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Adaptive admission control algorithm in a QoS-aware web system

Lookup NU author(s): Katja Gilly, Dr Nigel Thomas


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Internet traffic tends to show significant growth of demand at certain times of the day, or in response to special events. The consequence of these traffic peaks is that Web systems that are responding to user demands are congested due to their inability to serve a large volume of requests. The case for admission control in these situations is even stronger when Quality of Service (QoS) is considered as a primary objective in the Web system. In this work, we address two issues: on one hand, we consider and compare five throughput predictors to be used in a Web system in order to track its performance and, on the other hand, we propose a QoS-aware admission control and load balancing algorithm that prevents the Web system from sudden overload. The admission control algorithm is based on a resource allocation scheme that includes a throughput predictor. In order to obtain a low overhead, the monitoring of traffic arriving at the Web system is performed following an adaptive time slot scheduling based on the burstiness factor that we defined in previous work. Results show the benefits of our adaptive time slot scheduling compared to a fixed time scheduling. A discussion of the results of the five throughput predictors and the admission control algorithm is provided. We also compare the performance of our algorithm with Intelligent Queue-based Request Dispatcher (IQRD). The algorithm is designed to be included in a Web system composed by a set of Web servers distributed locally, which can also form part of a wider geographically distributed load balancing architecture.

Publication metadata

Author(s): Gilly K, Juiz C, Thomas N, Puigjaner R

Publication type: Article

Publication status: Published

Journal: Information Sciences

Year: 2012

Volume: 199

Pages: 58-77

Print publication date: 15/09/2012

ISSN (print): 0020-0255

ISSN (electronic): 1872-6291

Publisher: Elsevier Inc.


DOI: 10.1016/j.ins.2012.02.018


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