Supporting best-effort traffic with fair service curve

While PFQ algorithms can provide per-flow end-to-end delay guarantees for real-time traffic or protection among competing best-effort traffic, they have two important limitations. The first one is that, since only one parameter (a weight) is used to allocate resource for each flow, there is a coupling between delay and bandwidth allocation. When used for real-time traffic, this can result in network under-utilization. The second and less well known limitation is that, when used for best-effort traffic, PFQ algorithms favor throughputoriented applications such as FTP over delay-sensitive bursty applications such as WWW, and telnet. This is due to the memory-less instantaneous fairness property of PFQ algorithms. In a previous study [1], we proposed the Fair Service Curve (FSC) algorithm which enables more flexible delay and bandwidth allocation for real-time traffic through the use of non-linear service curves. In this paper, we show that, when used for best-effort traffic, FSC can improve performance of delay-sensitive bursty applications without negatively affecting the performance of throughput-oriented applications.

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“…In this paper, we present only a subset of our simulation results. Additional simulation results are presented in [14].…”

Section: Simulation Resultsmentioning

confidence: 99%

“…To compute the timestamps, we need to remember what part of the service curve was used to compute the timestamp of the previous packet. The details of the virtual time computation and algorithm pseudocode can be found in [14].…”

Section: Fair Service Curve Algorithmmentioning

confidence: 99%

Supporting best-effort traffic with fair service curve

Stephens

Stoica

et al. 1999

SIGMETRICS Perform. Eval. Rev.

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“…As discussed below, the primary goal of these algorithms is to divide up the bandwidth in a specified manner between the flows; they do not explicitly attempt to control the latencies of the requests. The second class of scheduling algorithms based on survice curves [7,19,23,26] attempt to simultaneously control both the bandwidth allocation and the latencies of the flows. Finally, storage-specific methods such as Façade [17], Stonehenge [13], SFQ(D) [15] and Avatar [28], either use variants of virtual-time based tagging or a feedback based mechanism to provide heuristic assurances.…”

Section: Related Workmentioning

confidence: 99%

“…Stoica et al [19,26] have identified cases where SCED may fail and have provided a modified virtual-time based algorithm to avoid starving a client for using excess capacity. However they don't guarantee that the client can meet its deadline if it uses the excess capacity.…”

Section: Algorithms Based On Service Curvesmentioning

confidence: 99%

pClock

Gulati

Merchant

Varman

2007

Proceedings of the 2007 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

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Storage consolidation is becoming an attractive paradigm for data organization because of the economies of sharing and the ease of centralized management. However, sharing of resources is viable only if applications can be isolated from each other. This work targets the problem of providing performance guarantees to an application irrespective of the behavior of other workloads. Application requirements are represented in terms of the average throughput, latency and maximum burst size. Most earlier schemes only do weighted bandwidth allocation; schemes that provide control of latency either cannot handle bursts or penalize applications for their own prior behavior, such as using spare capacity.Our algorithm pClock is based on arrival curves that intuitively capture the bandwidth and burst requirements of applications. We show analytically that an application following its arrival curve never misses its deadline. We have implemented pClock both in DiskSim [2] and as a module in the Linux kernel 2.6. Our evaluation shows three important features of pClock: (1) benefits over existing algorithms; (2) efficient performance isolation and burst handling; and (3) the ability to allocate spare capacity to either speed up some applications or to a background utility, such as backup. pClock can be efficiently implemented in a system without much overhead.

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“…Other forms of QoS control that take account of flow duration have been proposed as related work [11], [12]. However, they require that each node has a mechanism for per-flow scheduling or per-flow accounting.…”

Section: Introductionmentioning

confidence: 99%

QoS control to handle long-duration large flows and its performance evaluation

Kawahara

Mori

Abe

2006

2006 IEEE International Conference on Communications

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A method of controlling the rate of long-duration large flows and its performance evaluation is described in this paper. Most conventional QoS controls allocate a fair-share bandwidth to each flow regardless of its duration. Thus, a longduration large flow (such as a P2P flow) is allocated the same bandwidth as a short-duration flow (such as data from a Web page) in which the user is more sensitive to response time. As a result, long-duration flows will occupy the bandwidth over the long period and worsen response times of short-duration flows, and the conventional QoS methods do nothing to prevent this. We have, therefore, proposed a new form of QoS control that takes flow duration into account and assigns higher priority to the acceptance of shorter-duration flows. In this paper, we show through simulation that our method achieves high performance for short-duration flows without degrading the performance of long-duration flows. We also explain how to set parameters used in our method. Furthermore, we discuss the applicability of a packet-sampling technique to improve the method's scalability.

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Supporting best-effort traffic with fair service curve

Cited by 14 publications

References 2 publications

Supporting best-effort traffic with fair service curve

Supporting best-effort traffic with fair service curve

pClock

QoS control to handle long-duration large flows and its performance evaluation

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