Improving Quality of Business in Next Generation Telecom Networks

Improving Quality of Business in Next Generation Telecom Networks

DOI: 10.4018/978-1-5225-7598-6.ch090
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Abstract

Quality of business (QoBiz) is an important aspect of providing quality of telecommunication services that is being increasingly used in the pursuit of better business. It covers financial aspects of service provisioning, which is firmly related to service provider (SP) revenue and profit. In next generation network (NGN), relation between pure technical aspects (i.e., quality of service [QoS] and QoBiz) tend to be dynamic with pricing as an important tool for adjusting users' demand to network congestion, thus allowing a SP to maximize his revenue. This chapter aims to investigate and provide new possibilities for SPs to enhance their revenues using responsive pricing scheme for charging end users in NGN. Interaction of a SP and user is defined as a Stackelberg leader-follower game with provider acting as the leader and users acting as followers.
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Background

Pricing with QoS guarantees has gained a strong momentum in telecommunication networks in past decade. It has led to a new interdisciplinary research area of “Telecommunication Economics”, which investigates telecommunication networks from an economical rather than from a technical perspective and allows innovative solutions in network management, control and pricing (Courcoubetis & Weber, 2003).

QoS describes the ability of a network to provide a service with an assured service level but it appears that in NGN QoS differentiation will not provide a suitable economic framework for the trade-off between quality delivered by SPs and willingness to pay from users’ side. QoE is an alternative framework for pricing service quality according to the user perception (ITU-T G.1011, 2013). It is affected not only by technical (i.e. QoS) aspects, but on non-technical aspects of service too, such as service set-up, content, price and customer support, which are essential for both QoE and QoBiz evaluation. The distinction between QoS, QoE and QoBiz metrics in case of Internet services are first emphasized by Moorsel (2001). In Wolter and Moorsel (2001) possible relationships between QoS and QoBiz metrics are pointed out, particularly the effects of QoS degradations on the profitability of e-services. This research considers dynamic relationship between QoS and QoBiz metrics with pricing as an important tool for balancing users’ behaviour. Further, for the purpose of evaluating the impact of service composition and utility computing on QoBiz aspects of SPs, a distributed architecture of control systems that manages SLAs is proposed in Machiraju et al. (2002). Yu and Bouguettaya (2007) proposed the model for supporting optimized access of web services through service-oriented queries. Besides QoBiz parameters, this model captures functionality and users’ behaviour, as the key features of web services. Bjekovic and Kubicki (2011) address the need for an integration of non-functional aspects of service from the business perspective with aim of improving cooperation among business enterprises. In Radonjic Djogatovic et al. (2013) the model performing transparent mapping from QoS to QoBiz parameters is proposed. This QoBiz model is based on several QoS parameters that significantly affect both users’ demand and a SP’s requirements from the business perspective.

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