QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts

Large inter-datacenter transfers are crucial for cloud service efficiency and are increasingly used by organizations that have dedicated wide area networks between datacenters. A recent work uses multicast forwarding trees to reduce the bandwidth needs and improve completion times of point-to-multipoint transfers. Using a single forwarding tree per transfer, however, leads to poor performance because the slowest receiver dictates the completion time for all receivers. Using multiple forwarding trees per transfer alleviates this concern--the average receiver could finish early; however, if done naively, bandwidth usage would also increase and it is apriori unclear how best to partition receivers, how to construct the multiple trees and how to determine the rate and schedule of flows on these trees. This paper presents QuickCast, a first solution to these problems. Using simulations on real-world network topologies, we see that QuickCast can speed up the average receiver's completion time by as much as $10\times$ while only using $1.04\times$ more bandwidth; further, the completion time for all receivers also improves by as much as $1.6\times$ faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018, Honolulu, H

Probabilistic Congestion Control for Non-Adaptable Flows

In this paper we present a TCP-friendly congestion control scheme for non-adaptable flows. The main characteristic of these flows is that their data rate is determined by an application and cannot be adapted to the current congestion situation of the network. Typical examples of non-adaptable flows are those produced by networked computer games or live audio and video transmissions where adaption of the quality is not possible (e.g., since it is already at the lowest possible quality). We propose to perform congestion control for non-adaptable flows by suspending them at appropriate times so that the aggregation of multiple non-adaptable flows behaves in a TCP-friendly manner. The decision whether a flow is to be suspended is based on random experiments. In order to allocate probabilities for these experiments, the data rate of the non-adaptable flow is compared to the rate that a TCP flow would achieve under the same conditions. We present a detailed discussion of the proposed scheme and evaluate it through extensive simulations with the network simulator ns-2

IP Multicast via Satellite: A Survey

Many of the emerging applications in the Internet, such astele-conferencing, distance-learning, distributed games, softwareupdates, and distributed computing would benefit from multicastservices. In many of these applications, there is a need todistribute information to many sites that are widely dispersed fromeach other. Communication satellites are a natural technology optionand are extremely well suited for carrying such services. Despite thepotential of satellite multicast, there exists little support forsatellite IP multicast services. Both Internet Engineering andInternet Research Task Forces (IETF and IRTF) have been involved in aresearch effort to identify the design space for a general purposereliable multicast protocol and standardize certain protocolcomponents as emph{building blocks}. However, for satellitemulticast services, several of these components have a differentdesign space. In this paper, we attempt to provide an overview of thedesign space and the ways in which the network deployment andapplication requirements affect the solution space. We maintain asimilar taxonomy to that of the IETF efforts, and identify which keycomponents of a general multicast protocol are affected by two of themost common satellite network deployment scenarios. We also highlightsome of the issues which we think are critical in the development ofnext generation satellite IP multicast services

End-to-end single-rate multicast congestion detection using support vector machines

>Magister Scientiae - MScIP multicast is an efficient mechanism for simultaneously transmitting bulk data to multiple receivers. Many applications can benefit from multicast, such as audio and videoconferencing, multi-player games, multimedia broadcasting, distance education, and data replication. For either technical or policy reasons, IP multicast still has not yet been deployed in today’s Internet. Congestion is one of the most important issues impeding the development and deployment of IP multicast and multicast applications

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Optimization-based rate control in overlay multicast.

Zhang Lin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 74-78).Abstracts in English and Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Why use economic models? --- p.1Chapter 1.2 --- Why Overlay? --- p.2Chapter 1.3 --- Our Contribution --- p.3Chapter 1.4 --- Thesis Organization --- p.5Chapter Chapter 2 --- Related Works --- p.7Chapter 2.1 --- Overlay Multicast --- p.7Chapter 2.2 --- IP Multicast Congestion Control --- p.11Chapter 2.2.1 --- Architecture Elements of IP Multicast Congestion Control --- p.11Chapter 2.2.2 --- Evaluation of Multicast Video --- p.13Chapter 2.2.3 --- End-to-End Schemes --- p.14Chapter 2.2.4 --- Router-supported Schemes --- p.16Chapter 2.2.5 --- Conclusion --- p.19Chapter 2.3 --- Optimization-based Rate Control in IP unicast and multicast --- p.20Chapter 2.3.1 --- Optimization-based Rate Control for Unicast Sessions --- p.21Chapter 2.3.2 --- Optimization-based Rate Control for Multi-rate Multicast Sessions --- p.24Chapter Chapter 3 --- Overlay Multicast Rate Control Algorithms --- p.27Chapter 3.1 --- Motivations --- p.27Chapter 3.2 --- Problem Statement --- p.28Chapter 3.2.1 --- Network Model --- p.28Chapter 3.2.2 --- Problem Formulation --- p.29Chapter 3.2.3 --- Algorithm Requirement --- p.33Chapter 3.3 --- Primal-based Algorithm --- p.34Chapter 3.3.1 --- Notations --- p.34Chapter 3.3.2 --- An Iterative Algorithm --- p.36Chapter 3.3.3 --- Convergence Analysis --- p.37Chapter 3.3.3.1 --- Assumptions --- p.37Chapter 3.3.3.2 --- Convergence with various step-sizes --- p.39Chapter 3.3.3.3 --- Theorem Explanations --- p.39Chapter 3.4 --- Dual-based Algorithm --- p.40Chapter 3.4.1 --- The Dual Problem --- p.41Chapter 3.4.2 --- Subgradient Algorithm --- p.43Chapter 3.4.3 --- Interpretation of the Prices --- p.44Chapter 3.4.4 --- Convergence Analysis --- p.45Chapter Chapter 4 --- Protocol Description and Performance Evaluation --- p.47Chapter 4.1 --- Motivations --- p.47Chapter 4.2 --- Protocols --- p.47Chapter 4.2.1 --- Notations --- p.48Chapter 4.2.2 --- Protocol for primal-based algorithm --- p.48Chapter 4.2.3 --- Protocol for dual-based algorithm --- p.53Chapter 4.3 --- Performance Evaluation --- p.57Chapter 4.3.1 --- Simulation Setup --- p.57Chapter 4.3.2 --- Rate Convergence Properties --- p.59Chapter 4.3.3 --- Data Rate Constraint --- p.67Chapter 4.3.4 --- Link Measurement Overhead --- p.68Chapter 4.3.5 --- Communication Overhead --- p.70Chapter Chapter 5 --- Conclusion Remarks and Future Work --- p.73References --- p.7

Equation-Based Congestion Control for Unicast and Multicast Data Streams

We believe that the emergence of congestion control mechanisms for relatively-smooth congestion control for unicast and multicast traffic can play a key role in preventing the degradation of end-to-end congestion control in the public Internet, by providing a viable alternative for multimedia flows that would otherwise be tempted to avoid end-to-end congestion control altogether. The design of good congestion control mechanisms is a hard problem, even more so for multicast environments where scalability issues are much more of a concern than for unicast. In this dissertation, equation-based congestion control is presented as an alternative form of congestion control to the well-known TCP protocol. We focus on areas of equation-based congestion control which were not yet well understood and for which no adequate solutions existed. Starting from a unicast congestion control mechanism which in contrast to TCP provides smooth rate changes, we extend equation-based congestion control in several ways. We investigate how it can work together with applications which can only operate in a very limited region of available bandwidth and whose rate can thus not be adapted to the network conditions in the usual way. Such a congestion control mechanism can also complement conventional equation-based congestion control in regimes where available bandwidth is too low for further rate reduction. When extending unicast congestion control to multicast, it is of paramount importance to ensure that changes in the network conditions anywhere in the multicast tree are reported back to the sender as quickly as possible to allow the sender to adjust the rate accordingly. A scalable feedback mechanism that allows timely congestion feedback in the face of potentially very large receiver sets is one of the contributions of this dissertation. But also other components of a congestion control protocol, such as the rate increase/decrease policy or the slow-start mechanism, need to be adjusted to be able to use them in a multicast environment. Our resulting multicast congestion control protocol was implemented in a simulation environment for extensive protocol testing and turned into a library for the use in real-world applications. In addition, a simple video transmission tool was built for test purposes that uses this congestion control library