Intent-based resource matching strategy in cloud

He, Li; Qian, Zhicheng

doi:10.1016/j.ins.2020.05.045

Cited by 16 publications

(2 citation statements)

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“…Based on semantic similarity, Yuan et al [11] proposed a manufacturing resource-matching mechanism for cloud manufacturing platforms. He and Qian [12] proposed a resource matching strategy based on multi-attribute matching between cloud resources and tasks. Xiong et al [13] proposed a fair matching framework for P2P shared accommodation platforms based on preference consistency and resource compatibility.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation of Impact of Resource Competition on Shared Resource Utilisation

Deng¹,

Chen²

2022

Int. j. simul. model.

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This study aims to address the problem that the uncontrolled business response process of resourcematching platforms (RMPs), which leads to resource competition. The system dynamics (SD) is applied to obtain optimisation policy of the platform's resource utilisation from a production system. The business transaction system of RMPs is considered as a complex social and economic system. Then the SD simulation model of the business response process of RMPs is established, for which the success rate of demander response and resource utilisation are used as observation indices. Simulations of influencing factors were conducted from the perspective of platform controllability. It is indicated that the decision attributes especially the expected profit and the resource distribution have impacts on the user response, transaction success rate and the resource utilisation; and the influence of decision distribution is more obvious than that of decision attributes. An improvement in each of these factors can promote the response success rate and resource utilisation. These conclusions provide guidance for the coordination of resource competition and resource scheduling of the platforms.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation of Impact of Resource Competition on Shared Resource Utilisation

Deng¹,

Chen²

2022

Int. j. simul. model.

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“…In [18], the authors have focused on the task to match between cloud resources and processing tasks in accordance with multiple attributes as well as treats the interests of both provider and the user fairly. They have proposed an intent-based resource matching strategy in cloud that is aimed to improve the accuracy and efficiency of matching and overall satisfaction of both parties.…”

Section: Academic Activitiesmentioning

confidence: 99%

Intent-driven cloud resource design framework to meet cloud performance requirements and its application to a cloud-sensor system

Wu¹,

Horiuchi²,

Murase³

et al. 2021

J Cloud Comp

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In cloud service delivery, the cloud user is concerned about “what” function and performance the cloud service could provide, while the cloud provider is concerned about “how” to design proper underlying cloud resources to meet the cloud user’s requirements. We take the cloud user’s requirement as intent and aim to translate the intent autonomously into cloud resource decisions. In recent years, intent-driven management has been a widely spread management concept which aims to close the gap between the operator’s high-level requirements and the underlying infrastructure configuration complexity. Intent-driven management has drawn attention from telecommunication industries, standards organizations, the open source software community and academic research. There are various application of intent-driven management which are being studied and implemented, including intent-driven Software Defined Network (SDN), intent-driven wireless network configuration, etc. However, application of intent-driven management into the cloud domain, especially the translation of cloud performance-related intent into the amount of cloud resource, has not been addressed by existing studies. In this work, we have proposed an Intent-based Cloud Service Management (ICSM) framework, and focused on realizing the RDF (Resource Design Function) to translate cloud performance-related intent into concrete cloud computation resource amount settings that are able to meet the intended performance requirement. Furthermore, we have also proposed an intent breach prevention mechanism, P-mode, which is essential for commercial cloud service delivery. We have validated the proposals in a sensor-cloud system, designed to meet the user’s intent to process a large quantity of images collected by the sensors in a restricted time interval. The validation results show that the framework achieved 88.93 ~ 90.63% precision for performance inference, and exceeds the conventional resource approach in the aspects of human cost, time cost and design results. Furthermore, the intent breach prevention mechanism P-mode significantly reduced the breach risk, at the same time keeping a high level of precision.

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