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  • 1.
    Atxutegi, Eneko
    et al.
    University of the Basque Country, Spain.
    Liberal, Fidel
    University of the Basque Country, Spain.
    Haile, Habtegebreil Kassaye
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Brunström, Anna
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Arvidsson, Åke
    Kristianstad University, Sweden.
    On the use of TCP BBR in cellular networks2018In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, no 3, p. 172-179Article in journal (Refereed)
    Abstract [en]

    TCP BBR (Bottleneck Bandwidth and Round-trip propagation time) is a new TCP variant developed at Google, and which, as of this year, is fully deployed in Googles internal WANs and used by services such as Google.com and YouTube. In contrast to other commonly used TCP variants, TCP BBR is not loss-based but model-based: It builds a model of the network path between communicating nodes in terms of bottleneck bandwidth and minimum round-trip delay and tries to operate at the point where all available bandwidth is used and the round-trip delay is at minimum. Although, TCP BBR has indeed resulted in lower latency and a more efficient usage of bandwidth in fixed networks, its performance over cellular networks is less clear. This paper studies TCP BBR in live mobile networks and through emulations, and compares its performance with TCP NewReno and TCP CUBIC, two of the most commonly used TCP variants. The results from these studies suggest that in most cases TCP BBR outperforms both TCP NewReno and TCP CUBIC, however, not so when the available bandwidth is scarce. In these cases, TCP BBR provides longer file completion times than any of the other two studied TCP variants. Moreover, competing TCP BBR flows do not share the available bandwidth in a fair way, something which, for example, shows up when shorter TCP BBR flows struggle to get its fair share from longer ones. 

  • 2.
    Haile, Habtegebreil Kassaye
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Hurtig, Per
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Rate Measurement Over Short Time Scales inStationary Cellular Receivers2019In: Proceedings of the 3rd Workshop on Mobile Network Measurement (MNM 2019), Paris, France, June 2019, 2019Conference paper (Refereed)
    Abstract [en]

    An increasing number of cellular congestion controlalgorithms (CCAs) are relying on measurements of the deliveryrate observed at the receiver. Accordingly, early detection ofchanges in the receiver’s rate would improve the performanceof such algorithms. Rate measurements over short time intervalscould allow fast detection of change in the rate observed bythe upper layers of a cellular receiver. However, for cellularreceivers, upper-layer rate measurements over short time scalesproduce unreliable results due to the effect of underlying lowerlayer mechanisms such as scheduling and retransmissions. In thispaper, we introduce a rate estimation approach that reduces thevariability observed in short time scale receiver rate measurementsand allows faster rate change detection. We also integratean adaptive mechanism to improve online measurements overdifferent time scales.

  • 3.
    Haile, Habtegebreil Kassaye
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Hurtig, Per
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Brunström, Anna
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Rate Change Detection in Stationary Cellular Nodes2019In: Proceedings of the Fifteenth Swedish National Computer NetworkingWorkshop (SNCNW), Luleå, Sweden. 4-5 June, 2019Conference paper (Refereed)
    Abstract [en]

    An increasing number of cellular congestion controlalgorithms (CCAs) are relying on measurements of the deliveryrate observed at the receiver. Accordingly, early detection ofchanges in the receiver’s rate would improve the performanceof such algorithms. Rate measurements over short time intervalscould allow fast detection of change in the rate observed bythe upper layers of a cellular receiver. However, upper layerrate measurements for cellular receivers over a short time scaleproduce unreliable results due to the effect of underlying lowerlayer mechanisms. In this paper, we introduce a rate estimationapproach that reduces the variability observed in short timescale receiver rate measurements and allows faster rate changedetection.

  • 4.
    Haile, Habtegebreil Kassaye
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Hurtig, Per
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Brunström, Anna
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Atxutegi Narbona, Eneko
    University of the Basque Country.
    Liberal, Fidel
    University of the Basque Country.
    Arvidsson, Åke
    Kristianstad University.
    Evaluation of the Impact of TCP BBR Startup on CUBIC Traffic2018In: The Fourteenth Swedish National Computer Networking Workshop (SNCNW) 2018, 2018Conference paper (Other academic)
  • 5.
    Hurtig, Per
    et al.
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Haile, Habtegebreil Kassaye
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Grinnemo, Karl-Johan
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Brunström, Anna
    Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013).
    Atxutegi, Eneko
    University of the Basque Country, Spain.
    Liberal, Fidel
    University of the Basque Country, Spain.
    Arvidsson, Åke
    Kristianstad University.
    Impact of TCP BBR on CUBIC Traffic: A mixed workload evaluation2018In: Proceedings of the 30th International Teletraffic Congress, ITC 2018, IEEE, 2018, p. 218-226Conference paper (Refereed)
    Abstract [en]

    A recently proposed congestion control algorithm (CCA) called BBR (Bottleneck Bandwidth and Round-trip propagation time) has shown a lot of promise in avoiding some of the problems that have plagued loss-based CCAs. Nevertheless, deployment of a new alternative algorithm requires a thorough evaluation of the effect of the proposed alternative on established transport protocols like TCP CUBIC. Furthermore, evaluations that consider the heterogeneity of Internet traffic sizes would provide a useful insight into the deployability of an algorithm that introduces sweeping changes across multiple algorithm components. Yet, most evaluations of BBR's impact and competitive fairness have focused on the steady-state performance of large flows. This work expands on previous studies of BBR by evaluating BBR's impact when the traffic consists of flows of different sizes. Our experiments show that under certain circumstances BBR's startup phase can result in a significant reduction of the throughput of competing large CUBIC flows and the utilization of the bottleneck link. In addition, the steady-state operation of BBR can have negative impact on the performance of bursty flows using loss-based CCAs over bottlenecks with buffer sizes as high as two times the bandwidth-delay product. 

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