A method for optimal scheduling of cloud service energy consumption in a multi-service coexisting system

Abstract

The invention relates to a cloud service energy consumption optimization scheduling method in a multi-service coexisting system. A dual-objective optimization model for spectrum resource allocation that can simultaneously optimize the energy consumption of multiple cloud services and maximize system throughput is established, and the cloud service is introduced. The upper limit of upload energy, rewrite the minimum target of cloud service upload energy as the constraint condition that the energy is less than a certain threshold, so that the dual-objective optimization problem becomes a single-objective optimization problem, and then through the method of reverse iteration, the optimal energy consumption and The relationship between the channel sets assigned to the current time slot, and through this relationship, the two goals of optimizing system throughput and optimizing cloud service energy are unified on a time scale, and finally through the designed 0‑1 integer programming algorithm Or the Lagrangian dual algorithm is used to allocate channels to maximize the system throughput on the premise of meeting the energy consumption requirements of cloud services.

Description

technical field [0001] The invention relates to a cloud service energy consumption optimization scheduling method in a multi-service coexisting system, and belongs to the technical fields of wireless cloud computing technology and wireless resource optimization. Background technique [0002] The rapid growth of Internet traffic and continuous innovation of applications have promoted the development of mobile cloud computing technology. The wireless cloud service uploads application data to the cloud for processing through the wireless network, which reduces the computing power requirements for mobile terminals and improves business processing efficiency. However, compared with the vigorous development of wireless applications, the insufficient battery capacity of mobile terminals has always been a bottleneck that cannot be broken through. Therefore, how to reduce the energy consumption of terminals when uploading cloud service data has gradually become the focus of attention...

AI Technical Summary

Problems solved by technology

[0004] However, all the existing literatures only focus on the case of a single cloud service in the system, and the upload rate of the cloud service in the actual system is bound to be limited by the spectrum bandwidth occupied by the cloud service in addition to obeying the "energy optimal" scheduling strategy. The bandwidth occupied by a service must be related to other services in the system.

Therefore, it is in line with the actual situation to consider the cloud service scheduling strategy in the scenario of multi-service coexistence. There is no research in this area so far.

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