TY - GEN

T1 - Convergence complexity of optimistic rate based flow control algorithms

AU - Afek, Yehuda

AU - Mansour, Yishay

AU - Ostfeld, Zvi

N1 - Publisher Copyright:
© 1996 ACM.

PY - 1996/7/1

Y1 - 1996/7/1

N2 - This paper studies basic properties of rate based flowcontrol algorithms and of the max-min fairness criteria. For the algorithms we suggest a new approach for their modeling and analysis, which may be considered more "optimistic" and realistic than traditional approaches. Three variations of the approach are presented and their rate of convergence to an optimal max-min fairness solution is analyzed. In addition, we introduce and analyze approximate rate based flow control algorithms. We show that under certain conditions the approximate algorithms may converge faster. However, we show that the resulting flows may be substantially different than the flows according to the max-min fairness. We further demonstrate that the max-min fairness solution can be very sensitive to small changes, i.e., there are configurations in which an addition or deletion of a session with rate δ may change the allocation of another session by Ω(δ · 2 n/2), but by no more than O(δ · 2n). This implies that it might be hard to locally estimate in a given state how close a session is to its max-min fair allocation.

AB - This paper studies basic properties of rate based flowcontrol algorithms and of the max-min fairness criteria. For the algorithms we suggest a new approach for their modeling and analysis, which may be considered more "optimistic" and realistic than traditional approaches. Three variations of the approach are presented and their rate of convergence to an optimal max-min fairness solution is analyzed. In addition, we introduce and analyze approximate rate based flow control algorithms. We show that under certain conditions the approximate algorithms may converge faster. However, we show that the resulting flows may be substantially different than the flows according to the max-min fairness. We further demonstrate that the max-min fairness solution can be very sensitive to small changes, i.e., there are configurations in which an addition or deletion of a session with rate δ may change the allocation of another session by Ω(δ · 2 n/2), but by no more than O(δ · 2n). This implies that it might be hard to locally estimate in a given state how close a session is to its max-min fair allocation.

UR - http://www.scopus.com/inward/record.url?scp=0029700728&partnerID=8YFLogxK

U2 - 10.1145/237814.237837

DO - 10.1145/237814.237837

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AN - SCOPUS:0029700728

T3 - Proceedings of the Annual ACM Symposium on Theory of Computing

SP - 89

EP - 98

BT - Proceedings of the 28th Annual ACM Symposium on Theory of Computing, STOC 1996

PB - Association for Computing Machinery

T2 - 28th Annual ACM Symposium on Theory of Computing, STOC 1996

Y2 - 22 May 1996 through 24 May 1996

ER -