The curse of dimensionality gives rise to prohibitive computational requirements that render infeasible the exact solution of large-scale stochastic control problems. We study an efficient method based on linear programming for approximating solutions to such problems. The approach “fits ” a linear combination of pre-selected basis functions to the dynamic programming cost-to-go function. We develop error bounds that offer performance guarantees and also guide the selection of both basis functions and “state-relevance weights ” that influence quality of the approximation. Experimental results in the domain of queueing network control provide empirical support for the methodology. (Dynamic programming/optimal control: approximations/large-scale problems. Queues, algorithms: control of queueing networks.)

This survey reviews the forty-year history of research on transportation revenue management (also known as yield management). We cover developments in forecasting, overbooking, seat inventory control, and pricing, as they relate to revenue management, and suggest future research directions. The survey includes a glossary of revenue management terminology and a bibliography of over 190 references. In the forty years since the first publication on overbooking control, passenger reservations systems have evolved from low level inventory control processes to major strategic information systems. Today, airlines and other transportation companies view revenue management systems and related information technologies as critical determinants of future success. Indeed, expectations of revenue gains that are possible with expanded revenue management capabilities are now driving the acquisition

This paper presents a decentralized auction-based approach to pricing of edge-allocated bandwidth in a differentiated services Internet. The players in our network economy model are one raw-capacity seller per network, one broker per service per network, and users, to play the roles of whole-sellers, retailers, and end-buyers, respectively, in a two-tier wholeseller/retailer market, which is best interpreted as a "sender-pay" model. With the progressive second price auction mechanism as the basic building block, we conduct a game theoretic analysis, deriving optimal strategies for buyers and brokers, and show the existence of networkwide market equilibria.

The theme of this thesis is the design and analysis of decentralized and distributed market mechanisms for resource sharing in multiservice networks. The motivation for a market-based approach is twofold. First, in modern multiservice networks, resources such as bandwidth and buffer space have different value to different users, and these valuations cannot, in general, be accurately known in advance as users compete against each other for the resources. Second, the network resources themselves are distributed, and often, not subject to any single authority. We present

This paper presents a decentralized auction-based approach to pricing of edge-allocated bandwidth in the differentiated services model of the Internet. The players in this architecture are users, one raw-capacity seller per network and one broker per service per network. With the Progressive Second Price auction mechanism as the basic building block, we conduct a game theoretic analysis, deriving optimal strategies for buyers and brokers, and the existence of network-wide equilibria. We investigate the system dynamics by simulating a scenario with three inter-connected networks, and two types of services built on the proposed standard expedited forwarding (EF) and assured forwarding (AF) per-hop behaviors.

We consider a communication network with xed routing that can accommodate multiple service classes, diering in bandwidth requirements, demand pattern, call duration, and routing. The network charges a fee per call which can depend on the current congestion level, and which aects user's demand. Building on the single-node results of Paschalidis and Tsitsiklis, 2000, we consider both problems of revenue and welfare maximization and show that static pricing is asymptotically optimal in a regime of many, relatively small, users. In particular, the performance of an optimal (dynamic) pricing strategy is closely matched by a suitably chosen class-dependent static price, which does not depend on instantaneous congestion. This result holds even when we incorporate demand substitution eects into the demand model. More speci cally, we model the situation where price increases for a class of service might lead users to use another class as an imperfect substitute. For both revenue and welfare maximization objectives we characterize the structure of the asymptotically optimal static prices, expressing them as a function of a parsimonious number of parameters. We employ a simulation-based approach to tune those parameters and to eciently compute an eective policy away from the limiting regime. Our approach can handle large, realistic, instances of the problem.

\Lambda Abstract In this paper we consider a network implementing congestion pricing. For general user utility functions, and in a regime where user peak rates are small compared to network link capacities, we establish optimality of the considered pricing scheme. The corresponding optimal user policies are perhaps contrary to what one would expect: file transfers must either be done at maximal speed, or have access denied, whereas real time applications will display elasticity in their choice of sending rates. We also discuss how the optimality property is affected by price encoding mechanisms implemented in the network, and the resulting effect on user policies. 1

The problem of sharing bandwidth in a communication network has been the focus of much recent research aimed at guaranteeing an appropriate quality of service to users. This is particularly challenging in an environment with a great diversity of users and applications, which makes it difficult, if not impossible, to tightly constrain user attributes and requirements. This motivates shifting the burden of rate allocation from the network to the end-systems. We propose a decentralized scheme for user adaptation and study its dynamics. The proposed scheme uses congestion prices as a mechanism for providing both feedback and incentives to end-systems. Keywords---Pricing, quality of service, congestion control, Internet I.

Abstract- We have designed a Clearing House (CH) architecture that facilitates resource reservations over multiple network domains, and performs local admission control. Two key ideas employed in this design to make the CH scalable to a large user base are hierarchy and aggregation. In our model, we assume the network is composed of various basic routing domains which can be aggregated to form logical domains. This introduces a hierarchical tree of logical domains and a distributed CH architecture is associated with each logical domain to maintain the intradomain aggregate reservations. The parent CH in the logical tree maintains the inter-domain reservation requests. Call setup time is reduced by performing advanced reservations based on statistical estimates of the call traffic across various links. We explore, with simulations, the efficiency of the CH-architecture in terms of resource utilization, call rejections and reservation setup time.

Pricing is one of the biggest challenges facing the next generation of the Internet. Even if flat rate pricing is one of the main reasons for the success of the Internet, the only way to prevent network congestion and to differentiate services is to adopt usage-based pricing schemes. We review in this paper, from a mathematical modeling point of view, the pricing schemes without resource reservation that have been developed in the literature. Indeed, an advantage of the absence of reservation in the Internet is that network management is cheap. Even if accounting and billing will increase this cost, we believe that pricing without resource reservation is the lesser of two evils when costly bandwidth reservation procedures are applied.