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Error Control and Support for Large-Scale Multicast Applications
Large-scale distributed applications often require data to be
distributed from one or more of the participants to many or all of the
others. This is most efficiently handled by multicast. Unfortunately,
multicast in the Internet suffers from many problems, several of which
have been addressed by the research conducted as part of this project:
- Loss
One of the foremost problems is the unreliability of the Internet
multicast service: some studies have shown over 30% packet loss,
making it a challenge to communicate. Even much lower loss rates are a
problem in large-scale applications, as the retransmit requests can
easily flood the sender, resulting in so-called sender implosion.
As part of this project, lightweight multicast services (LMS) were
developed and improved, that make efficient propagation and
fulfillment of retransmit requests possible, allowing for a simple and
effective implementation of reliable multicast protocols on top of
this service. To avoid additional load on the source and improve
response time, the system aggregates and directs the retransmit
request to a close-by participant that did not suffer the loss.
- Congestion Control
With multicast gaining attraction, it becomes important to ensure that
multicast traffic does not overload the network or unnecessarily
impair other traffic, a mechanism commonly known as congestion
control. This is an especially challenging task in multicast, due to
the heterogeneity of the link conditions. A subtle balance needs to be
found between quick response to congestion and avoiding constant
switching of the worst-case link, which would result in the transmit
rate dropping to zero. Our result, SRM/CC, combines these mechanisms
and is able to find this balance.
- Availability and Simplicity
The above mechanisms
provide for efficient solution of two main problems at a minimal
network overhead. During the project it became clear that multicast
would not be as quickly and widely deployed as expected: many users
would be unable to get multicast service from their network providers.
We thus started looking at end-system multicast
(ALMI) and dedicated-server
multicast
(AMcast).
Our results are very promising and became a driving force behind many
other research projects on self-organizing and/or structured overlay
networks.
- Scalability
Multicast routing information is a major burden on Internet routers.
We developed Imprecise Multicast Routing to trade significant savings
in router memory and state information, as well as in processing
complexity, against a small penalty in additional traffic.
- Applications
A network function is nothing without applications using it. One of
the most promising applications is Media-on-Demand, for entertainment
as well as for education and information. Our research in that area
resulted in the first scalable, simple, and practicable mechanism
whose performance is basically indistinguishable from the theoretical
optimum. In addition, it supports a wide variety of scenarios,
including pure one-way communication, with no data transmitted from
the receivers to the sender.
Key Results
The following lists some of the key achievements of our research
(for more results and details, see the
publications below):
- LMS was one of the first to propose partial offloading of router
functions to nearby hosts. It partially initiated and heavily
influenced the design of PGM, a mechanism for reliable multicast
that is widely deployed in the Internet.
- ALMI was one of the first to
propose self-organizing overlay networks on top of the Internet to
perform some function that was not or not satisfactorily offered by
the underlying network. It builds on the Internet philosophy that
the network should only be burdened by work that cannot efficiently
be done in end systems. It has spurred significant interest in this
area and many research projects, that use end systems to build
higher-order network topologies.
- Media-on-Demand is likely become a major
source of network traffic. We show that
Fuzzycast, a simple, semi-randomized
algorithm that is much more efficient than previous mechanisms and
whose performance is basically indistinguishable from the
theoretical optimum.
Publications
Participants
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