Dynamic programming: deterministic and stochastic models
Dynamic programming: deterministic and stochastic models
Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
SIAM Journal on Optimization
Routing and wavelength assignment in optical networks
IEEE/ACM Transactions on Networking (TON)
Service overlay networks: SLAs, QoS, and bandwidth provisioning
IEEE/ACM Transactions on Networking (TON)
The Mathematics of Internet Congestion Control (Systems and Control: Foundations and Applications)
The Mathematics of Internet Congestion Control (Systems and Control: Foundations and Applications)
Auction-based resource reservation in 2.5/3G networks
Mobile Networks and Applications
Pricing Communication Networks: Economics, Technology and Modelling (Wiley Interscience Series in Systems and Optimization)
Pricing the internet with multibid auctions
IEEE/ACM Transactions on Networking (TON)
An auction mechanism for allocating the bandwidth of networks to their users
Computer Networks: The International Journal of Computer and Telecommunications Networking
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This paper concerns the problem of allocating network capacity through periodic auctions, in which users submit bids for fixed amounts of end-to-end service. We seek a distributed allocation policy over a general network topology that optimizes revenue for the operator, under the provision that resources allocated in a given auction are reserved for the entire duration of the connection. We first study periodic auctions under reservations for a single resource, modeling the optimal revenue problem as a Markov decision process (MDP), and developing a receding horizon approximation to its solution. Next, we consider the distributed allocation of a single auction over a general network, writing it as an integer program and studying its convex relaxation; techniques of proximal optimization are applied to obtain a convergent algorithm. Combining the two approaches we formulate a receding horizon optimization of revenue over a general network topology, leading to a convex program with a distributed solution. The solution is also generalized to the multipath case, where many routes are available for each end-to-end service. A simulation framework is implemented to illustrate the performance of the proposal, and representative examples are shown.