Method and system for hierarchical task offloading in heterogeneous mobile edge computing network

Abstract

Embodiments of the present application relate to the technical field of heterogeneous edge computing networks, and in particular to a design method, system, storage medium, and device for hierarchical task offloading in a heterogeneous mobile edge computing network. The method includes: an edge device, an edge server and a cloud computing center, the edge device judges whether to offload tasks according to the price fed back by the edge server and the energy consumption of local computing, and the edge server judges whether to offload tasks according to the price fed back by the cloud computing center and the local computing power The energy consumption of the edge device determines whether to offload the task, and the cloud computing center adjusts the price according to minimizing the energy consumption of the entire computing network, and repeats the above steps until the offloading strategy of the edge device, the decision Prices and penalties were stable. The method realizes the minimization of energy consumption in the entire computing network in the distributed system through the price and penalty mechanism, effectively reducing the overall energy consumption; the setting of the penalty fee reduces the probability of system congestion.

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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