FLA-SLA aware cloud collation formation using fuzzy preference relationship multi-decision approach for federated cloud

• Main Authors: Vadla, Pradeep Kumar, Kolla, Bhanu Prakash, Perumal, Thinagaran
• Format: Article
• Language: English
• Published: Universiti Putra Malaysia Press 2020
• Online Access: http://psasir.upm.edu.my/id/eprint/76860/1/07%20JST-1650-2019.pdf; http://psasir.upm.edu.my/id/eprint/76860/; http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2028%20(1)%20Jan.%202020/07%20JST-1650-2019.pdf

Cloud Computing provides a solution to enterprise applications in resolving their services at all level of Software, Platform, and Infrastructure. The current demand of resources for large enterprises and their specific requirement to solve critical issues of services to their clients like avoiding resources contention, vendor lock-in problems and achieving high QoS (Quality of Service) made them move towards the federated cloud. The reliability of the cloud has become a challenge for cloud providers to provide resources at an instance request satisfying all SLA (Service Level Agreement) requirements for different consumer applications. To have better collation among cloud providers, FLA (Federated Level Agreement) are given much importance to get consensus in terms of various KPI’s (Key Performance Indicator’s) of the individual cloud providers. This paper proposes an FLA-SLA Aware Cloud Collation Formation algorithm (FS-ACCF) considering both FLA and SLA as major features affecting the collation formation to satisfy consumer request instantly. In FS-ACCF algorithm, fuzzy preference relationship multi-decision approach was used to validate the preferences among cloud providers for forming collation and gaining maximum profit. Finally, the results of FS-ACCF were compared with S-ACCF (SLA Aware Collation Formation) algorithm for 6 to 10 consecutive requests of cloud consumers with varied VM configurations for different SLA parameters like response time, process time and availability.