Variability in TCP round-trip times

Aikat, Jay; Kaur, Jasleen; Smith, F. Donelson; Jeffay, Kevin

doi:10.1145/948238.948241

Cited by 41 publications

(38 citation statements)

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“…Such delays may be affected by time measurement uncertainties such as drifting clocks and clock resolution [15], clock synchronization uncertainty [15], destination host processing and queuing time (e.g. in case of application based ping) [11], intrusiveness of the measuring system [10] or delays on the sender node [11].…”

Section: A Measurement Uncertainty In Diagnosismentioning

confidence: 99%

Towards a Framework for Self-Adaptive Reliable Network Services in Highly-Uncertain Environments

Ceccarelli

Grønbæk

Montecchi

et al. 2010

2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops

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Abstract-In future inhomogeneous, pervasive and highly dynamic networks, end-nodes may often only rely on unreliable and uncertain observations to diagnose hidden network states and decide upon possible remediation actions. Inherent challenges exists to identify good and timely decision strategies to improve resilience of end-node services. In this paper we present a framework, called ODDR (Observation, Diagnosis, Decision, Remediation), for improving resilience of network based services through integration of self-adaptive monitoring services, network diagnosis, decision actions, and finally execution (and monitoring) of remediation actions. We detail the motivations to the ODDR design, then we present its architecture, and finally we describe our current activities towards the realization and assessment of the framework services and the main results currently achieved.

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Section: A Measurement Uncertainty In Diagnosismentioning

confidence: 99%

Towards a Framework for Self-Adaptive Reliable Network Services in Highly-Uncertain Environments

Ceccarelli

Grønbæk

Montecchi

et al. 2010

2010 13th IEEE International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops

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“…In order to emulate more realistic Internet environments, we add cross traffic modelled from various observations on RTT distribution [26], flow sizes [27] and flow arrival [28]. As modelling the Internet traffic in itself is a topic of research, we do not dwell on which model is more realistic.…”

Section: Dumbell With Background Internet Trafficmentioning

confidence: 99%

Dual-Resource TCP/AQM for Processing-Constrained Networks

Shin

Chong

Rhee

2006

Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications

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Abstract-This paper examines congestion control issues for TCP flows that require in-network processing on the fly in network elements such as gateways, proxies, firewalls and even routers. Applications of these flows are increasingly abundant in the future as the Internet evolves. Since these flows require use of CPUs in network elements, both bandwidth and CPU resources can be a bottleneck and thus congestion control must deal with "congestion" on both of these resources. In this paper, we show that conventional TCP/AQM schemes can significantly lose throughput and suffer harmful unfairness in this environment, particularly when CPU cycles become more scarce (which is likely the trend given the recent explosive growth rate of bandwidth). As a solution to this problem, we establish a notion of dual-resource proportional fairness and propose an AQM scheme, called DualResource Queue (DRQ), that can closely approximate proportional fairness for TCP Reno sources with in-network processing requirements. DRQ is scalable because it does not maintain perflow states while minimizing communication among different resource queues, and is also incrementally deployable because of no required change in TCP stacks. The simulation study shows that DRQ approximates proportional fairness without much implementation cost and even an incremental deployment of DRQ at the edge of the Internet improves the fairness and throughput of these TCP flows. Our work is at its early stage and might lead to an interesting development in congestion control research.

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“…It can be seen that in many cases, the slope for the packets with high chip-rate is much less than it 2 In [5], we found that if RTT is 35 ms, then a loss probability of 1% results in flows being in time-out 1% of the time, while a loss probability of 5% results in the flows being in time-out 50% of the time.…”

Section: Downstream Loss Probability High Chiprates and Burstsmentioning

confidence: 78%

“…For example, the loss probability of a packet that is 99-fast at the 244µs time-scale is 5%, which is 5 times larger than the unconditional loss probability. While 5 times larger is clearly significant, a loss probability of 5% is especially bad since time-out becomes a serious problem with such a high loss probability 2 . Figure 3 also shows that the probability of experiencing a large drop event is greatly amplified when packets are sent with high chip-rates after non-MSS sized packets.…”

Section: Downstream Loss Probability High Chiprates and Burstsmentioning

confidence: 99%