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Fair Scheduling in Networks Through Packet Election

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Title: Fair Scheduling in Networks Through Packet Election
Author: Jagabathula, Srikanth; Shah, Devavrat
Department: Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Issue Date: 2011-03
Abstract: We consider the problem of designing a fair scheduling algorithm for discrete-time constrained queuing networks. Each queue has dedicated exogenous packet arrivals. There are constraints on which queues can be served simultaneously. This model effectively describes important special instances like network switches, interference in wireless networks, bandwidth sharing for congestion control and traffic scheduling in road roundabouts. Fair scheduling is required because it provides isolation to different traffic flows; isolation makes the system more robust and enables providing quality of service. Existing work on fairness for constrained networks concentrates on flow based fairness. As a main result, we describe a notion of packet based fairness by establishing an analogy with the ranked election problem: packets are voters, schedules are candidates, and each packet ranks the schedules based on its priorities. We then obtain a scheduling algorithm that achieves the described notion of fairness by drawing upon the seminal work of Goodman and Markowitz (1952). This yields the familiar Maximum Weight (MW) style algorithm. As another important result, we prove that the algorithm obtained is throughput optimal. There is no reason a priori why this should be true, and the proof requires nontraditional methods.
URI: http://hdl.handle.net/1721.1/72604
ISSN: 0018-9448
Citation: Jagabathula, Srikanth, and Devavrat Shah. “Fair Scheduling in Networks Through Packet Election.” IEEE Transactions on Information Theory 57.3 (2011): 1368–1381.
Version: Author's final manuscript
Terms of Use: Creative Commons Attribution-Noncommercial-Share Alike 3.0
Detailed Terms: http://creativecommons.org/licenses/by-nc-sa/3.0/
Published as: http://dx.doi.org/10.1109/tit.2010.2103851
Journal: IEEE Transactions on Information Theory

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