Pricing Of Network Services Research Articles

Peer-to-Peer Energy Trading Pricing Mechanisms: Towards a Comprehensive Analysis of Energy and Network Service Pricing (NSP) Mechanisms to Get Sustainable Enviro-Economical Energy Sector

Peer-to-peer (P2P) energy trading facilitates both consumers and prosumers to exchange energy without depending on an intermediate medium. This system makes the energy market more decentralized than before, which generates new opportunities in energy-trading enhancements. In recent years, P2P energy trading has emerged as a method for managing renewable energy sources in distribution networks. Studies have focused on creating pricing mechanisms for P2P energy trading, but most of them only consider energy prices. This is because of a lack of understanding of the pricing mechanisms in P2P energy trading. This paper provides a comprehensive overview of pricing mechanisms for energy and network service prices in P2P energy trading, based on the recent advancements in P2P. It suggests that pricing methodology can be categorized by trading process in two categories, namely energy pricing and network service pricing (NSP). Within these categories, network service pricing can be used to identify financial conflicts, and the relationship between energy and network service pricing can be determined by examining interactions within the trading process. This review can provide useful insights for creating a P2P energy market in distribution networks. This review work provides suggestions and future directions for further development in P2P pricing mechanisms.

SNAP: A DSS to analyze network service pricing for state networks

This study describes the implementation of a spreadsheet-oriented Decision Support System (DSS) that helps in making telecommunications pricing decisions. The system, SNAP-DSS or Service Network Application and Pricing (SNAP)-based DSS, is developed using Microsoft Excel 2007 that also incorporates VBA programming language. We present this research within the context of OneNet, a non-profit state telecommunications service agency. The SNAP-DSS offers the ability to select the rate card options that best fit the preferred pricing strategies by providing a real-time, user-friendly, graphical user interface. The DSS not only captures the effect of changes in the pricing factors on each rate card option, but also allows the user to analyze various rate card options in different scenarios using different parameters. The paper includes some lessons learned for the DSS community.

End-to-end availability-dependent pricing of network services

We discuss how a new pricing scheme can be integrated within a communication network. The pricing scheme is based on the availability of end-to-end communications, and is an alternative to congestion pricing, which is not applicable when communication capacity is higher than demand (as happens in most communication backbone networks). We also investigate how, based on this scheme, an optimization algorithm for updating the network topology can be applied. The network update problem is modeled as a combinatorial optimization problem, which is approximately solved using a Genetic Algorithm. The good results obtained in a case study show that the method is robust and can be applied even when end-to-end availability measures can only be computed approximately (in this case, using a Monte Carlo method).

An enhanced network service pricing model considering network externalities

In this paper, we provide an evaluation model for marketable quality and profitability. We define the marketable quality as a qualitative aspect of profitability. Not always there is a clear tradeoff relation between marketable quality and profitability. Therefore, it is important to discover how to increase the profitability by enhancing marketable quality. We apply the real values of some leading manufacturing Japanese corporations to our proposed model to analyze its accuracy. From the analysis, we found that theoretical and real standard values of the marketable quality indicator were both 0.6. This shows that the proposed model has a good approximation. From the fair relation of network service providers and consumers, we present the network pricing guidelines for the maximum profitability, while enhancing the marketable quality. Also, we enhance our proposed network service pricing model considering network externalities.

Discriminatory Congestion Pricing of Network Services: A Game Theoretic Approach Using Adverse Selection

The quality of network services deteriorates as network utilization increases beyond a certain point, i.e., congestion externalities. Many researchers have proposed congestion pricing models which internalize congestion externalities. However, most studies are based on a unit pricing which cannot reflect user’s different congestion sensitivities. The purpose of this paper is to propose a discriminatory congestion pricing model using adverse selection. Our pricing mechanism provides a

Mandatory Unbundling and Irreversible Investment in Telecom Networks

This paper addresses the investment impact of network sharing mandated by the 1996 Telecommunications Act. Such investments involve sunk costs and so are irreversible. Regulators allow entrants to utilize such facilities at prices reflecting the cost of building a new, efficient, large-scale network. Such sharing opportunities are extensive, covering virtually all network services, and extremely flexible, as entrants can rent facilities in small increments for short duration. Because entrants do not bear the sunk costs, there is an asymmetric allocation of risk and return not properly accounted for in the pricing of network services. This creates a significant investment disincentive.

Incentive-compatible adaptation of Internet real-time multimedia

The rapid deployment of new applications and the interconnection of networks with increasing diversity of technologies and capacity make it more challenging to provide end-to-end quality assurance to the value-added services, such as the transmission of real-time multimedia and mission critical data. In a network with enhancements for QoS support, pricing of network services based on the level of service, usage, and congestion provides a natural and equitable incentive for multimedia applications to adapt their sending rates according to network conditions. We have developed an intelligent service architecture that integrates resource reservation, negotiation, pricing and adaptation in a flexible and scalable way. In this paper, we present a generic pricing structure that characterizes the pricing schemes widely used in the current Internet, and introduce a dynamic, congestion-sensitive pricing algorithm that can be used with the proposed service framework. We also develop the demand behavior of adaptive users based on a physically reasonable user utility function. We introduce our multimedia testbed and describe how the proposed intelligent framework can be implemented to manage a video conference system. We develop a simulation framework to compare the performance of a network supporting congestion-sensitive pricing and adaptive reservation to that of a network with a static pricing policy. We study the stability of the dynamic pricing and reservation mechanisms, and the impact of various network control parameters. The results show that the congestion-sensitive pricing system takes advantage of application adaptivity to achieve significant gains in network availability, revenue, and user-perceived benefit relative to the fixed-price policy. Congestion-based pricing is stable and effective in limiting utilization to a targeted level. Users with different demand elasticity are seen to share bandwidth fairly, with each user having a bandwidth share proportional to its relative willingness to pay for bandwidth. The results also show that even a small proportion of adaptive users may result in a significant performance benefit and better service for the entire user population-both adaptive and nonadaptive users. The performance improvement given by the congestion-based adaptive policy further improves as the network scales and more connections share the resources. Finally, we complement the simulation with experimental results demonstrating important features of the adaptation process.

Mandatory Unbundling and Irreversible Investment in Telecom Networks

This paper addresses the impact on investment incentives of the network sharing arrangements mandated by the Telecommunications Act of 1996, with a focus on the implications of irreversible investment. Although the goal is to promote competition, the sharing rules now in place reduce incentives to build new networks or upgrade existing ones. Such investments are irreversible -- they involve sunk costs. The basic framework adopted by regulators allows entrants to utilize such facilities at prices reflecting what it would cost a new, efficient, large-scale network to be built. Such sharing opportunities are extensive, covering virtually the entire suite of network services provided, and extremely flexible, as the entrant can rent facilities in small increments for short duration, with no long-term contracts required. Because the entrant does not bear the sunk costs, this leads to an asymmetric allocation of risk and return that is not properly accounted for in the pricing of network services, which creates a significant investment disincentive.

Optimization network flow control and price coordination with feedback: proposal of a new distributed algorithm

The usage of price instruments was found to offer an interesting opportunity for reactive congestion flow control in communication or computer networks where the objective is to maximize the total utility of all traffic sources over their transmission rates. The proposed control mechanisms were, amongst others, based on the Price Method—known also as the Interaction Balance Method—and both synchronous and asynchronous versions were developed. It was, however, so far assumed that the transmission network model was known exactly and that no traffic was lost and the traffic routes were fixed and known to the transmitting sources. In this paper, we formulate the flow control problem in a modified form, allowing in particular for the routing decisions to be hidden from the sources, and recall the concept of the Price Coordination with Feedback (known also under the name of the Interaction Balance Method with Feedback—IBMF). It is then shown that the use of this approach allows for proposing the new distributed algorithm for pricing of network services. The existence of an optimal solution in steady state is proved under reasonable assumptions and the convergence issues are discussed. Two examples are provided to illustrate the operation of the proposed algorithm and to compare its performance with the usage of classical price coordination.

Congestion-dependent pricing of network services

We consider a service provider (SP) who provides access to a communication network or some other form of on-line services. Users initiate calls that belong to a set of diverse service classes, differing in resource requirements, demand pattern, and call duration. The SP charges a fee per call, which can depend on the current congestion level, and which affects users' demand for calls. We provide a dynamic programming formulation of the problems of revenue and welfare maximization, and derive some qualitative properties of the optimal solution. We also provide a number of approximate approaches, together with an analysis that indicates that near-optimality is obtained for the case of many, relatively small, users. In particular, we show analytically as well as computationally, that the performance of an optimal pricing strategy is closely matched by a suitably chosen static price, which does not depend on instantaneous congestion. This indicates that the easily implementable time-of-day pricing will often suffice. Throughout, we compare the alternative formulations involving revenue or welfare maximization, respectively, and draw some qualitative conclusions.