Open Access

ARTICLE

AMAD: Adaptive Mapping Approach for Datacenter Networks, an Energy-Friend Resource Allocation Framework via Repeated Leader Follower Game

Ahmad Nahar Quttoum^1,*, Muteb Alshammari²

1 Department of Computer Engineering, Faculty of Engineering, The Hashemite University, Zarqa, 13133, Jordan
2 Department of Information Technology, Faculty of Computing and Information Technology, Northern Border University, Arar, 91431, Saudi Arabia

* Corresponding Author: Ahmad Nahar Quttoum. Email:

Computers, Materials & Continua 2024, 80(3), 4577-4601. https://doi.org/10.32604/cmc.2024.054102

Received 19 May 2024; Accepted 11 August 2024; Issue published 12 September 2024

Abstract

Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling solutions. Resource utilization is a quite challenging process; indeed, clients of CDNs usually tend to exaggerate their true resource requirements when they lease their resources. Service providers are committed to their clients with Service Level Agreements (SLAs). Therefore, any amendment to the resource allocations needs to be approved by the clients first. In this work, we propose deploying a Stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client tenants. Through this, the providers seek to retrieve those leased unused resources from their clients. Cooperation is not expected from the clients, and they may ask high price units to return their extra resources to the provider’s premises. Hence, to motivate cooperation in such a non-cooperative game, as an extension to the Vickery auctions, we developed an incentive-compatible pricing model for the returned resources. Moreover, we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each client. Compared to other benchmark models, the assessment results show that our proposed models provide for timely negotiation schemes, allowing for better resource utilization rates, higher utilities, and grid-friend CDNs.

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Keywords

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