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Optimization of Managing Resources in Edge-Cloud Networks

Saloni BansalGLA University,Department of Computer Engineering and Applications,Mathura,IndiaAmit MittalGraphic Era Hill University Bhimtal Campus,School of Allied Sciences,Uttarakhand,IndiaMohammed I. HabelalmateenThe Islamic University of Al Diwaniyah,College of Technical Engineering,Department of Computers Techniques Engineering,Al Diwaniyah,IraqSaloni ManhasChandigarh Group of Colleges,Chandigarh Engineering College,Department of Computer Application,Mohali,Punjab,India,140307A. AchilovTashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University,Docent Department of Physics and Chemistry,Tashkent,UzbekistanAlankrita JoshiEngineering Graphic Era Deemed to be University,Department of Electronics & Comm.,Dehradun,India,248002
2024en
ABI

Аннотация

Computer services provided by the cloud and edge may improve performance for mobile devices. Although the cloud is capable of handling large processing demands, the edge's local computing power may help reduce the process' delay. Their cooperation is crucial to edge-cloud computational business models as it has the potential to improve guarantee QoS utilization. This paper proposes an efficient solution that enables computing resources to be exchanged between the cloud and edge in the form of buyback and wholesale. We outline the difficulties in controlling computing resources for the cloud in order to determine wholesale price, the distribution of local resources, and buyback procedures for the process of sharing computer resources.Next, we tackle these issues from two angles:(i)maximizing societal welfare and(ii)maximizing profit for both.We have proposed an ideal and shown the concavity welfare in order to optimize. Since it is challenging to directly show the convexity of the fundamental problem, we first illustrated the attention to the wholesale price for ii). After that, we created the best possible pricing plan and controlled cloud computing resources to maximize their profitability. Numerical evaluations suggest that although maximizing societal welfare may maximize total profit, optimal pricing may maximize individual gains.

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