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Fair Resource Allocation Policies in Reverse Auction-Based Cloud Market

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Abstract

The increasing number of Internet of Things (IoT) applications and their dependence on cloud computing for computational services has resulted in the cloud market’s growth. This growth has attracted many business organizations to offer cloud services, leading to significant competition amongst the cloud service providers. Reverse auction has been widely used to model such competition when there are many cloud service providers. A study on fair resource allocation mechanisms is performed in this work, and a family of such mechanisms is proposed. This work considers a reverse auction-based cloud market where users submit their combinatorial bids. This work emphasizes the importance of fairness in cloud resource allocation and its implementation in a cloud market. The proposed priority-based fair resource allocation mechanisms remove the bidder drop problem in a cloud market where a few major cloud providers dominate and control the whole market. Performance of the proposed fair resource allocation mechanisms is studied based on various metrics such as the number of winning auction rounds, providers’ revenue, users’ procurement cost, etc., in a simulated environment. It is observed that the naïve and not well-established providers in the market also win when fair mechanisms based on priority methods are implemented. They also get a chance to win the auction and can offer the resources successfully to the customer.

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  1. Department of Computer Science and Engineering, Motilal Nehru National Institute of Technology, Allahabad, Prayagraj, UP, 211004, India

    Dinesh Kumar

  2. Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, UP, 221005, India

    Gaurav Baranwal

  3. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, 110067, India

    Deo Prakash Vidyarthi

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  1. Dinesh Kumar
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Kumar, D., Baranwal, G. & Vidyarthi, D.P. Fair Resource Allocation Policies in Reverse Auction-Based Cloud Market. SN COMPUT. SCI. 2, 483 (2021). https://doi.org/10.1007/s42979-021-00907-y

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