Research Article
Design of an Efficient Trustful-Lightweight Cloud Service Provisioning Model using Service Optimizer
@ARTICLE{10.4108/eai.19-10-2021.171468, author={Suvarna S. Pawar and Y. Prasanth}, title={Design of an Efficient Trustful-Lightweight Cloud Service Provisioning Model using Service Optimizer}, journal={EAI Endorsed Transactions on Cloud Systems: Online First}, volume={}, number={}, publisher={EAI}, journal_a={CS}, year={2021}, month={10}, keywords={Cloud services, QoS, trust-aware model, Service Optimizer, Trustful Lightweight Cloud Service provisioning, weighted coefficients}, doi={10.4108/eai.19-10-2021.171468} }- Suvarna S. Pawar
Y. Prasanth
Year: 2021
Design of an Efficient Trustful-Lightweight Cloud Service Provisioning Model using Service Optimizer
CS
EAI
DOI: 10.4108/eai.19-10-2021.171468
Abstract
INTRODUCTION: The establishment of trusted cloud services pretends to provide high impactful service with better satisfaction to the web-users and cloud service providers. Moreover, various existing trust-aware algorithms use diverse QoS measurements and related attributes, leading to the complex selection of cloud services.
OBJECTIVES: Thus, this research intends to propose a Trustful-Lightweight Cloud Service Provisioning algorithm (TL-CSP) using Service Optimizer (SO).
METHODS: Initially, the QoS metrics are determined by evaluating attributes based on a ranking method based on the users' requests. It is performed with the computation of weighted coefficients of received requests from the users. The service optimization is performed using a global optimizer to assist the cloud users in selecting the service with better satisfaction.
RESULTS: The proposed TL-CSP accuracy is validated and compared with the existing cloud service provisioning algorithm to measure the proposed model's efficiency.
CONCLUSION: The simulation is carried out in a MATLAB environment. The proposed TL-CSP intends to shows a better trade-off in contrast to prevailing approaches.
Copyright © 2021 Suvarna S. Pawar et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.