Admission Control and Request Scheduling for Secured-concurrent-available Architecture

Abstract

The Internet society is continuously growing and the need of performance studies in this field is essential in order to obtain better throughput for the Web users. Moreover, Internet applications and clients have varied service expectations and demand provisioning of different levels of QoS to multiple traffic classes on the Internet. Meeting client QoS expectations prove to be a difficult task for E-Commerce service providers, especially when web servers experience overload conditions that cause increased response time, request rejections, user frustration, lowered usage of the service and reduced revenues. A recently proposed MLF (Multi Layered Filtering) framework manages potential workload; it also guaranties data freshness for all transactions that complete within their deadlines without service differentiation using request filtering and admission control schemes. In this paper, an improved request classifier and class-based admission control scheme called Multi-phase Admission Control (MPAC) that can be integrated with the MLF framework to prioritize user requests into several service classes according to their importance, and offer differentiated quality of service in terms of minimizing the frustration of premium users is presented and evaluated. The performance evaluations carried out confirm that the scheme can significantly boost the reward for having serviced a request while providing better QoS to clients.

A QoS-sensitive model for e-commerce customer behavior

“…Moreover, response time is a QoS dimension and is more easily measurable than other dimensions in modeling customer behavior. In the context of the literature on service differentiation and adaptation, response time is sometimes related to the QoS provided to users (Totok and Karamcheti, 2010; Suchacka and Borzemski, 2013; Harini and Padmanabhan, 2013; Larisa et al , 2014; Zatwarnicki and Zatwarnicka, 2014). In this study, the approach proposed for modeling customer behavior is developed with due consideration of response time as the main QoS dimension.…”