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Distributed Rate Allocation for Inelastic Flows

Hande, Prashanth and Zhang, Shengyu and Chiang, Mung (2007) Distributed Rate Allocation for Inelastic Flows. IEEE/ACM Transactions on Networking, 15 (6). pp. 1240-1253. ISSN 1063-6692. doi:10.1109/TNET.2007.896507.

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A common assumption behind most of the recent research on network rate allocation is that traffic flows are elastic, which means that their utility functions are concave and continuous and that there is no hard limit on the rate allocated to each flow. These critical assumptions lead to the tractability of the analytic models for rate allocation based on network utility maximization, but also limit the applicability of the resulting rate allocation protocols. This paper focuses on inelastic flows and removes these restrictive and often invalid assumptions. First, we consider nonconcave utility functions, which turn utility maximization into difficult, nonconvex optimization problems. We present conditions under which the standard price-based distributed algorithm can still converge to the globally optimal rate allocation despite nonconcavity of utility functions. In particular, continuity of price-based rate allocation at all the optimal prices is a sufficient condition for global convergence of rate allocation by the standard algorithm, and continuity at at least one optimal price is a necessary condition. We then show how to provision link capacity to guarantee convergence of the standard distributed algorithm. Second, we model real-time flow utilities as discontinuous functions. We show how link capacity can be provisioned to allow admission of all real-time flows, then propose a price-based admission control heuristics when such link capacity provisioning is impossible, and finally develop an optimal distributed algorithm to allocate rates between elastic and real-time flows.

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Additional Information:© 2007 IEEE. Manuscript received November 30, 2005; revised September 17, 2006; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor F. Paganini. This work was supported in part by National Science Foundation (NSF) Grants CCF-0440443, CNS-0417607, and CNS-0427677, in part by the Air Force Office of Scientific Research (AFOSR) Grant FA9550–06–1–0297, in part by the Defense Research Advanced Projects Agency (DARPA) Grant HR0011–06–1–0008, and in part by the CBMANET program. Part of this paper was presented at IEEE INFOCOM 2005.
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Air Force Office of Scientific Research (AFOSR)FA9550–06–1–0297
Defense Advanced Research Projects Agency (DARPA)HR0011–06–1–0008
Subject Keywords:Capacity provisioning, congestion control, inelastic flow, network control by pricing, network utility maximization, optimization, resource allocation
Issue or Number:6
Record Number:CaltechAUTHORS:20161102-144047352
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:71684
Deposited By: Kristin Buxton
Deposited On:02 Nov 2016 23:39
Last Modified:11 Nov 2021 04:49

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