Demand management for telecommunications services

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Economics of Quality of Experience

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Capacity acquisition and task allocation with tax-band pricing in telecom networks

Bu çalışmada bir şirketin, birden fazla tedarikçiden ağ kapasitesi kiralarken karşılaşılacağı eniyileme problemi incelenmiştir. Problem ele alınırken, bir firmanın veri ağları üzerinde gerçekleştirebileceği işler sabit zamanlı ve sabit boyutlu işler olmak üzere başlıca iki kategoriye ayrılmıştır. Bu iki kategorideki işlerin ihtiyaç duydukları zaman ve bant genişlikleri ile kalite gereksinimleri oldukça farklıdır. Bu nedenle çalışmada; farklı fiyat, kalite ve görev dağılımlarının firmaların optimal davranışını nasıl etkilediği analiz edilmiştir. Problemin karmaşıklığını biraz olsun azaltmak amacıyla, kaynak ve talep hazır olduğu sürece, kapasite için bir üst limit bulunmadığı ve kapasitenin limitsiz olduğu varsayılmıştır. Firmaların bu maliyet en küçültme problemi modellenirken, Courcoubetis ve diğerlerinin (2000a) önerdiği her bir tedarikçinin doğru parçalarından oluşan dışbükey doğrusal amaç fonksiyonuna sahip olduğu kademeli (tax-band) fiyatlandırma politikası dikkate alınmış ve amaç fonksiyonu iki tür maliyeti yansıtacak şekilde oluşturulmuştur. Bu maliyetlerden ilki, tedarikçilerin farklı fiyat seviyelerini yansıtan satın alma maliyetidir. İkinci maliyet ise, son teslim tarihlerinin kaçırılması veya vadelerin geçirilmesi, kalitenin düşmesinden kaynaklanan maliyetler ve karar merci bilinçli olarak hizmet niteliği düzeyini düşürdüğünde veya başka bir tedarikçiye yöneldiğinde meydana gelen hizmet niteliği değişim maliyeti gibi olası fırsat maliyetleridir. Ayrıca, gevşetilmiş problemin çözümünde daha iyi bir alt sınır elde etmek için Genelleştirilmiş Bender Ayrıştırma (Generalized Bender’s Decompomposition – GBD) algoritması uygulanmıştır.    Anahtar Kelimeler: Telekomünikasyon ağları, hizmet niteliği, kademeli (tax-band) fiyatlandırma.Usage of data networks encompasses not only the traditional data applications but also newer applications such as real-time audio/video streaming, voice over TCP/IP, real-time transactions, asynchronous messaging and other batch transactions over digital networks. Each application has different capacity and quality of service (QoS) requirements. Each is affected differently by network reliability and speed. Major network providers have already started efforts to accommodate the QoS demand generated by these applications. Providers charge differently for the capacity they sell. For example, Internet service providers (ISPs) offer a combination of fixed price for a fixed maximum bandwidth (all-you-can-send) or pay per hour (or minute) for again a maximum bandwidth. Wireless phone companies charge for text messaging based on bytes sent. Certain calling plans offer different per minute charges for phone conversations depending on when the call is placed. A firm uses data networks to perform and support business operations, which we will call tasks. For example, a videoconference is a type of task, so is a remote web site update. The obvious commonality is that both tasks require network resources. A network resource is characterized by its capacity (bandwidth and duration) and QoS. We assume that the contract signed between the firm and the provider specifies the amount of bandwidth and quality guaranteed at a given time. Duration specifies the period during which the resource is available. There are two types of costs associated with using data networks. The first one is the resource (i.e., bandwidth, capacity) acquisition cost. The second is the opportunity cost incurred due to insufficient quality realized in performing certain tasks such as video conferencing. Given a heterogeneous set of tasks and resources that differ in bandwidth and quality requirements, it might be in the firm's best interest to use either multiple providers or sign multiple contracts with different bandwidth and quality requirements. For example, while resources with lower quality can be used for data applications, more expensive resources might be utilized for real-time applications with high QoS requirements. Therefore, the problem that the firm has to solve is a cost minimization problem that reflects a trade off between the cost of acquiring resources and the opportunity cost of degradation in realized quality of tasks performed. The quality of service of the resource affects the customer in two ways. First, size-fixed tasks might be delayed beyond acceptable deadlines. Second, the realized quality of a time-fixed task such as a videoconference might be unacceptable creating an opportunity cost for the customer. In general, opportunity cost reflects the importance of a task. The more important the task is, the higher the penalty for not achieving desired targets (such as audio or visual quality). The decision maker will minimize the total cost by considering the trade-off among these costs when assigning tasks to resources. In our study we formulate a cost minimization problem subject to QoS and capacity constraints. We consider the tax-band pricing scheme suggested by Courcoubetis et al. (2000a) in which each supplier has a convex piecewise-linear cost function for each resource offered. Courcoubetis et al. (2000a) claim that tax-band pricing reduces bursty traffic since customers are likely to reduce such demand to avoid paying more. Suppliers in general would prefer having more customers with less capacity demand rather than fewer customers with high capacity demand. Given this pricing structure the customer has to decide how much capacity to acquire and how to allocate tasks. For tractability we relax the due date constraints and assume that all tasks and resources are available at time zero. We also assume that real-time applications have desired transmission rates and any deviation from that creates an opportunity cost for the customer. In spirit, this is the same objective function used in Kasap et al. (2007) that trades the quality cost with the capacity cost but the cost structure for capacity is quite different in this problem. In this study, firstly, we present tax-band pricing. Secondly, a formulation and a solution procedure based on GBD are described.  Keywords: Telecommunication networks, quality of service (QoS), tax-band pricing

Telecommunication Economics

This book constitutes a collaborative and selected documentation of the scientific outcome of the European COST Action IS0605 Econ@Tel "A Telecommunications Economics COST Network" which run from October 2007 to October 2011. Involving experts from around 20 European countries, the goal of Econ@Tel was to develop a strategic research and training network among key people and organizations in order to enhance Europe's competence in the field of telecommunications economics. Reflecting the organization of the COST Action IS0605 Econ@Tel in working groups the following four major research areas are addressed: - evolution and regulation of communication ecosystems; - social and policy implications of communication technologies; - economics and governance of future networks; - future networks management architectures and mechanisms

Telecommunication Economics

This book constitutes a collaborative and selected documentation of the scientific outcome of the European COST Action IS0605 Econ@Tel "A Telecommunications Economics COST Network" which run from October 2007 to October 2011. Involving experts from around 20 European countries, the goal of Econ@Tel was to develop a strategic research and training network among key people and organizations in order to enhance Europe's competence in the field of telecommunications economics. Reflecting the organization of the COST Action IS0605 Econ@Tel in working groups the following four major research areas are addressed: - evolution and regulation of communication ecosystems; - social and policy implications of communication technologies; - economics and governance of future networks; - future networks management architectures and mechanisms

Modelbased accounting and charging systems for digital products in the e-learning

In der Arbeit wurde ein Konzept entwickelt, das eine modellbasierte Betrachtung des Pricings digitaler Produkte ermöglicht