A GA-Tabu Based User Centric Approach for Discovering Optimal Qos Composition

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Author(s)

Vivek Gaur 1,* Praveen Dhyani 2 O. P. Rishi 3

1. Birla Institute of Technology, Computer Science Department, Jaipur, 302017, India

2. Banasthali University, Computer Science Department, Jaipur 302001, India

3. Kota Engineering College, Computer Science Department, Kota 324010, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2015.02.08

Received: 20 Oct. 2014 / Revised: 16 Nov. 2014 / Accepted: 23 Dec. 2014 / Published: 8 Feb. 2015

Index Terms

Cloud services, service utility, QoS, ge-netic algorithm, Tabu search

Abstract

Cloud computing is an emerging internet-based paradigm of rendering services on pay- as -per -use basis. Increasing growth of cloud service providers and services creates the need to provide a tool for retrieval of the high-quality optimal cloud services composition with relevance to the user priorities. Quality of Service rank-ings provides valuable information for making optimal cloud service selection from a set of functionally equiva-lent service candidates. To obtain weighted user-centric Quality of Service Composition, real-world invocations on the service candidates are usually required. To avoid the time-consuming and expensive real-world service invocations, this paper proposes framework for predic-tion of optimal composition of services requested by the user. Taking advantage of the past service usage experi-ences of the consumers more cost effective results are achieved. Our proposed framework enables the end user to determine the optimal service composition based on the input weight for individual service Quality of Service. The Genetic algorithm and basic Tabu search is applied for the user-centric Quality of Service ranking prediction and the optimal service composition. The experimental results proves that our approaches outperform other competing approaches.

Cite This Paper

Vivek Gaur, Praveen Dhyani, O. P. Rishi, "A GA-Tabu Based User Centric Approach for Discovering Optimal Qos Composition", International Journal of Modern Education and Computer Science (IJMECS), vol.7, no.2, pp.56-62, 2015. DOI:10.5815/ijmecs.2015.02.08

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