A QoS-based dynamic pricing approach for services provisioning in heterogeneous wireless access networks

In this paper we propose a simple QoS-based dynamic pricing approach for services provisioning in a heterogeneous wireless access network environment which attempts to increase user’s satisfaction level by firstly, maximizing the provided QoS level, and secondly, by applying dynamic pricing strategies according to the QoS. These strategies will allow service providers to maximize their profits. Simulation results demonstrate that the proposed dynamic pricing approach benefits both users and wireless service providers (WSPs). Results also suggest that users have better overall satisfaction due to a better QoS level and fairer prices. The analysis shows that our proposed pricing approach contributes to an increase in WSPs profits compared to the application of the flat-rate pricing model in a competitive market-model.     

Pricing and capacity decisions for non-profit internet service providers

Many universities and other non-profit organizations started Internet dial-up access as a value-added service to their respective communities. The implementation and maintenance of these services becomes a nontrivial task, requiring large annual budgets to keep these systems up and running. The mandate for these non-profit entities is to recover the costs of providing their value added services in the long run while maintaining a guaranteed quality of service (QoS) level. The pricing and capacity planning problem of the non-profit Internet Service Providers (ISPs) has three difficult aspects. First, pricing based on cost recovery has inherent challenges. Second, the non-profit ISPs have to tackle the growth of unpredictable demand that calls for continuous capacity expansion. Third, capacity expansion in terms of Internet dial-up lines comes only in bulk units which typically exhibit economy of scale characteristics. Another critical issue of capacity expansion is the timing of the expansion since the installation of production-mode capacity requires lead-time. This paper proposes a Busiest-Minute Planning Model (BMPM) for the non-profit ISPs to effectively solve the aforementioned issues. The BMPM model provides non-profit ISPs a mechanism to determine the optimum capacity for a given QoS level. The mechanism can predict when existing capacity becomes saturated by taking into account the desired QoS and future demand change. The BMPM model proposed in this paper was tested using data from a non-profit ISP—The Northeast Regional Data Center (NERDC) of the State of Florida. The results suggest that our BMPM model is very effective in solving the pricing and capacity expansion decisions of NERDC and can be applied to other non-profit ISPs.     

An architecture for managing virtual circuit and virtual path services in ATM networks

ATM networks rely on the Virtual Circuit (VC) and Virtual Path (VP) concepts to provide unicast connection-oriented services with Quality of Service (QoS) guarantees. This paper presents a model for managing the configuration and performance of the VC and VP services in these networks. The model consists of a connection management architecture that provides the services and is instrumented for network management purposes, and a network management architecture that uses the OSI management model to provide access to the appropriate service monitoring and control functions. The network management architecture proposes complete managed object definitions that achieve a variety of monitoring and control objectives: service configuration, service performance at the call and cell level, and service control. The latter includes the capability to establish VPs and control their allocated networking capacity and also control parameters of the signaling system that affect the performance of the VC service. The architecture was implemented in its entirety on the Xunet ATM testbed, and several experiments were conducted to illustrate the trade-off between the throughput of the VC service and the allocation of capacity to VPs. The experiments further demonstrated that the signaling system can create throughput bottlenecks in the absence of VPs in the network, and therefore, the network operator can increase performance by controlling the VP distribution.     

A fuzzy multi-objective model for capacity allocation and pricing policy of provider in data communication service with different QoS levels

Data communication service has an important influence on e-commerce. The key challenge for the users is, ultimately, to select a suitable provider. However, in this article, we do not focus on this aspect but the viewpoint and decision-making of providers for order allocation and pricing policy when orders exceed service capacity. It is a multiple criteria decision-making problem such as profit and cancellation ratio. Meanwhile, we know realistic situations in which much of the input information is uncertain. Thus, it becomes very complex in a real-life environment. In this situation, fuzzy sets theory is the best tool for solving this problem. Our fuzzy model is formulated in such a way as to simultaneously consider the imprecision of information, price sensitive demand, stochastic variables, cancellation fee and the general membership function. For solving the problem, a new fuzzy programming is developed. Finally, a numerical example is presented to illustrate the proposed method. The results show that it is effective for determining the suitable order set and pricing policy of provider in data communication service with different quality of service (QoS) levels.     

Modeling and analysis of the effects of QoS and reliability on pricing, profitability, and risk management in multiperiod grid-computing networks

In this paper we develop a network equilibrium model for optimal pricing and resource allocation in Computational Grid Network. We consider a general network economy model with Grid Resource Providers, Grid Resource Brokers and Grid Users. The proposed framework allows for the modeling and theoretical analysis of Computational Grid Markets that considers a non-cooperative behavior of decision-makers in the same tier of the grid computing network (such as, for example, Grid Resource Providers) as well as cooperative behavior between tiers (between Resource Providers and Grid Brokers). We introduce risk management into the decision making process by analyzing the decision-marker's reliability and quality of service (QoS) requirement. We analyze resource allocation patterns as well as equilibrium price based on demand, supply, and cost structure of the grid computing market network. We specifically answer the following questions with several numerical examples: How do system reliability levels affect the QoS levels of the service providers and brokers under competition? How do system reliability levels affect the profits of resource providers and brokers in a competitive market? How do system reliability levels influence the pricing of the services in a competitive environment? How do users' service request types, QoS requirements, and timing concerns affect users' behaviors, costs and risks in equilibrium? How does the market mechanism allocate resources to satisfy the demands of users? We find that for users who request same services certain timing flexibility can not only reduce the costs but also lower the risks. The results indicated that the value of QoS can be efficiently priced based on the heterogeneous service demands.     

Optimal service of aging demands in a single-server system with variable service rate and payment for buffer place rent

Necessary and sufficient conditions are obtained for optimal service of aging demands, which minimize the value of an additive performance functional with specified cost of rent of places. Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 145–150, May–June, 2000.