Abslmci-This paper proposes an adaptive bandwidth control algorithm that efficiently provides aggregate loss guarantee to resolve the problem of inefficient bandwidth allocation doe to incomplete, inaccurate traffic descriptors supplied by users. Because the control attempts to alloeate the bandwidth only just enough to meet the QoS requirement, the amount of baudwidth saving compared to static aUocation can be substantial. Another distinct advantage of our control algorithm i s that no a priori information on the traffic characteristics of the aggregate is required. From the simnlation study, the proposed control can maintain the packet loss QoS while attaining very high utilization, and is robust against different system configurations and controller parameters.
Abstract-Class-based traffic treatment frameworks such as Differentiated Service (DiffServ) have been proposed to resolve the poor scalability problem in the flow-based approach. Although the performance is differentiated in a class-based basis, the performance seen by individual flows in the same class may differ from that seen by the class and has not been well understood. We investigate this issue by simulation in a single node under FIFO, static priority, waiting time priority, and weighted fair queueing scheduling schemes. Our results indicate that such performance discrepancy occurs especially when flows joining the same class are heterogeneous, which is not uncommon considering that the same type of applications can generate traffic having very different statistical behaviors such as video traffic with different activity levels, or voice traffic with different compression schemes. We found that per-flow delay statistics, including the average and the 99 th percentile delay, can be very different from the corresponding class delay statistics, depending on flow burstiness, overall traffic load, as well as the queue discipline. We also propose a solution to reduce the mean delay variance experienced by flows in the same class.
Symposium: Internet Performance
I. INTRODUCTIONTo overcome poor scalability and high complexity in per-flow traffic handling, per-aggregate or class-based packet scheduling has been suggested (as in the DiffServ architecture [1]), where QoS differentiation is made on a per-class basis. However, the implicit assumption is that the per-flow performance and the aggregate/class performance is close, which may not hold under certain circumstances, as shown in this paper. Equating the per-flow QoS and the class performance when they in fact could disagree degrades the perceived application performance, or deteriorates the integrity of service differentiation. For instance, if the packet delay bound or mean delay of class B is supposed to be twice that of class A, it could happen that some flow in class A sees a delay bound 20% worse than the class while some in class B sees a delay bound 20% better than the class. This certainly is unfair to class A users since the ratio of the delays is now 1.33 instead of 2, as expected. This phenomenon calls for the attention to identify quantitative deviations between the perflow QoS and the class QoS so that applications can be made aware of what QoS levels to expect from the network.
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