Research on Minimizing Payment Cost of Multiple Cloud Service Provider

Daimi Aafiya¹

Section:Research Paper, Product Type: Isroset-Journal
Vol.7 , Issue.4 , pp.6-13, Aug-2019

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v7i4.613

Online published on Aug 31, 2019

Copyright © Daimi Aafiya . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Todays many businesses are shifting their workloads to cloud storage to save capital costs for building and maintaining hardware infrastructures and avoid the complexity of managing data centers. Cloud computing has become a popular commercial service. The CSP (Cloud Service Provider) provides data storage services in which includes Get and Put function, using this geographically distributed data centers around the world. Selection of different CSPs datacenters and cloud customers facing two challenges, first one is how to allocating data to the datacenters in worldwide to satisfy application Service level objectives (SLO) requirement which includes both data availability and retrieval latency and second is how to allocate reserve resources & data in the datacenters which belongs to different CSP to minimizing payment cost. Find out the solution of these challenges firstly used integer-programming techniques for handles cost minimization problems. Here used three techniques for reducing service latency and payment cost first multicast-based data transferring second coefficient based data reallocation and third is request redirection based congestion and using PPM-C (Prediction by Partial Matching-Cloud) data compression technique, this helps to reduce storage cost and data transfer computing time

Key-Words / Index Term :
Service Level Objectives, Cloud Computing, Resources Reservation, CSP, Payment Cost Minimization, PPM-C compression, and Data Availability

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