Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Computer Science and Information Technologies
Arpita Shah
Charotar University of Science And Technology (CHARUSAT)
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Efficient and scalable multitenant placement approach for in-memory database over supple architecture Arpita Shah; Narendra Patel
Computer Science and Information Technologies Vol 1, No 2: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v1i2.p39-46

Abstract

Of late Multitenant model with in-memory database has become prominent area for research. The paper has used advantages of multitenancy to reduce the cost for hardware, labor and make availability of storage by sharing database memory and file execution. The purpose of this paper is to give overview of proposed Supple architecture for implementing in memory database backend and multitenancy, applicable in public and private cloud settings. Backend in-memory database uses column-oriented approach with dictionary based compression technique. We used dedicated sample benchmark for the workload processing and also adopt the SLA penalty model. In particular, we present two approximation algorithms, multitenant placement (MTP) and best-fit greedy to show the quality of tenant placement. The experimental results show that multi-tenant placement (MTP) algorithm is scalable and efficient in comparison with best fit greedy algorithm over proposed architecture.
Co-Authors Narendra Patel