@article {43417,
	title = {LGCC: A Novel High-Throughput and Low Delay Paradigm Shift in Multi-Hop Congestion Control},
	journal = {IEEE/ACM Transactions on Networking },
	year = {2023},
	month = {08/2023},
	pages = {1-16},
	publisher = { IEEE},
	abstract = {Technological advancements have provided wireless links with very high data rate capacity for 5G/6G mobile networks and WiFi 6, which will be widely deployed by 2025. However, the capacity can have substantial fluctuations, violating the assumption at the transport layer that the capacity is (almost) steady. In this paper, we present a general and efficient, yet deployable solution to this problem through a novel design empowered with a rich theory, allowing a significantly improved experience in using new technologies, especially mobile cellular services. We employ the well-known theory of food-chain models in biology, where a bottleneck link can be modeled as prey, while flows are predators. We extend this model to a chain of predators and preys to form a multi-hop congestion controller, called LGCC. Through simulation evaluation with real-life 5G traces we show the effectiveness of LGCC, compared with the state-of-the-art ABC (Accel-Brake Control). Our results show an order of magnitude bottleneck queuing delay decrease, with only a small decrease in throughput because LGCC tries to never exceed link capacities. LGCC{\textquoteright}s design can additionally open a new paradigm in stable multi-hop congestion control and flow aggregation.},
	keywords = {5G/6G, food chain, logistic growth, Multi-hop congestion control},
	issn = {1558-2566},
	doi = {10.1109/TNET.2023.3301291},
	url = {https://ieeexplore.ieee.org/document/10216921},
	author = {Teymoori, Peyman and Welzl, Michael and Hayes, David}
}
@article {42554,
	title = {Investigating Predictive Model-Based Control to Achieve Reliable Consistent Multipath mmWave Communication},
	journal = {Computer Communications},
	volume = {194},
	year = {2022},
	month = {10/2022},
	pages = {29-43},
	publisher = { Elsevier},
	abstract = {Millimeter-wave (mmWave) radio is a key building block in 5G and beyond cellular networks. However, mmWave channels are very sensitive to environmental conditions and depend on Line-of-Sight\&nbsp; connections to provide very high data rates. Achieving reliable, consistent communication {\textemdash} i.e., a steady link rate together with low delay {\textemdash} over mmWave links is therefore a challenging problem. The goal of this work is to explore the use of predictive control to manage and simultaneously use multiple available mmWave paths to achieve reliable consistent communication by means of a multipath proxy. We investigate transient solutions of Markov Modulated Fluid Queues (MMFQ) to model the short-term evolution of the proxy{\textquoteright}s packet queue, consistent with the use of Markovian models to capture the behavior of mmWave channel blocking. We propose a combination of models that can be solved using newly proposed matrix-analytic techniques in a timely enough manner for use in real-time control. This gives us a prediction, over a short time horizon, of either proxy queue distributions or probabilities of reaching particular proxy buffer levels. Thus, it enables the proxy to make preemptive path decisions in order to maintain a desired Quality of Service. A proof-of-concept simulation study demonstrates the efficacy of our proposed MMFQ-based predictive approach over both static and purely reactive control approaches. Further, we explore the potential benefits of a hybrid approach to path management, combining both predictive and reactive control. This can allow the controller to cater for unforeseen events that cannot be forecast by the predictive controller, mitigating the resulting extra queuing and corresponding delay spikes.},
	keywords = {5G/6G/+, mmWave, Mobile networks, Multipath, Proxy},
	doi = {10.1016/j.comcom.2022.07.011},
	url = {https://www.sciencedirect.com/science/article/pii/S0140366422002596},
	author = {David Andrew {Hayes} and Ros, David and Alay, {\"O}zg{\"u} and Teymoori, Peyman and Tine Margretha {Vister}}
}
@article {27478,
	title = {Estimating an Additive Path Cost with Explicit Congestion Notification},
	journal = {IEEE Transactions on Control of Network Systems},
	volume = {8},
	year = {2021},
	note = {Currently published in early access on IEEExplore.},
	month = {06/2021},
	pages = {859--871},
	publisher = { IEEE},
	abstract = {Network Utility Maximization (NUM) is a well accepted theoretical framework that describes how congestion controls cooperate to achieve an ideal sending rate allocation, for given utility functions of senders and constraints of the network. These network constraints are expressed as a "cost{\textquoteright}{\textquoteright} in the framework. In practice, most congestion control mechanisms obtain feedback that is different from the framework{\textquoteright}s "cost{\textquoteright}{\textquoteright}. This paper focuses on Explicit Congestion Notification (ECN), which has been shown to be advantageous when it is available, e.g. with the popular Datacenter TCP (DCTCP) mechanism. However, different from the framework{\textquoteright}s cost, ECN marks are not additive. We present a practical solution to this problem. Our solution changes how end hosts interpret the ECN signal, while for the router side, a special configuration of RED is used.},
	issn = { 2325-5870},
	doi = {10.1109/TCNS.2021.3053179},
	url = {https://doi.org/10.1109/TCNS.2021.3053179},
	author = {Teymoori, Peyman and David Andrew {Hayes} and Welzl, Michael and Gjessing, Stein}
}
@inproceedings {27953,
	title = {Reliable Consistent Multipath mmWave Communication},
	journal = {International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM{\textquoteright}21)},
	year = {2021},
	note = {Authors{\textquoteright} version of the work available. Please refer to DOI for the definitive version.},
	month = {11/2021},
	pages = { 149{\textendash}158},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {Reliable consistent communication over millimeter-wave (mmWave) channels is a challenging problem due to their sensitivity to blocking of Line of Sight connections. Even though mmWave is a key building block in 5G and future generation cellular networks, making solutions to this problem space important. Our aim is to use predictive control to manage and simultaneously use multiple available mmWave paths to achieve reliable consistent communication (i.e. steady transmission rate with low delay) with a multipath proxy. To this end we investigate transient solutions of Markov Modulated Fluid Queue models (MMFQ), apt because the mmWave blocking has been modeled with Markovian models. We propose a combination of models that can be solved using newly proposed matrix analytic techniques in a timely enough manner for use in real-time control. This gives us a prediction of either proxy queue distributions or probabilities of reaching proxy buffer levels over a short time horizon, enabling the proxy to make preemptive path decisions to maintain a desired Quality of Service. A proof of concept simulation study demonstrates the efficacy of our proposed MMFQ-based predictive approach over either static or purely reactive control approaches.},
	isbn = {9781450390774},
	doi = {10.1145/3479239.3485684},
	url = {https://doi.org/10.1145/3479239.3485684},
	author = {David Andrew {Hayes} and Ros, David and Alay, {\"O}zg{\"u} and Teymoori, Peyman}
}
@techreport {26310,
	title = {Estimating an Additive Path Cost with Explicit Congestion Notification (extended version)},
	number = {487},
	year = {2019},
	note = {Submitted 2018, awaiting completion of reviews},
	month = {03/2019},
	publisher = {University of Oslo},
	abstract = {Abstract{\textemdash}Network Utility Maximization (NUM) is a well accepted theoretical concept that describes how congestion controls could cooperate to achieve an ideal sending rate allocation, for given utility functions of senders and constraints of the network. These network constraints are expressed as a {\textquotedblleft}cost{\textquotedblright} in the framework. In practice, most congestion control mechanisms obtain feedback that is different from a {\textquotedblleft}cost{\textquotedblright}. This paper focuses on Explicit Congestion Notification (ECN), which has been shown to be quite advantageous when it is available, e.g. with the popular Datacenter TCP (DCTCP) mechanism. However, different from a cost, ECN marks are not additive. We present a practical solution to this problem. Our solution changes how end hosts interpret the ECN signal, while the router side can be implemented via an unusual configuration of RED parameters.},
	isbn = {978-82-7368-452-3},
	issn = {0806-3036},
	url = {https://heim.ifi.uio.no/michawe/research/publications/NUM-ECN_report_2019.pdf},
	author = {Teymoori, Peyman and David Andrew {Hayes} and Welzl, Michael and Gjessing, Stein}
}
@inproceedings {24964,
	title = {Even Lower Latency, Even Better Fairness:Logistic Growth Congestion Control in Datacenters},
	journal = {The 41st IEEE Conference on Local Computer Networks (LCN)},
	year = {2016},
	note = {Dubai, UAE. November 7-10.},
	month = {11/2016},
	pages = {10--18},
	publisher = {IEEE},
	abstract = {Datacenter transport has attracted much recent interest, however, most proposed improvements require changing the datacenter fabric, which hinders their applicability and deployability over commodity hardware. In this paper, we present a novel congestion controller, Logistic Growth Control (LGC), for datacenters which does not require changes to the datacenter fabric. LGC uses a similar ECN marking as in DCTCP, but adapts to congestion using the logistic growth\&nbsp; function. This function has been proven to have nice characteristics including stability, convergence, fairness, and scalability, which are very appealing for\&nbsp; congestion control. As a result, our LGC mechanism operates in the datacenter network in a more stable and fair manner, leading to less queuing and latency. LGC also behaves better than DCTCP, and it converges to the fair share of the bottleneck link capacity irrespective of the Round-Trip-Time (RTT). We discuss the stability and fairness of LGC using a fluid model, and show its performance improvement with simulations.},
	isbn = {978-1-5090-2054-6},
	doi = {10.1109/LCN.2016.12},
	author = {Teymoori, Peyman and David Andrew {Hayes} and Welzl, Michael and Gjessing, Stein}
}
@inproceedings {24643,
	title = {Feedback in Recursive Congestion Control},
	journal = {Computer Performance Engineering: 13th European Workshop on Performance Engineering, EPEW 2016, Proceedings},
	volume = {9951},
	year = {2016},
	note = {Chios, Greece, October 5-7},
	month = {09/2016},
	pages = {109--125},
	publisher = {Springer International Publishing},
	edition = {Lecture Notes in Computer Science},
	address = {Cham},
	abstract = {In recursive network architectures such as RINA or RNA, it is\&nbsp;natural for multiple layers to carry out congestion control. \&nbsp;These\&nbsp;layers can be stacked in arbitrary ways and provide more ways to\&nbsp;use feedback than before (which of the many controllers along an\&nbsp;end-to-end path should be notified?). This in turn raises concerns\&nbsp;regarding stability and performance of such a system of interacting\&nbsp;congestion control mechanisms. In this paper, we report on a\&nbsp;\&nbsp;first analysis of feedback methods in recursive networks that we\&nbsp;carried out using a fluid model with a packet queue\&nbsp;approximation. We find that the strict pushback feedback based on\&nbsp;queue size can have stability issues, but robust control can be\&nbsp;achieved when each congestion controller receives feedback\&nbsp;from all sources of congestion within and below its layer.\&nbsp;},
	isbn = {978-3-319-46433-6},
	doi = {10.1007/978-3-319-46433-6_8},
	url = {http://dx.doi.org/10.1007/978-3-319-46433-6_8},
	author = {David Andrew {Hayes} and Teymoori, Peyman and Welzl, Michael},
	editor = {Fiems, Dieter and Paolieri, Marco and Platis, Agapios}
}
