RFC2887 - The Reliable Multicast Design Space for Bulk Data Transfer

Network Working Group M. Handley

Request for Comments: 2887 S. Floyd

Category: Informational ACIRI

B. Whetten

Talarian

R. Kermode

Motorola

L. Vicisano

Cisco

M. Luby

Digital Fountain, Inc.

August 2000

The Reliable Multicast Design Space for Bulk Data Transfer

Status of this Memo

This memo provides information for the Internet community. It does

not specify an Internet standard of any kind. Distribution of this

memo is unlimited.

Abstract

The design space for reliable multicast is rich, with many possible

solutions having been devised. However, application requirements

serve to constrain this design space to a relatively small solution

space. This document provides an overview of the design space and

the ways in which application constraints affect possible solutions.

1. IntrodUCtion

The term "general purpose reliable multicast protocol" is something

of an oxymoron. Different applications have different requirements

of a reliable multicast protocol, and these requirements constrain

the design space in ways that two applications with differing

requirements often cannot share a single solution. There are however

many successful reliable multicast protocol designs that serve more

special purpose requirements well.

In this document we attempt to review the design space for reliable

multicast protocols intended for bulk data transfer. The term bulk

data transfer should be taken as having broad meaning - the main

limitations are that the data stream is continuous and long lived -

constraints necessary for the forms of congestion control we

currently understand. The purpose of this review is to gather

together an overview of the field and to make eXPlicit the

constraints imposed by particular mechanisms. The aim is to provide

guidance to the standardization process for protocols and protocol

building blocks. In doing this, we cluster potential solutions into

a number of loose categories - real protocols may be composed of

mechanisms from more than one of these clusters.

The main constraint on solutions is imposed by the need to scale to

large receiver sets. For small receiver sets the design space is

much less restricted.

2. Application Constraints

Application requirements for reliable multicast (RM) are as broad and

varied as the applications themselves. However, there are a set of

requirements that significantly affect the design of an RM protocol.

A brief list includes:

o Does the application need to know that everyone received the data?

o Does the application need to constrain differences between

receivers?

o Does the application need to scale to large numbers of receivers?

o Does the application need to be totally reliable?

o Does the application need ordered data?

o Does the application need to provide low-delay delivery?

o Does the application need to provide time-bounded delivery?

o Does the application need many interacting senders?

o Is the application data flow intermittent?

o Does the application need to work in the public Internet?

o Does the application need to work without a return path (e.g.

satellite)?

o Does the application need to provide secure delivery?

In the context of standardizing bulk data transfer protocols, we can

rule out applications with multiple interacting senders and

intermittent data flows. It is not that these applications are

unimportant, but that we do not yet have effective congestion control

for such applications.

2.1. Did everyone receive the data?

In many applications a logically defined unit or units of data is to

be delivered to multiple clients, e.g., a file or a set of files, a

software package, a stock quote or package of stock quotes, an event

notification, a set of slides, a frame or block from a video. An

application data unit (ADU) is defined to be a logically separable

unit of data that is useful to the application. In some cases, an

application data unit may be short enough to fit into a single packet

(e.g., an event notification or a stock quote), whereas in other

cases an application data unit may be much longer than a packet

(e.g., a software package).

A protocol may optionally provide delivery confirmation to ensure

reliable delivery, i.e., a mechanism for receivers to inform the

sender when data has been delivered. There are two types of

confirmation, at the application data unit level and at the packet

level. Application data unit confirmation is useful at the

application level, e.g., to inform the application about receiver

progress and to decide when to stop sending packets about a

particular application data unit. Packet confirmation is useful at

the transport level, e.g., to inform the transport level when it can

release buffer space being used for storing packets for which

delivery has been confirmed.

Some applications have a strong requirement for confirmation that all

the receivers got an ADU, or if not, to be informed of which specific

receivers failed to receive the entire ADU. Examples include

applications where receivers pay for data, and reliable file-system

replication. Other applications do not have such a requirement. An

example is the distribution of free software.

If the application does need to know that every receiver got the ADU,

then a positive acknowledgment must be received from every receiver,

although it may be possible to aggregate these acknowledgments. If

the application needs to know precisely which receivers failed to get

the ADU, additional constraints are placed on acknowledgment

aggregation.

It should be noted that different mechanisms can be used for ADU-

level confirmation and packet-level confirmation in the same

application. For example, an ADU-level confirmation mechanism using

positive acknowledgments may sit on top of a packet-level NACK or

FEC-based transport. Typically this only makes sense when ADUs are

significantly larger than a single packet.

2.2. Constraining differences

Some applications need to constrain differences between receivers so

that the data reception characteristics for all receivers falls

within some range. An example is a stock price feed, where it is

unacceptable for a receiver to suffer delivery that is delayed

significantly more than any other receiver.

This requirement is difficult to satisfy without harming performance.

Typically solutions involve not sending more than a limited amount of

new data until positive acknowledgments have been received from all

the receivers. Such a solution does not cope with network and end-

system failures well.

2.3. Receiver Set Scaling

There are many applications for RM that do not need to scale to large

numbers of receivers. For such applications, a range of solutions

may be available that are not available for applications where

scaling to large receiver sets is a requirement.

A protocol must achieve good throughput of application data units to

receivers. This means that most data that is delivered to receivers

is useful in recovering the application data unit that they are

trying to receive. A protocol must also provide good congestion

control to fairly share the available network resources between all

applications. Receiver set scaling is one of the most important

constraints in meeting these requirements, because it strictly limits

the mechanisms that can be used to achieve these requirements to

those that will efficiently scale to a large receiver population.

Acknowledgement packets have been employed by many systems to achieve

these goals, but it is important to understand the strength and

limitations of different ways of using such packets.

In a very small system, it may be acceptable to have the receivers

acknowledge every packet. This approach provides the sender with the

maximum amount of information about reception conditions at all the

receivers, information that can be used both to achieve good

throughput and to achieve congestion control.

For larger systems, such "flat ACK" schemes cause acknowledge

implosions at the sender. Attempts have been made to reduce this

problem by sending aggregate ACKs infrequently [RMWT98, BC94], but it

is very difficult to incorporate effective congestion control into

such protocols because of the spareceness of feedback.

Using negative acknowledgments (NACKs) instead of ACKs reduces this

problem to one of NACK implosion (only from the receivers missing the

packets), and because the sender really only needs to know that at

least one receiver is missing data in order to achieve good

throughput, various NACK suppression mechanisms can be applied.

An alternative to NACKs is ACK aggregation, which can be done by

arranging the receivers into a logical tree, so that each leaf sends

ACKs to its parent which aggregates them, and passes them on up the

tree. Tree-based protocols scale well, but tree formation can be

problematic.

Other ACK topologies such as rings are also possible, but are often

more difficult to form and maintain than trees are. An alternative

strategy is to add mechanisms to routers so that they can help out in

achieving good throughput or in reducing the cost of achieving good

throughput.

All these solutions improve receiver set scaling, but they all have

limits of one form or another. One class of solutions scales to an

infinite number of receivers by having no feedback channel whatsoever

in order to achieve good throughput. These open-loop solutions take

the initial data and encode it using an FEC-style mechanism. This

encoded data is transmitted in a continuous stream. Receivers then

join the session and receive packets until they have sufficient

packets to decode the original data, at which point they leave the

session.

Thus, it is clear that the intended scale of the session constrains

the possible solutions. All solutions will work for very small

sessions, but as the intended receive set increases, the range of

possible solutions that can be deployed safely decreases.

It should also be noted that hybrids of these mechanisms are

possible, and that using one mechanism at the packet-level and a

different (typically higher overhead) solution at the ADU level may

also scale reasonably if the ADUs are large compared to packets.

2.4. Total vs Semi-reliable

Many applications require delivery of application data units to be

totally reliable; if any of the application data unit is missing,

none of the received portion of the application data unit is useful.

File transfer applications are a good example of applications

requiring total reliability.

However, some applications do not need total reliability. An example

is audio broadcasting, where missing packets reduce the quality of

the received audio but do not render it unusable. Such applications

can sometimes get by without any additional reliability over native

IP reliability, but often having a semi-reliable multicast protocol

is desirable.

2.5. Time-bounded Delivery

Many applications just require data to be delivered to the receivers

as fast as possible. They have no absolute deadline for delivery.

However, some applications have hard delivery constraints - if the

data does not arrive at the receiver by a certain time, there is no

point in delivering it at all. Such time-boundedness may be as a

result of real-time constraints such as with audio or video

streaming, or as the result of new data superseding old data. In

both cases, the requirement is for the application to have a greater

degree of control over precisely what the application sends at which

time than might be required with applications such as file transfer.

Time-bounded delivery usually also implies a semi-reliable protocol,

but the converse does not necessarily hold.

3. Network Constraints

The properties of the network in which the application is being

deployed may themselves constrain the reliable multicast design

space.

3.1. Internet vs Intranet

In principle the Internet and intranets are the same. In practice

however, the fact that an intranet is under one administration might

allow for solutions to be configured that can not easily be done in

the public Internet. Thus, if the data is of very high value, it

might be appropriate to enhance the routers to provide assistance to

a reliable multicast transport protocol. In the public Internet, it

is less likely that the additional expense required to support this

state in the routers would be acceptable.

3.2. Return Path

In principle, when feedback is required from receivers, this feedback

can be multicast or unicast. Multicast feedback has advantages,

especially in NACK-based protocols where it is valuable for NACK

suppression. However, it is not clear at this time whether all ISPs

will allow all members of a session to send to that session. If

multicast feedback is not allowed, then unicast feedback can almost

always be substituted, although often at the expense of additional

messages and mechanisms.

Some networks may not allow any form of feedback however. The

primary example of this occurs with satellite broadcasts where the

back channel may be very narrow or even non-existent. For such

networks the solution space is very constrained - only FEC-based

encodings have any real chance of working. If the receivers are

direct satellite receivers, then no congestion control is needed, but

it is dangerous to make such assumptions because it is possible for a

satellite hop to feed downstream networks. Thus, congestion control

still needs to be considered with solutions that do not have a return

path.

3.3. Network Assistance

A reliable multicast protocol must involve mechanisms running in end

hosts, and must involve routers forwarding multicast packets.

However under some circumstances, it is possible to rely on some

additional degree of assistance from network elements. Broadly

speaking we can cluster RM protocols into four classes depending on

the degree of support received from other network elements.

No Additional Support

The routers merely forward packets, and only the sender and

receivers have any reliable multicast protocol state.

Layered Approaches

Data is split across multiple multicast groups. Receivers join

appropriate groups to receive only the traffic they require. This

may in some cases require fast join or leave functionality from

the routers, and may require more forwarding state in the routers.

Server-based Approaches

Additional nodes are used to assist with data delivery or feedback

aggregation. These additional nodes might not be normal senders

or receivers, and may be present on the distribution or feedback

tree only to provide assistance to the reliable multicast

protocol. They would not otherwise receive the multicast traffic.

Router-based Approaches

With router-based approaches, routers on the normal data

distribution tree from the sender to the receivers assist in the

delivery of data or feedback aggregation or suppression. As

routers can directly influence multicast routing, they have more

control over which traffic goes to which group members than

server-based approaches. However routers do not normally have a

large amount of spare memory or processing power, which restricts

how much functionality can be placed in the routers. In addition,

router code is normally more difficult to upgrade than application

code, so router-based approaches need to be very general as they

are more difficult to deploy and to change.

4. Good Throughput Mechanisms

Two main concerns that a RM protocol must address are congestion

control and good throughput. Packet loss plays a major role with

respect to both concerns. The primary symptom of congestion in many

networks is packet loss. The primary obstacle that must be overcome

to achieve good throughput is packet loss. Thus, measuring and

reacting to packet loss is crucial to address both concerns. RM

solutions that address these concerns can be roughly categorized as

using one or more of the following techniques:

o Data packet acknowledgment.

o Negative acknowledgment of missing data packets.

o Redundancy allowing not all packets to be received.

These techniques themselves can be usefully subdivided, so that we

can examine the parts of the requirement space in which each

mechanism can be deployed. In this section, we focus on using these

mechanisms for achieving good throughput, and in the next section we

focus on using these mechanisms for congestion control.

4.1. ACK-based Mechanisms

The simplest ACK-based mechanism involves every receiver sending an

ACK packet for every data packet it receives and resending packets

that are lost by any receiver. Such mechanisms are limited to very

small receiver groups by the implosion of ACKs received at the

sender, and for this reason they are impractical for most

applications.

Putting multiple ACKs into a single data packet [RMWT98] reduces the

implosion problem by a constant amount, allowing slightly larger

receiver groups. However a limit is soon reached whereby feedback to

the sender is too infrequent for sender-based congestion control

mechanisms to work reliably.

Arranging the receivers into a ring [WKM94] whereby an "ACK-token" is

passed around the ring prevents the implosion problem for data.

However ring creation and maintenance may itself be problematic.

Also if ring creation does not take into account network topology

(something which is difficult to achieve in practice), then the

number of ACK packets crossing the network backbone for each data

packet sent may increase O(n) with the number of receivers.

4.1.1. Tree-based ACK Mechanisms

Arranging the receivers into a tree [MWB+98, KCW98] whereby receivers

generate ACKs to a parent node, which aggregates those ACKs to its

parent in turn, is both more robust and more easily configured than a

ring. The ACK-tree is typically only used for ACK-aggregation - data

packets are multicast from the sender to the receivers as normal.

Trees are easier to construct than rings because more local

information can be used in their construction. Also they can be more

fault tolerant than rings because node failures only affect a subset

of receivers, each of which can easily and locally decide to by-pass

its parent and report directly to the node one level higher in the

tree. With good ACK-tree formation, tree-based ACK mechanisms have

the potential to be one of the most scalable RM solutions.

To be simple to deploy, tree-based protocols must be self-organizing

- the receivers must form the tree themselves using local information

in a scalable manner. Such mechanisms are possible, but are not

trivial. The main scaling limitations of tree-based protocols

therefore come from the tree formation and maintenance mechanisms

rather than from the use of ACKs. Without such a scalable and

automatic tree-formation mechanism, tree-based protocols must rely on

manual configuration, which significantly limits their applicability

(often to intranets) and (due to the complexity of configuration)

their scalability.

Orthogonal to the issue of tree formation is the issue of suBTree

retransmission. With appropriate router mechanisms, or the use of

multiple multicast groups, it is possible to allow the intermediate

tree nodes to retransmit missing data to the nodes below them in the

tree rather than relying on the original sender to retransmit the

data. This relies on there being a good correlation at the point of

the intermediate node between the ACK tree and the actual data tree,

as well as there being a mechanism to constrain the retransmission to

the subtree. A good automatic tree formation mechanism combined with

the use of administrative scoped multicast groups might provide such

a solution. Without such tree formation mechanisms, subtree

retransmission is difficult to deploy in large groups in the public

internet. This could also be solved by the use of transport-

level router mechanisms to assist or perform retransmission, although

existing router mechanisms [FLST98] support NACK-based rather than

ACK-based protocols.

Another important issue is the nature of the aggregation performed at

interior nodes on the ACK-tree. Such nodes could:

1. aggregate ACKs by sending a single ACK when all their children

have ACKed,

2. aggregate ACKs by listing all the children that have ACKed,

3. send an aggregated ACK with a NACK-like exception list.

For data packets, 1. is clearly more scalable, and should be

preferred. However if the sender needs to know exactly which

receivers received the data, 2. and 3. provide this information.

Fortunately, there is usually no need to do this on a per-packet

basis, but rather on a per-ADU basis. Doing 1. on a per packet

basis, and 3. on a per ADU basis is the most scalable solution for

applications that need this information, and suffers virtually no

disadvantage compared to the other solutions used on a per-packet

basis.

4.2. NACK-based mechanisms

Instead of sending an ACK for every data packet received, receivers

can send a negative acknowledgment (NACK) for every data packet they

discover they did not receive. This has a number of advantages over

ACK-based mechanisms:

o The sender no longer needs to know exactly how many receivers

there are. This removes the topology-building phase needed for

ring- or tree-style ACK-based algorithms.

o Fault-tolerance is made somewhat simpler by making receivers

responsible for reliability.

o Sender state can be significantly reduced because the sender does

not need to keep track of the receivers state.

o Only a single NACK is needed from any receiver to indicate a

packet that is missing by any number of receivers. Thus NACK

suppression is possible.

The disadvantages are that it is more difficult for the sender to

know that it can free transmission buffers, and that additional

session level mechanisms are needed if the sender really needs to

know if a particular receiver actually received all the data.

However for many applications, neither of these is an issue.

4.2.1. NACK Suppression

The key differences between NACK-based protocols is in how NACK-

suppression is performed. The goal is for only one NACK to reach the

sender (or a node that can resend the missing data) as soon as

possible after the loss is first noticed, and for only one copy of

the missing data to be received by those nodes needing

retransmission.

Different mechanisms come close to satisfying these goals in

different ways.

o SRM [FJM95] uses random timers weighted by the round trip time

between the sender and each node missing the data. This is

effective, but requires computing the RTT to each receiver before

suppression works properly.

o NTE [HC97] uses a sender-triggered mechanism based on random keys

and sliding masks. This does not require random timers, and works

for very large sessions, but makes it difficult to provide the

constant low-level stream of feedback needed to perform congestion

control.

o AAP [Ha99] uses exponentially distributed random timers and is

effective for large sessions without needing to compute the RTT to

each receiver.

o PGM [FLST98] and LMS [PPV98] use additional mechanisms in routers

to suppress duplicate NACKs. In the case of PGM, router

assistance suppliments SRM-stype random timers and localizes the

suppression so that the whole group does not need suppressing.

The most general of these mechanisms is probably exponentially

weighted random timers. Although SRM style timers can reduce

feedback delay, they are harder to use correctly in situations where

all the RTTs are not known, or where the number of respondees is

unknown. In contrast, exponentially weighted random timers work well

across a large range of session sizes with good worst case delay

characteristics.

Either form of random timer based mechanism can be supplemented by

router-support where it is available. Sender triggered NACK

mechanisms (e.g. [HC97]) are more difficult to integrate with

router-based support mechanisms.

4.3. Replication

Some RM protocols can be designed so as to not need explicit

reliability mechanisms except in comparatively rare cases. An

example is in a multicast game, where the position of a moving object

is continuously multicast. This positional stream does not require

additional reliability because a new position superseding the old one

will be sent before any retransmission could take place. However,

when the moving object interacts with other objects or stops moving,

then an explicit reliability mechanism is required to reliably send

the interaction information or last position.

It is not just games that can be built in this manner - the NTE

shared text editor[HC97] uses just such a mechanism with changes to a

line of text. For every change the whole line is sent, and so long

as the user keeps typing no explicit reliability mechanism is needed.

The major advantage of replication is that it is not susceptible to

spatially uncorrelated packet loss. With a traditional ACK or NACK

based protocol, the probability of any particular packet being

received by all the receivers in a large group can be very low. This

leads to high retransmission rates. In contrast, replicated

streams do not suffer as the size of the receiver group increases -

different receivers lose different packets, but this does not

increase network traffic.

4.4. Packet-level Forward Error Correction

Forward Error Correction (FEC) is a well known technique for

protecting data against corruption. For reliable multicast it is

most useful in the form of erasure codes.

The simplest form of packet-level FEC is to take a group of packets

that is to be sent, and to XOR the packets together to form a

newpacket which is also sent. If there were three original packets

plus the XOR packet sent, then if a receiver is missing any one of

the original data packets, but receives the XOR packet, then it can

reproduce the missing original packet.

More general erasure codes exist [BKKKLZ95], [Ri97], [LMSSS97] that

allow the generation of n encoding packets from k original data

packets. In such cases, so long as at least k of the n encoding

packets are received, then the k original data packets can be

reproduced.

To apply FEC the sender groups data packets into rounds, and encoding

packets are produced based on all the data packets in a round. A

round may consist of all data packets in an entire application data

unit in some cases, whereas in other cases it may consist of a group

of data packets that make up only a small portion of an application

data unit.

Using erasure codes to repair packet loss is a significant

improvement over simple retransmission because the dependency on

which packets have been lost is removed. Thus, the amount of repair

traffic required to repair spatially uncorrelated packet loss is

considerably lessened.

We can divide packet-level FEC schemes into two categories: proactive

FEC and reactive FEC. The difference between the two is that for

proactive FEC the sender decides a priori how many encoding packets

to send for each round of data packets, whereas for reactive FEC the

sender initially transmits only the original data packets for each

round. Then, the sender uses feedback from the receivers to compute

how many packets were lost by the receiver that experienced the most

loss in each round, and then only that number of additional encoding

packets are sent for that round. These encoding packets will then

also serve to repair loss at the other receivers that are missing

fewer packets. The receivers report via ACKs or NACKs how many

packets are missing from each round. With NACKs, only the receiver

missing the most packets need send a NACK for this round, so this is

used to weight the random timers in the NACK calculation.

Proactive and reactive FEC can be combined, e.g., a certain amount of

proactive FEC can be sent for each round and if there are receivers

that experience more loss than can be overcome by this for some

rounds then they can request and receive additional encoding packets

for these rounds.

FEC is very effective at reducing the repair traffic for packet loss.

However, it requires that the data to be sent to be grouped into

rounds, which can add to end-to-end latency. For bulk-data

applications this is typically not a problem, but this may be an

issue for interactive applications where replication may be a better

solution.

4.5. Layered FEC

An alternative use of packet level FEC is possible when data is

spread across several multicast groups [RVC98], [BLMR98]. In such

cases, the original k data packets are used to generate n encoding

packets, where n is much larger than k. The n encoded packets are

then striped across multiple multicast groups. When a receiver

wishes to receive the original data it joins one or more of the

multicast groups, and receives the encoding packets. Once it has

received k different encoding packets, the receiver can then leave

all the multicast groups and reconstruct the original data.

The primary importance of such a layering is that it allows different

receivers to be able to receive the traffic at different rates

according to the available capacity. Such schemes do not require any

form of feedback from the receivers to the sender to ensure good

throughput, and therefore the need for good throughput does not

constrain the size of the receiver set. However, to perform adequate

network congestion control using receiver joins and leaves in this

manner may require coordination between members that are behind the

same congested link from the sender. As described in the next

section, [RVC98] suggests such a layered congestion control scheme.

5. Congestion Control Mechanisms

The basic delivery model of the Internet is best-effort service. No

guarantees are given as to throughput, delay or packet loss. End-

systems are expected to be adaptive, and to reduce their transmission

rate to a level appropriate for the congestion state of the network.

Although increasingly the Internet will start to support reserved

bandwidth and differentiated service classes for specialist

applications, unless an end-system knows explicitly that it has

reserved bandwidth, it must still perform congestion control.

Broadly speaking, there are five classes of single-sender multicast

congestion control solution:

o Sender-controlled, one group.

A single multicast group is used for data distribution. Feedback

from the group members is used to control the rate of this group.

The goal is to transmit at a rate dictated by the slowest

receiver.

o Sender-controlled, multiple groups.

One initial multicast group is adaptively subdivided into multiple

subgroups with subdivisions centered on congestion points in the

network. Application-level relays buffer data from a group nearer

the original sender, and retransmit it at a slower rate into a

group further from the original sender. In this way, different

receivers can receiver the data at different rates. Sender-based

congestion control takes place between the members of a subgroup

and their relay.

o Receiver-controlled, one group.

A single multicast group is used for data distribution. The

receivers determine if the sender is transmitting too rapidly for

the current congestion state of the network, and they leave the

group if this is the case.

o Receiver-controlled, layered organization.

A layered approach for how to combine this scheme with a

congestion control protocol that requires no receiver feedback is

described in [RVC98]. The sender stripes data across multiple

multicast groups simultaneously. Receivers join and leave these

layered groups depending on their measurements of the congestion

state of the network, so that the amount of data being received is

always appropriate. However, this scheme relies on receivers to

join and leave the different multicast groups in a coordinated

fashion behind a bottleneck link, and it has not yet been

completely confirmed that this approach will scale in practice to

the Internet. As a result, more work on this congestion control

mechanism would be beneficial.

o Router-based congestion control.

It is possible to add additional mechanisms to multicast routers

to assist in multicast congestion control. Such mechanisms could

include:

o Conditional joins (a multicast join that specifies a loss rate

above which it is acceptable for the router to reject the

join).

o Router filtering of traffic that exceeds a reasonable rate.

This may include mechanisms for filtering traffic at different

points in the network at different rates depending on local

congestion conditions [LVS99].

o Fair queuing schemes combined with end-to-end adaptation.

Router-based schemes generally require more state in network

routers than has traditionally been acceptable for backbone

routers. Thus, in the near-term, such schemes are only likely to

be applicable for intranet solutions.

For reliable multicast protocols, it is important to consider

congestion control at the same time as reliability is being

considered. The same mechanisms that are used to provide reliability

will sometimes be used to provide congestion control.

In the case of receiver-based congestion control, open-loop delivery

using FEC is the likely choice for achieving good throughput for

bulk- data transfer. This is because open-loop delivery requires no

feedback from receivers, and thus it is a perfect match with a

receiver-based congestion-control mechanism that operates without

feedback from receivers.

6. Security Considerations

Generally speaking, security considerations have relatively little

effect on constraining the design space for reliable multicast

protocols. The primary issues constraining the design space are all

related to receiver-set scaling. For authentication of the source

and of data integrity, receiver-set scaling is not a significant

issue. However, for data encryption, key distribution and

particularly re-keying may be significantly affected by receiver-set

scaling. Tree and graph based re-keying solutions[WHA98,WGL97] would

appear to be appropriate solutions to these problems. It is not

clear however that such re-keying solutions need to directly affect

the design of the data distribution part of a reliable multicast

protocol.

The primary question to consider for the security of reliable

multicast protocols is the role of third-parties. If nodes other

than the original source of the data are allowed to send or resend

data packets, then the security model for the protocol must take this

into account. In particular, it must be clear whether such third

parties are trusted or untrusted. A requirement for trusted third

parties can make protocols difficult to deploy on the Internet.

Untrusted third parties (such as receivers that retransmit the data)

may be used so long as the data authentication mechanisms take this

into account. Typically this means that the original sender

digitally signs and timestamps the data, and that the third parties

resend this signed timestamped payload unmodified.

Unlike unicast protocols, denial-of-service attacks on multicast

transport state are easy if the protocol design does not take such

attacks into account. This is because any receiver can join the

session, and can then produce feedback that influences the progress

of a session involving many other receivers. Hence protection

against denial-of-service attacks on reliable multicast protocols

must be carefully considered. A receiver that requests

retransmission of every packet, or that refuses to acknowledge

packets in an ACK-based protocol can potentially bring a reliable

multicast session to a standstill. Senders must have appropriate

policy to deal with such conditions, and if necessary, evict the

receiver from the group. A single receiver masquerading as a large

number of receivers may still be an issue under such circumstances

with protocols that support NACK-like functionality. Providing

unique "keys" to each NACKer when they first NACK using a unicast

response might potentially prevent such attacks.

Denial-of-service attacks caused by traffic flooding are however

somewhat easier to protect against than with unicast. Unwanted

senders can simply be pruned from the distribution tree using the

mechanisms implemented in IGMP v3[CDT99].

7. Conclusions

In this document we present an overview of the design space for

reliable multicast within the context of one-to-many bulk-data

transfer. Other flavors of multicast application are not considered

in this document, and hence the overview given should not be

considered inclusive of the design space for protocols that fall

outside the context of one-to-many bulk-data transfer. During the

course of this overview, we have reaffirmed the notion that the

process of reliable multicast protocol design is affected by a number

of factors that render the generation of a "one size fits all

solution" moot. These factors are then described to show how an

application's needs serve to constrain the set of available

techniques that may be used to create a reliable multicast protocol.

We examined a number of basic techniques and to show how well they

can meet the needs of certain types of applications.

This document is intended to provide guidance to the IETF community

regarding the standardization of reliable multicast protocols for

bulk-data transfer. Given the degree to which application

requirements constrain reliable multicast solutions, and the diverse

set of applications that need to be supported, it should be clear

that any standardization work should take great pains to be future-

proof. This would seem to imply not standardizing complete reliable

multicast transport protocols in one pass, but rather examining the

degree to which such protocols are separable into functional building

blocks, and standardizing these blocks separately to the maximum

degree that makes sense. Such an approach allows for protocol

evolution, and allows applications with new constraints to be

supported with maximal reuse of existing and tested mechanisms.

8. Acknowledgments

This document represents an overview of the reliable multicast design

space. The ideas presented are not those of the authors, but are

collected from the varied presentations and discussions in the IRTF

Reliable Multicast Research Group. Although they are too numerous to

list here, we thank everyone who has participated in these

discussions for their contributions.

9. Authors' Addresses

Mark Handley

ATT Center for Internet Research at ICSI,

International Computer Science Institute,

1947 Center Street, Suite 600,

Berkeley, CA 94704, USA

EMail: mjh@aciri.org

Sally Floyd

ATT Center for Internet Research at ICSI,

International Computer Science Institute,

1947 Center Street, Suite 600,

Berkeley, CA 94704, USA

EMail: floyd@aciri.org

Brian Whetten

Talarian Corporation,

333 Distel Circle,

Los Altos, CA 94022, USA

EMail: whetten@talarian.com

Roger Kermode

Motorola Australian Research Centre

Level 3, 12 Lord St,

Botany NSW 2019,

Australia

EMail: Roger.Kermode@motorola.com

Lorenzo Vicisano

Cisco Systems,

170 West Tasman Dr.

San Jose, CA 95134, USA

EMail: lorenzo@cisco.com

Michael Luby

Digital Fountain, Inc.

600 Alabama Street

San Francisco, CA 94110

EMail: luby@digitalfountain.com

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