Buffer overflow management in QoS switches

We consider two types of buffering policies that are used in network switches supporting QoS (Quality of Service). In the FIFO type, packets must be released in the order they arrive; the difficulty in this case is the limited buffer space. In the bounded-delay type, each packet has a maximum delay time by which it must be released, or otherwise it is lost. We study the cases where the incoming streams overload the buffers, resulting in packet loss. In our model, each packet has an intrinsic value; the goal is to maximize the total value of packets transmitted Our main contribution is a thorough investigation of the natural greedy algorithms in various models. For the FIFO model we prove tight bounds on the competitive ratio of the greedy algorithm that discards the packets with the lowest value. We also prove that the greedy algorithm that drops the earliest packets among all low-value packets is the best greedy algorithm. This algorithm can be as much as 1.5 times better than the standard tail-drop policy, that drops the latest packets. In the bounded delay model we show that the competitive ratio of any online algorithm for a uniform bounded delay buffer is bounded away from 1, independent of the delay size. We analyze the greedy algorithm in the general case and in three special cases: delay bound 2; link bandwidth 1; and only two possible packet values. Finally, we consider the off-line scenario. We give efficient optimal algorithms and study the relation between the bounded-delay and FIFO models in this case.

[1]  Ronald L. Rivest,et al.  Introduction to Algorithms , 1990 .

[2]  Sanjoy K. Baruah,et al.  On the competitiveness of on-line real-time task scheduling , 1991, [1991] Proceedings Twelfth Real-Time Systems Symposium.

[3]  Sanjoy K. Baruah,et al.  On-line scheduling in the presence of overload , 1991, [1991] Proceedings 32nd Annual Symposium of Foundations of Computer Science.

[4]  Dennis Shasha,et al.  D/sup over/; an optimal on-line scheduling algorithm for overloaded real-time systems , 1992, [1992] Proceedings Real-Time Systems Symposium.

[5]  QUTdN QeO,et al.  Random Early Detection Gateways for Congestion Avoidance , 1993 .

[6]  Amos Fiat,et al.  On-line load balancing with applications to machine scheduling and virtual circuit routing , 1993, STOC.

[7]  Walter Willinger,et al.  On the self-similar nature of Ethernet traffic , 1993, SIGCOMM '93.

[8]  Richard J. Lipton,et al.  Online interval scheduling , 1994, SODA '94.

[9]  Dennis Shasha,et al.  D^over: An Optimal On-Line Scheduling Algorithm for Overloaded Uniprocessor Real-Time Systems , 1995, SIAM J. Comput..

[10]  T. V. Lakshman,et al.  The drop from front strategy in TCP and in TCP over ATM , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[11]  R. K. Shyamasundar,et al.  Introduction to algorithms , 1996 .

[12]  David Clark,et al.  An Approach to Service Allocation in the Internet , 1997 .

[13]  Amos Fiat,et al.  On-line routing of virtual circuits with applications to load balancing and machine scheduling , 1997, JACM.

[14]  Zheng Wang,et al.  An Architecture for Differentiated Services , 1998, RFC.

[15]  David L. Black,et al.  An Architecture for Differentiated Service , 1998 .

[16]  Arnold L. Rosenberg,et al.  Scheduling Time-Constrained Communication in Linear Networks , 1998, SPAA.

[17]  Miguel A. Labrador,et al.  Packet dropping policies for ATM and IP networks , 1999, IEEE Communications Surveys & Tutorials.

[18]  Van Jacobson,et al.  An Expedited Forwarding PHB , 1999, RFC.

[19]  Sudipto Guha,et al.  Approximating the throughput of multiple machines under real-time scheduling , 1999, STOC '99.

[20]  Christophe Diot,et al.  Simple performance models of differentiated services schemes for the Internet , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[21]  Reuven Bar-Yehuda,et al.  A unified approach to approximating resource allocation and scheduling , 2000, STOC '00.

[22]  Boaz Patt-Shamir,et al.  Optimal smoothing schedules for real-time streams , 2004, PODC '00.

[23]  Andras Veres,et al.  The chaotic nature of TCP congestion control , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[24]  Subhash Suri,et al.  Online Scheduling with Hard Deadlines , 2000, J. Algorithms.

[25]  Cynthia A. Phillips,et al.  Off-line admission control for general scheduling problems , 2000, SODA '00.

[26]  Boaz Patt-Shamir,et al.  Optimal smoothing schedules for real-time streams (extended abstract) , 2000, PODC.

[27]  Reuven Bar-Yehuda,et al.  A unified approach to approximating resource allocation and scheduling , 2001, JACM.

[28]  Sudipto Guha,et al.  Approximating the Throughput of Multiple Machines in Real-Time Scheduling , 2002, SIAM J. Comput..

[29]  Yishay Mansour,et al.  Loss-bounded analysis for differentiated services , 2001, ACM-SIAM Symposium on Discrete Algorithms.