sis 19(22): e4

Research Article

Cloud Services Ranking by measuring Multiple Parameters using AFIS

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  • @ARTICLE{10.4108/eai.13-7-2018.159354,
        author={Sagheer Abbas and Tahir Alyas and Atifa Athar and Muhammad Adnan Khan and Areej Fatima and Waseem Ahmad Khan},
        title={Cloud Services Ranking by measuring Multiple Parameters using AFIS},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={6},
        number={22},
        publisher={EAI},
        journal_a={SIS},
        year={2019},
        month={7},
        keywords={Web Services, Cloud Services, Ranking, AFIS},
        doi={10.4108/eai.13-7-2018.159354}
    }
    
  • Sagheer Abbas
    Tahir Alyas
    Atifa Athar
    Muhammad Adnan Khan
    Areej Fatima
    Waseem Ahmad Khan
    Year: 2019
    Cloud Services Ranking by measuring Multiple Parameters using AFIS
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.159354
Sagheer Abbas1, Tahir Alyas2, Atifa Athar3, Muhammad Adnan Khan1,*, Areej Fatima1,2, Waseem Ahmad Khan1
  • 1: Department of Computer Science, NCBA&E, Lahore, Pakistan
  • 2: Department of Computer Science, Lahore Garrison University, Lahore, Pakistan
  • 3: Department of Computer Science, CUI, Lahore, Pakistan
*Contact email: madnankhan@ncbae.edu.pk

Abstract

Assigning a level to a number of choices is referred to as ranking. The concept of ranking is applied in many situations, wherein, team rankings, player rankings, university rankings, and country rankings are commonly used these days. Similarly, in cloud standardization, ranking the web services is a principal concern, as it is a relatively new approach, assigning ranks to cloud facilities has gained significant attention from researchers across the globe. Furthermore, cloud services standardization is an important idea as it is necessary if it is required to assign ranking for cloud services. There are few limitations in cloud standardization as there is no technique to check valid services and its classifications, wherein, the standardization of cloud services will play a major role in controlling the redundancy of cloud services. In this article, a new cloud service ranking method is proposed using an Adaptive Fuzzy Inference System (AFIS).