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A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers

Shashi Kant Gupta1 , Mohammadi Akheela Khanum2

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-2 , Page no. 469-476, Feb-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i2.469476

Online published on Feb 28, 2019

Copyright © Shashi Kant Gupta, Mohammadi Akheela Khanum . 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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IEEE Style Citation: Shashi Kant Gupta, Mohammadi Akheela Khanum, “A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.469-476, 2019.

MLA Style Citation: Shashi Kant Gupta, Mohammadi Akheela Khanum "A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers." International Journal of Computer Sciences and Engineering 7.2 (2019): 469-476.

APA Style Citation: Shashi Kant Gupta, Mohammadi Akheela Khanum, (2019). A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers. International Journal of Computer Sciences and Engineering, 7(2), 469-476.

BibTex Style Citation:
@article{Gupta_2019,
author = {Shashi Kant Gupta, Mohammadi Akheela Khanum},
title = {A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {7},
Issue = {2},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {469-476},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3689},
doi = {https://doi.org/10.26438/ijcse/v7i2.469476}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.469476}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3689
TI - A Review: Distributed Auction-Based Framework v/s Cluster-Based Framework for Auto Scalable IaaS Provisioning in Geo-Data Centers
T2 - International Journal of Computer Sciences and Engineering
AU - Shashi Kant Gupta, Mohammadi Akheela Khanum
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 469-476
IS - 2
VL - 7
SN - 2347-2693
ER -

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Abstract

This research paper proposes a cluster-based framework for Infrastructure-as-a-Service (IAAS) which enables customers effectively hosted intensified performance computing applications and cloud service providers (CSP’s) to use their resources beneficially. The solution incorporates the cluster-based framework which handles the geographical data centers grouped logically in clusters. This cluster-based framework overcomes the challenges of traditional centralized provisioning approaches. A. Efficient on-demand IaaS provisioning. B. Auto-scaling of increasing number of IaaS requests. C. Effectively use of Geographical Data center computing resources. D. Maintain Quality of Service parameter requirements for different IaaS requests. Incorporate Vickrey-Clarke-Groves (VCG) mechanism to solve exaggeration and collusion issues. The solution generated extended to host cloud applications based on mobile and how effectively it will work in a changeable environment. To pace the performance of the distributed IaaS framework vs (RCG-IaaS) regional IaaS provisioning model based on an efficient decomposition technique, Column generation as a large scale optimization tool, I use the additional performance metrics as follows: Basic Performance metric: Speedup (Su): Speed gain of using more processing nodes over a single node, Efficiency (E): Percentage of maximum performance (speedup or utilization) achievable (%), Elasticity (El): Dynamic interval of auto-scaling resources with workload variation & Cloud Productivity: QoS of Cloud (QoS): The satisfaction rate of a cloud service or benchmark testing (%), Service Cost (Cost): The price per cloud service (Compute, Storage etc.) provided ($/hour), Availability (A): Percentage of time the system is up to deliver useful work (%).

Key-Words / Index Term

Cloud Computing, VCG mechanism, IaaS, Data Centers, Cluster, Auction, Distributed, Geo (Geographically)

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