NDLI: Efficient multi-objective particle swarm optimisation based ranking system for cloud service selection

Content Provider	IET Digital Library
Author	Kunhambu, Dileep Varapravathu Balan, Rathnamani Vijayalakshmi Siva
Abstract	Cloud computing knowledge achieves the prominent role in elaborating the systems and distributing the applications throughout the internet. Currently, in a cloud computing environment, expedient service selection is essential, since cloud users dependably have assorted sorts of applications with various quality necessities. The cloud service ranking has four phases: receiving user's requirement, estimating the quality of service (QoS) attributes by monitoring, selecting candidate services and service ranking. Previously, a cloud service ranking based on QoS attributes employs both essential and non-essential requirements and both objective and subjective assessments. Existing cloud service ranking system experiences multifaceted nature issues. In order to overcome these issues the authors’ proposed technique is introduced. Their system comprises of three stages which are screening, optimal pseudo services and clustering process. In the Screening, the appropriate candidate's services are selected. In the wake of screening, candidate's services are optimally chosen to utilisean enhanced multi-objective particle swarm optimisation algorithm. Finally, for the purpose of ranking the selected candidate's services are clustered by hierarchical clustering algorithm and pick the best services. The proposed technique is actualised in JAVA with CloudSim.
Starting Page	297
Ending Page	304
Page Count	8
ISSN	17518628
Volume Number	13
e-ISSN	17518636
Issue Number	Issue 3, Feb (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/13/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2018.5164
Journal	IET Communications
Publisher Date	2018-10-31
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Candidate Services Cloud Computing Cloud Computing Environment Cloud Computing Knowledge Cloud Service Ranking System Cloud Service Selection Cloud User CloudSim Data Handling Technique Internet Software JAVA Multiobjective Particle Swarm Optimisation Algorithm Nonessential Requirements Optimal Pseudoservices Optimisation Technique Particle Swarm Optimisation Pattern Clustering QoS Attributes Quality of Service Quality of Service Attributes Selected Candidate Service Selection
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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