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Scalable Profit Optimized Incentive Mechanism for Resources in Cloudlet Based Mobile Edge Computing Framework

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Abstract

Cloud Computing is the origin for various distributed computing such as mobile cloud computing, mobile edge computing, fog computing, transparent computing etc. The proposed work focuses mainly on mobile cloud computing and mobile edge computing. It discusses various frameworks to execute these computing and pricing models suitable to be incorporated with mentioned computing environments. One such mobile cloud computing framework is scalable key parameter yield of resources (SKYR) framework, which is a cloudlet-based computing framework. In this computing framework, cloudlet is the main computing component which provides the cloud-based services at the local level in the vicinity of the mobile users. This SKYR framework lacks intrinsic pricing module and utility efficiency module. The proposed work facilitates SKYR framework with mentioned modules and hence improves its performance to great extent as shown in the result section. The paper also discusses pricing model which facilitates profit maximization and auction theory for resource providers and users. Latest theoretical profit maximization incentive mechanism (PMIM) pricing model is improved in this proposed work to scalable profit optimized incentive mechanism for resources pricing model. The proposed pricing model addresses the drawbacks of the PMIM. The utility module discusses about the utility efficiency calculation mechanism which helps to analyse the performance of cloudlets and judges the satisfaction level of cloudlets which act as resource provider and mobile users.

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  1. Department of CSE, NITTTR, Chandigarh (U.T), India

    Santosh Kumar Yadav

  2. Department of CSE, Central University of Haryana, Mahendragarh, Haryana, India

    Rakesh Kumar

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  1. Santosh Kumar Yadav
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Yadav, S.K., Kumar, R. Scalable Profit Optimized Incentive Mechanism for Resources in Cloudlet Based Mobile Edge Computing Framework. Wireless Pers Commun 125, 159–207 (2022). https://doi.org/10.1007/s11277-022-09546-9

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