Assessment of the Performance for E-Commerce Architecture vis-à-vis Advance Queuing Topology Algorithm (AQTA)

Srivastava, R (2014) Assessment of the Performance for E-Commerce Architecture vis-à-vis Advance Queuing Topology Algorithm (AQTA). International Journal of Computer Applications, 85 (6). pp. 21-25. ISSN 0975-8887

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Abstract

In this paper, we describe the formatting guidelines for IJCA Journal Submission. Impulsive stresses posed by unanticipated drifts of requests from users on Internet have made it exceptionally perplexing for E-Commerce to offer projected enactment of the architecture. In order to provide stable service, it is important for electronic commerce architecture to recognize the performances in terms of response time for requests, delay in accessing the services offered by servers implemented in E-Commerce architecture, and the number of requests waiting in the queue and thereby identifying the strategies to service the requests promptly. The correct and swift algorithm can prominently aid to build and operate electronic commerce architecture more proficiently. In this paper, design and implementation of an algorithm named, AQTA is proposed, which uses the queuing models to prioritize the requests from different classes of users. The proposed algorithm takes the requests from clients, and uses three different set of algorithms simultaneously, namely, Classifier Algorithm, Priority Queue Algorithm and Final Queue Algorithm, to improve the performance of architecture. The comprehensive performance of the AQTA Algorithm is depicted using various Queuing models and the results are shown accordingly. The queue models which are implemented using the simulation study include the comparative study of the AQTA models using M/M/n/K and G/G/n/K models.

Affiliation: Skyline University College
SUC Author(s): Srivastava, R
All Author(s): Srivastava, R
Item Type: Article
Uncontrolled Keywords: AQTA Classifier Algorithm Priority Queue Algorithm Final Queue Algorithm M/M/n/K G/G/n/K.
Subjects: A Business and Management > AB Business and Management
Divisions: Skyline University College > School of Business
Depositing User: Mr SUC Library
Date Deposited: 10 Jun 2022 12:33
Last Modified: 10 Jun 2022 12:33
URI: https://research.skylineuniversity.ac.ae/id/eprint/408
Publisher URL: https://doi.org/10.5120/14846-3200
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/25751
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