Hierarchical collaborative decision-making intra-network resource scheduling method, system, and storage medium

Abstract

The invention discloses a hierarchical collaborative decision-making intra-network resource scheduling method, a system, and a storage medium. The intra-network resource scheduling method comprises the steps of obtaining a computing power demand interest packet requested by an upstream network node in a computing power network; judging whether the current network node meets the computing power demand of the computing power demand interest packet or not, if yes, providing computing power service for data in the computing power demand interest packet according to a deployed performance function,and if not, providing forwarding service for the computing power demand interest packet. According to the technical scheme, the scheduling decision mechanism of the fine-grained local scheduling layer is optimized by means of global information, so that the utilization rate of resources such as global computing power and storage of the computing power network is improved, and load balancing of resources in the network is realized; besides, through the mode of combining the coarse-grained global scheduling layer and the fine-grained local scheduling layer, the non-end-to-end hierarchical collaborative decision-making intra-network resource scheduling capability is provided, the realization of an efficient and balanced intra-network resource scheduling function from the technical level is facilitated, and the overall performance of the computing power network is also improved.

Description

technical field [0001] The present invention relates to the technical field of network information processing, in particular to a network resource scheduling method, system and storage medium for layered collaborative decision-making. Background technique [0002] The traditional data processing method is to perform specific tasks in the core cloud. However, data processing is performed through the centralized orchestration layer in the cloud computing architecture. This method has a long round-trip delay and cannot meet various new applications (such as VR, automatic driving, etc.) high real-time requirements. With network resources such as computing and storage closer to users, edge computing pushes content and services closer to users, effectively alleviating the problem of high latency in cloud computing architecture. Edge computing has the advantages of low latency, high bandwidth, and proximity to users. The development of edge computing has promoted the integration o...

AI Technical Summary

Problems solved by technology

3) Large-scale scheduling. The current scheduling method has serious limitations when dealing with large-scale resources and tasks. The centralized end-to-end scheduling strategy has problems including too complex search patterns and local problems when solving large-scale scheduling problems. How to solve the large-scale scheduling problem is the key to scheduling strategy design due to the shortcomings of too many optimal solutions

4) Efficient routing addressing, static pre-configuration or routing addressing based on DNS resolution has problems of low efficiency and high overhead, and is not suitable for lightweight computing resources

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