کنترل تراکم، خدمات متمایز و مدیریت ظرفیت کارآمد از طریق یک استراتژی قیمت گذاری رمان

Pricing is an effective tool to control congestion and achieve Quality of Service (QoS) provisioning for multiple differentiated levels of service. In this paper, we propose a practical, flexible and computationally simple pricing strategy that can achieve QoS provisioning in Differentiated Services networks with multiple priority classes operating in an efficient economic market, while also maintaining stable transmission rates from end-users. In contrast to previous work, in which dynamic pricing strategies are based on the state of congestion alone, our strategy adds a separate price component for the preferential service received by a packet. This permits an efficient market for network resources and services, with the price charged being dependent upon both the cost of the resources and the dynamically changing demand for it. In addition, this automatically enforces efficient capacity management in the allocation of resources among the various service classes, leading to a user-centric approach where a user is not charged a higher price unless preferential service is actually delivered. Our analytical and simulation results demonstrate that, with the combination of user adaptation and our pricing strategy, differentiated services can be achieved with stable transmission rates. This paper concludes with a discussion of various operational issues associated with actual deployment of such a pricing strategy.

The network resources in the Internet are dynamically shared among a large number of users, posing a significant challenge in the guaranteed provisioning of quality-of-service (QoS) to individual users. During the last several years, QoS issues in the Internet have attracted significant research interest as well as commercial investments. One of the ways to achieve QoS guarantees on a per-flow basis is to make a priori reservations of buffer and bandwidth resources in the network. This approach is used in the Integrated Services (IntServ) architecture [4], which relies upon a reservation setup protocol such as RSVP [26]. The per-flow management required at the routers, however, calls into question the scalability of this approach. The Differentiated Services architecture (DiffServ) [3] is an alternate method that achieves improved scalability by aggregating data packets into a small number of service classes and defining router behaviors expected by packets belonging to each of these classes. DiffServ allows up to 64 different service classes that serve only to define the treatment a packet will receive in relation to other packets, but do not provide absolute guarantees on performance. In the absence of guarantees, as in IntServ, the role of capacity planning for traffic from various classes of service becomes critical to achieving satisfactory service. These bandwidth contracts, referred to as service-level agreements (SLAs), can provide reasonable guarantees only when established over long time scales [18]. The user demands for various levels of service can change rapidly due to a variety of reasons; participation in SLAs between providers, therefore, is not likely to lead to an efficient use of network resources. Mechanisms for capacity planning and congestion control through dynamic pricing, however, can be significantly more efficient and also more responsive to changes in, and the demand for, the network resources. This paper explores a practical, flexible and computationally simple user-centric pricing strategy that can achieve QoS provisioning in DiffServ networks with multiple priority classes operating in an efficient economic market, while also maintaining stable transmission rates from end-users.

In this paper, we have presented a novel pricing strategy based on separating the pricing components due to network resources and due to the preferential service received by a packet. This strategy allows a simple, practical and computationally efficient means to achieve QoS provisioning for multiple classes of service in a DiffServ environment, while also maintaining stable transmission rates from the end users. In particular, our strategy of adding a separate price component for preferential service allows a more efficient market in which the price charged for each service class is determined by the cost of providing such service and the dynamically changing demand for it. This serves to enforce efficiency in capacity management among the various service classes. We have used both queueingtheoretic analysis and simulation to demonstrate the stability and feasibility of such a pricing strategy. Our pricing strategy can be adapted in a variety of frameworks that achieve congestion control and differentiated services through pricing.