Edge Server Deployment Method Based on Response Ratio Priority

Abstract

The edge server deployment method based on the response ratio priority disclosed by the present invention includes initializing the global clock; the current program time slice t n When the time comes: determine the service request; determine multiple edge servers; initialize the edge server; adjust the global clock and clear the service request; update the current service request and form the current request list; traverse all the current edge servers to realize the status of all edge servers Handle updates with the service; t n At each moment, each edge server processes the service request it is currently processing, and at the same time adopts the response ratio priority scheduling method to respond to the newly generated service request in the client object; complete t n After the processing flow of each server at time, return to start the next time slice t n+1 . The scheme of the invention effectively improves the performance of processor scheduling.

Description

technical field [0001] The invention relates to distributed system optimization deployment calculation, in particular to an edge server deployment method based on response ratio priority. Background technique [0002] The advent of 5G networks provides strong support for technologies such as cloud computing, but also brings certain challenges. Among them, the most prominent problems are: the centralization of computing resources in cloud computing has brought about problems such as low response speed, poor scalability, high traffic density, and low security. Therefore, edge computing emerged as the times require. In edge computing, in order to maximize the use of resources and process computing requests as soon as possible, the arrangement and allocation of edge servers is particularly important. Due to the unpredictability of user behavior, how to arrange each edge server at a suitable location, and after the user sends a request, rationally allocate spare computing resour...

AI Technical Summary

Problems solved by technology

[0002] The advent of 5G networks provides strong support for cloud computing and other technologies, but also brings certain challenges

Among them, the most prominent problems are: the centralization of computing resources in cloud computing has brought about problems such as low response speed, poor scalability, high traffic density, and low security. Therefore, edge computing emerged as the times require.

[0004] The existing technical solution adopts a greedy strategy, targets the server with the smallest load in the local area, and expands to the entire service range little by little until all services are processed. Since the load size is used as a reference basis, there still exists High latency ratio and network bandwidth occupation

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