Method and system for unloading layered tasks in heterogeneous mobile edge computing network

Abstract

The embodiment of the invention relates to the technical field of heterogeneous edge computing networks, and in particular relates to a design method and system for layered task unloading in a heterogeneous mobile edge computing network, a storage medium and equipment. The method comprises edge equipment, an edge server and a cloud computing center; the edge equipment judges whether to unload a task or not according to the price fed back by the edge server and the locally calculated energy consumption; the edge server judges whether to unload the task or not according to the price fed back bythe cloud computing center and the locally calculated energy consumption; the cloud computing center adjusts the price according to the minimized energy consumption of the whole computing network; andthe steps are cycled until the unloading strategy of the edge equipment, the decision strategy of the edge server and the price and penalty of the computing resources published by the cloud computingcenter are stable. According to the method, the energy consumption minimization in the whole computing network in the distributed system is realized through a price and penalty mechanism, and the overall energy consumption is effectively reduced; and the penalty rate is set to reduce the probability of system blockage.

Description

technical field [0001] Embodiments of the present application relate to the technical field of heterogeneous edge computing networks, and in particular, relate to a method, system, storage medium, and device for hierarchical task offloading in a heterogeneous mobile edge computing network. Background technique [0002] The rapid development of the Internet of Things has brought us into the post-cloud era, and a large amount of data will be generated in our daily life. IoT applications may require extremely fast response times, privacy of data, and more. If the data generated by the Internet of Things is transmitted to the cloud computing center, the network load will be increased, the network may cause congestion, and there will be a certain delay in data processing. [0003] With the promotion of the Internet of Things and cloud services, a new problem-solving model, edge computing, emerges as the times require, that is, data is generated, processed, and analyzed at the ed...

AI Technical Summary

Problems solved by technology

But the premise of the blocking game is that the competitors are homogeneous, but if the cloud computing center, edge server and edge devices in the network have different energy consumption models, the blocking game cannot be used to achieve energy efficiency in a multi-layer edge computing network. consumption optimization

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