Distributed mobile edge computing resource scheduling method and system for delay-sensitive task

Abstract

The invention discloses a distributed mobile edge computing resource scheduling method and system for a delay-sensitive task, and the method comprises the following steps: predicting an access source edge node and a convergence edge node of an edge computing network within the maximum delay of a to-be-processed delay-sensitive task of a vehicle; enabling the control layer to calculate the data transmission cost to other edge nodes in the network from the resource information table by taking the source edge node and the convergence edge node as target nodes; extracting the task processing cost of each edge node from the resource information table, respectively summing the task processing cost and the data transmission cost to obtain the total cost, and putting the edge nodes into a resource queue according to the total cost; and allocating the delay sensitive tasks to be processed to k edge nodes with the lowest total cost in the resource queue for processing, and completing scheduling. According to the method, the edge nodes are sequenced, and the calculation tasks are distributed to the edge nodes, so that the minimization of calculation delay and the minimization of task processing cost can be realized.

Description

technical field [0001] The invention belongs to the technical field of computer communication, and in particular relates to a resource scheduling method and system for distributed mobile edge computing of delay-sensitive tasks. Background technique [0002] The Internet of Vehicles (IoV), which mainly consists of connected vehicles, roadside infrastructure, faces many challenges, mainly due to high mobility, limitations of on-board resources and computing power, etc.; (Quality of Experience, QoE) at the same time, it is difficult to complete computing-intensive applications locally. Only by determining an intelligent computing strategy including data computing and data transmission strategies and deploying them seamlessly can delay-sensitive vehicle services be provided. This requires that computing strategies must consider various factors (network delay, bandwidth, computing power, mobility characteristics, etc.) and provide delay-sensitive in-vehicle services at low cost. ...

AI Technical Summary

Problems solved by technology

However, this existing algorithm does not take into account the hotspot areas in the entire network. If the task request of a local hotspot area is too large, the algorithm needs to be iterated continuously to meet the user's QoE request, and the cost is relatively high.

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