support the service instance computing resources and edge server resources required by the management function.The method effectively improves the operation efficiency of the supervision platform for Communication Power Supply and Computer Room Environment and reduces the waste of computing resources.Finally,on the basis of the above content,this thesis implements an adaptive supervision platform for Communication Power Supply and Computer Room Environment based on edge computing.The platform's ability to cope with the needs of large,geographically dispersed data centers,providing an efficient microservice adaptive solution,verifies the reliability of the above.