| Rfc | 5693 |
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| Title | Application-Layer Traffic Optimization (ALTO) Problem Statement |
|---|
| Author | J.
Seedorf, E. Burger |
|---|
| Date | October 2009 |
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| Format: | TXT, HTML |
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| Status: | INFORMATIONAL |
|---|
|
Network Working Group J. Seedorf
Request for Comments: 5693 NEC
Category: Informational E. Burger
Neustar Inc.
October 2009
Application-Layer Traffic Optimization (ALTO) Problem Statement
Abstract
Distributed applications -- such as file sharing, real-time
communication, and live and on-demand media streaming -- prevalent on
the Internet use a significant amount of network resources. Such
applications often transfer large amounts of data through connections
established between nodes distributed across the Internet with little
knowledge of the underlying network topology. Some applications are
so designed that they choose a random subset of peers from a larger
set with which to exchange data. Absent any topology information
guiding such choices, or acting on suboptimal or local information
obtained from measurements and statistics, these applications often
make less than desirable choices.
This document discusses issues related to an information-sharing
service that enables applications to perform better-than-random peer
selection.
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.
Copyright Notice
Copyright (c) 2009 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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the Trust Legal Provisions and are provided without warranty as
described in the BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Overview . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2. State-of-the-Art . . . . . . . . . . . . . . . . . . . . . 4
2. Definitions . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. The Problem . . . . . . . . . . . . . . . . . . . . . . . . . 7
4. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . . 8
4.1. File sharing . . . . . . . . . . . . . . . . . . . . . . . 8
4.2. Cache/Mirror Selection . . . . . . . . . . . . . . . . . . 8
4.3. Live Media Streaming . . . . . . . . . . . . . . . . . . . 8
4.4. Real-Time Communications . . . . . . . . . . . . . . . . . 9
4.5. Distributed Hash Tables . . . . . . . . . . . . . . . . . 9
5. Aspects of the Problem . . . . . . . . . . . . . . . . . . . . 9
5.1. Information Provided by an ALTO Service . . . . . . . . . 9
5.2. ALTO Service Providers . . . . . . . . . . . . . . . . . . 10
5.3. ALTO Service Implementation . . . . . . . . . . . . . . . 10
5.4. User Privacy . . . . . . . . . . . . . . . . . . . . . . . 10
5.5. Topology Hiding . . . . . . . . . . . . . . . . . . . . . 11
5.6. Coexistence with Caching . . . . . . . . . . . . . . . . . 11
6. Security Considerations . . . . . . . . . . . . . . . . . . . 11
7. Contributors . . . . . . . . . . . . . . . . . . . . . . . . . 12
8. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 12
9. Informative References . . . . . . . . . . . . . . . . . . . . 13
1. Introduction
1.1. Overview
Distributed applications, both peer-to-peer (P2P) and client/server
used for file sharing, real-time communication, and live and on-
demand media streaming, use a significant amount of network capacity
and CPU cycles in the routers [WWW.wired.fuel]. In contrast to
centralized applications, distributed applications access resources
such as files or media relays distributed across the Internet and
exchange large amounts of data in connections that they establish
directly with nodes sharing such resources.
One advantage of highly distributed systems results from the fact
that the resources such systems offer are often available through
multiple replicas. However, applications generally do not have
reliable information of the underlying network and thus have to
select among the available peers that provide such replicas randomly
or based on information they deduce from partial observations that,
in some situations, lead to suboptimal choices. For example, one
peer-selection algorithm is based only on the measurements during
initial connection establishment between two peers. Since actual
data transmission does not begin, the algorithm measures only the
round-trip time and cannot reliably deduce actual throughput between
the peers. Thus, such a peer-selection algorithm that simply uses
round-trip time may result in a suboptimal choice of peers.
Many of today's P2P systems use an overlay network consisting of
direct peer connections. Such connections often do not account for
the underlying network topology. In addition to having suboptimal
performance, such networks can lead to congestion and cause serious
inefficiencies. As shown in [ACM.fear], traffic generated by popular
P2P applications often cross network boundaries multiple times,
overloading links that are frequently subject to congestion
[ACM.bottleneck]. Moreover, such transits, besides resulting in a
poor experience for the user, can be quite costly to the network
operator.
Recent studies ([ACM.ispp2p], [WWW.p4p.overview], [ACM.ono]) show a
possible solution to this problem. Internet Service Providers
(ISPs), network operators, or third parties can collect more reliable
network information. This information includes relevant information
such as topology or link capacity. Normally, such information
changes on a much longer time scale than information used for
congestion control on the transport layer. Providing this
information to P2P applications can enable them to apply better-than-
random peer selection with respect to the underlying network
topology. As a result, it may be possible to increase application
performance, reduce congestion, and decrease the overall amount of
traffic across different networks. Presumably, both applications and
the network operator can benefit from such information. Thus,
network operators have an incentive to provide, either directly
themselves or indirectly through a third party, such information;
applications have an incentive to use such information. This
document discusses issues related to an information-sharing service
that enables applications to perform better-than-random peer
selection.
Section 2 provides definitions. Section 3 introduces the problem.
Section 4 describes some use cases where both P2P applications and
network operators benefit from a solution to such a problem.
Section 5 describes the main issues to consider when designing such a
solution. Note a companion document to this document, "Application-
Layer Traffic Optimization (ALTO) Requirements" [ALTO-REQS], goes
into the details of these issues.
1.2. State-of-the-Art
The papers [ACM.ispp2p], [PATH-SEL], and [WWW.p4p.overview] present
examples of contemporary solution proposals that address the problem
described in this document. Moreover, these proposals have
encouraging simulation and field test results. These and similar,
independent, solutions all consist of two essential parts:
o a discovery mechanism that a P2P application uses to find a
reliable information source, and
o a protocol that P2P applications use to query such sources in
order to retrieve the information needed to perform better-than-
random selection of the endpoints providing a desired resource.
It is not clear how such solutions will perform if deployed globally
on the Internet. However, wide adoption is unlikely without
agreement on a common solution, based upon an open standard.
2. Definitions
The following terms have special meaning in the definition of the
Application-Layer Traffic Optimization (ALTO) problem.
Application: A distributed communication system (e.g., file sharing)
that uses the ALTO service to improve its performance or quality
of experience while improving resource consumption in the
underlying network infrastructure. Applications may use the P2P
model to organize themselves, use the client-server model, or use
a hybrid of both (i.e., a mixture between the P2P model and the
client-server model).
Peer: A specific participant in an application. Colloquially, a
peer refers to a participant in a P2P network or system, and this
definition does not violate that assumption. If the basis of the
application is the client-server or hybrid model, then the usage
of the terms "client" and "server" disambiguates the peer's role.
P2P: Peer-to-Peer.
Resource: Content (such as a file or a chunk of a file) or a server
process (for example, to relay a media stream or perform a
computation) that applications can access. In the ALTO context, a
resource is often available in several equivalent replicas. In
addition, different peers share these resources, often
simultaneously.
Resource Identifier: An application-layer identifier used to
identify a resource, no matter how many replicas exist.
Resource Provider: For P2P applications, a resource provider is a
specific peer that provides some resources. For client-server or
hybrid applications, a provider is a server that hosts a resource.
Resource Consumer: For P2P applications, a resource consumer is a
specific peer that needs to access resources. For client-server
or hybrid applications, a consumer is a client that needs to
access resources.
Transport Address: All address information that a resource consumer
needs to access the desired resource at a specific resource
provider. This information usually consists of the resource
provider's IP address and possibly other information, such as a
transport protocol identifier or port numbers.
Overlay Network: A virtual network consisting of direct connections
on top of another network and established by a group of peers.
Resource Directory: An entity that is logically separate from the
resource consumer and that assists the resource consumer to
identify a set of resource providers. Some P2P applications refer
to the resource directory as a P2P tracker.
ALTO Service: Several resource providers may be able to provide the
same resource. The ALTO service gives guidance to a resource
consumer and/or resource directory about which resource
provider(s) to select in order to optimize the client's
performance or quality of experience, while improving resource
consumption in the underlying network infrastructure.
ALTO Server: A logical entity that provides interfaces to the
queries to the ALTO service.
ALTO Client: The logical entity that sends ALTO queries. Depending
on the architecture of the application, one may embed it in the
resource consumer and/or in the resource directory.
ALTO Query: A message sent from an ALTO client to an ALTO server; it
requests guidance from the ALTO service.
ALTO Response: A message that contains guiding information from the
ALTO service as a reply to an ALTO query.
ALTO Transaction: A transaction that consists of an ALTO query and
the corresponding ALTO response.
Local Traffic: Traffic that stays within the network infrastructure
of one Internet Service Provider (ISP). This type of traffic
usually results in the least cost for the ISP.
Peering Traffic: Internet traffic exchanged by two Internet Service
Providers whose networks connect directly. Apart from
infrastructure and operational costs, peering traffic is often
free to the ISPs, within the contract of a peering agreement.
Transit Traffic: Internet traffic exchanged on the basis of economic
agreements amongst Internet Service Providers (ISPs). An ISP
generally pays a transit provider for the delivery of traffic
flowing between its network and remote networks to which the ISP
does not have a direct connection.
Application Protocol: A protocol used by the application for
establishing an overlay network between the peers and exchanging
data on it, as well as for data exchange between peers and
resource directories, if applicable. These protocols play an
important role in the overall ALTO architecture. However,
defining them is out of the scope of the ALTO WG.
ALTO Client Protocol: The protocol used for sending ALTO queries and
ALTO replies between an ALTO client and ALTO server.
Provisioning Protocol: A protocol used for populating the ALTO
server with information.
+------+
+-----+ | Peers
+-----+ +------+ +=====| |-*-+
| |.......| |====+ +-*-*-+ *
+-----+ +------+ | * *****
Source of ALTO | *
Information Server | +-*---+
+=====| | Resource Directory
+-----+ (Tracker, proxy)
Legend:
=== ALTO client protocol
*** Application protocol (out of scope)
... Provisioning or initialization (out of scope)
Figure 1: Overview of Protocol Interaction between ALTO Elements
Figure 1 shows the scope of the ALTO client protocol: peers or
resource directories can use such a protocol as ALTO clients to query
an ALTO server. The mapping of topological information onto an ALTO
service as well as the application protocol interaction between peers
and resource directories are out of scope for the ALTO client
protocol.
3. The Problem
Network engineers have been facing the problem of traffic
optimization for a long time and have designed mechanisms like MPLS
[RFC3031] and Diffserv [RFC3260] to deal with it. The problem these
protocols address consists in finding (or setting) optimal routes (or
optimal queues in routers) for packets traveling between specific
source and destination addresses. Solutions are based on
requirements such as low latency, high reliability, and priority.
Such solutions are usually implemented at the link and network layers
and tend to be almost transparent.
However, distributed applications in general and, in particular,
bandwidth-greedy P2P applications that are used, for example, for
file sharing, cannot directly use the aforementioned techniques. By
cooperating with external services that are aware of the network
topology, applications could greatly improve the traffic they
generate. In fact, when a P2P application needs to establish a
connection, the logical target is not a stable host, but rather a
resource (e.g., a file or a media relay) that can be available in
multiple instances on different peers. Selection of a good host from
an overlay topological proximity has a large impact on the overall
traffic generated.
Note that while traffic considerations are important, several
other factors also play a role on the performance experienced by
users of distributed applications. These include the need to
avoid overloading individual nodes, fetching rare pieces of a file
before those pieces are available at a multiplicity of nodes, and
so on. However, better information about topological conditions
does improve the overall selection algorithm on an important
aspect.
Better-than-random peer selection is helpful in the initial phase of
the process. Consider a P2P protocol in which a querying peer
receives a list of candidate destinations where a resource resides.
From this list, the peer will derive a smaller set of candidates to
connect to and exchange information with. In another example, a
streaming video client may be provided with a list of destinations
from which it can stream content. In both cases, the use of topology
information in an early stage will allow applications to improve
their performance and will help ISPs make a better use of their
network resources. In particular, an economic goal for ISPs is to
reduce the transit traffic on interdomain links.
Addressing the Application-Layer Traffic Optimization (ALTO) problem
means, on the one hand, deploying an ALTO service to provide
applications with information regarding the underlying network and,
on the other hand, enhancing applications in order to use such
information to perform better-than-random selection of the endpoints
with which they establish connections.
4. Use Cases
4.1. File sharing
File-sharing applications allow users to search for content shared by
other users and to download respective resources from other users.
For instance, search results can consist of many instances of the
same file (or chunk of a file) available from multiple sources. The
goal of an ALTO solution is to help peers find the best ones
according to the underlying networks.
On the application side, integration of ALTO functionalities may
happen at different levels. For example, in the completely
decentralized Gnutella network, selection of the best sources is
totally up to the user. In systems like BitTorrent and eDonkey,
central elements such as trackers or servers act as mediators.
Therefore, in the former case, improvement would require modification
in the applications, while in the latter it could just be implemented
in some central elements.
4.2. Cache/Mirror Selection
Providers of popular content, like media and software repositories,
usually resort to geographically distributed caches and mirrors for
load balancing. Today, selection of the proper mirror/cache for a
given user is based on inaccurate geolocation data, on proprietary
network-location systems, or is often delegated to the user herself.
An ALTO solution could be easily adopted to ease such a selection in
an automated way.
4.3. Live Media Streaming
P2P applications for live streaming allow users to receive multimedia
content produced by one source and targeted to multiple destinations,
in a real-time or near-real-time way. This is particularly important
for users or networks that do not support multicast. Peers often
participate in the distribution of the content, acting as both
receivers and senders. The goal of an ALTO solution is to help a
peer to find effective communicating peers that exchange the media
content.
4.4. Real-Time Communications
P2P real-time communications allow users to establish direct media
flows for real-time audio, video, and real-time text calls or to have
text chats. In the basic case, media flows directly between the two
endpoints. Unfortunately, however, a significant portion of users
have limited access to the Internet due to NATs, firewalls, or
proxies. Thus, other elements need to relay the media. Such media
relays are distributed over the Internet with public addresses. An
ALTO solution needs to help peers find the best relays.
4.5. Distributed Hash Tables
Distributed hash tables (DHTs) are a class of overlay algorithms used
to implement lookup functionalities in popular P2P systems, without
using centralized elements. In such systems, a peer maintains the
addresses of a set of other peers participating in the same DHT in a
routing table, sorted according to specific criteria. An ALTO
solution can provide valuable information for DHT algorithms.
5. Aspects of the Problem
This section introduces some aspects of the problem that some people
may not be aware of when they first start studying the problem space.
5.1. Information Provided by an ALTO Service
The goal of an ALTO service is to provide applications with
information they can use to perform better-than-random peer
selection. In principle, there are many types of information that
can help applications in peer selection. However, not all of the
information to be conveyed is amenable to an ALTO-like service. More
specifically, information that can change very rapidly, such as
transport-layer congestion, is out of scope for an ALTO service.
Such information is better suited to be transferred through an in-
band technique at the transport layer instead of an ALTO-like, out-
of-band technique at the application layer. An ALTO solution for
congestion will either have outdated information or must be contacted
too frequently by applications. And finally, information such as
end-to-end delay and available bandwidth can be more accurately
measured by applications, themselves.
The kind of information that is meaningful to convey to applications
via an out-of-band ALTO service is any information that applications
cannot easily obtain themselves and that changes on a much longer
time scale than the instantaneous information used for congestion
control on the transport layer. Examples for such information are
operator's policies, geographical location or network proximity
(e.g., the topological distance between two peers), the transmission
costs associated with sending/receiving a certain amount of data to/
from a peer, or the remaining amount of traffic allowed by a peer's
operator (e.g., in case of quotas or limited flat-rate pricing
models).
5.2. ALTO Service Providers
At least three different kinds of entities can provide ALTO services:
1. Network operators. Network operators usually have full knowledge
of the network they administer and are aware of their network
topology and policies.
2. Third parties. Third parties are entities separate from network
operators but that may either have collected network information
or have arrangements with network operators to learn the network
information. Examples of such entities are content-delivery
networks like Akamai, which control wide and highly distributed
infrastructures, or companies providing an ALTO service on behalf
of ISPs.
3. User communities. User communities run distributed algorithms,
for example, for estimating the topology of the Internet.
5.3. ALTO Service Implementation
It is important for the reader to understand there are significant
user communities that expect an ALTO server to be a centralized
service. Likewise, there are other user communities that expect the
ALTO service be a distributed service, possibly even based on or
integrating with a P2P service.
As a result, one can reasonably expect there to be some sort of
service-discovery mechanism to go along with the ALTO protocol
definition.
5.4. User Privacy
On the one hand, there are data elements an ALTO client could provide
in its query to an ALTO server that could help increase the level of
accuracy in the replies. For example, if the querying client
indicates what kind of application it is using (e.g., real-time
communications or bulk data transfer), the server will be able to
indicate priorities in its replies, accommodating the requirements of
the traffic the application will generate. On the other hand,
applications might consider such information private. In addition,
some applications may not know a priori what kind of request they
will be making.
5.5. Topology Hiding
Operators, with their intimate knowledge of their network topology,
can play an important role in addressing the ALTO problem. However,
operators often consider revealing details of such network
information to be confidential.
5.6. Coexistence with Caching
Caching is an approach to improving traffic generated by
applications, and it requires large amounts of data transfers. In
some cases, such techniques have proven to be extremely effective in
both enhancing user experience and saving network resources.
A cache, either explicitly or transparently, replaces the content
source. Thus, a cache must, in principle, use and support the same
protocol as the querying peer. That is, if a cache stores web
content, it must present an HTTP interface to the web client. Any
cache solution for a given protocol needs to present that same
protocol to the client. Said differently, each caching solution for
a different protocol needs to implement that specific protocol. For
this reason, one can only reasonably expect caching solutions for the
most popular protocols, such as HTTP and BitTorrent.
It is extremely important to realize that caching and ALTO are
entirely orthogonal. ALTO, especially if it is aware of caches, can
in fact direct clients to nearby caches where the user could get a
much better quality of experience.
6. Security Considerations
This document is neither a requirements document nor a protocol
specification. However, we believe it is important for the reader to
understand areas of security and privacy that will be important for
the design and implementation of an ALTO solution. Moreover, issues
such as digital rights management are out of scope for ALTO, as they
are not technically enforceable at this level.
Some environments and use cases of ALTO may require client or server
authentication before providing sensitive information. In order to
support those environments interoperably, the ALTO requirements
document [ALTO-REQS] outlines minimum-to-implement authentication and
other security requirements.
Applications can decide to rely on information provided by an ALTO
server to enhance the peer-selection process. In principle, this
enables the ALTO service that provides such information to influence
the behavior of the application, basically letting a third-party --
the ALTO service provider -- take an important role in a distributed
system it was not previously involved in.
For example, in the case of an ALTO server deployed and run by an
ISP, the P2P community might consider such a server hostile because
the operator could:
o use ALTO to prevent content distribution and enforce copyrights;
o redirect applications to corrupted mediators providing malicious
content;
o track connections to perform content inspection or logging;
o apply policies based on criteria other than network efficiency.
For example, the service provider may suggest routes suboptimal
from the user's perspective in order to avoid peering points
regulated by inconvenient economic agreements.
It is important to note there is no protocol mechanism to require
ALTO for P2P applications. If, for some reason, ALTO fails to
improve the performance of P2P applications, ALTO will not gain
popularity and the P2P community will not use it.
At the time of this writing, the privacy issues described in
Section 5.4 are relevant for an ALTO solution. Users may be
reluctant to disclose sensitive information to an ALTO server.
Operators, on the other hand, may not wish to disclose information
that would expose details of their interior topology. When exploring
the solution space in detail, one needs to consider these issues so
that an ALTO protocol does not presume mandatory information
disclosure, by either clients or servers.
7. Contributors
This document was initially edited by Enrico Marocco and Vijay
Gurbani. In the role of Working Group chairs, they have continued to
provide significant edits and inputs to the current authors.
8. Acknowledgments
Vinay Aggarwal and the P4P working group conducted the research work
done outside the IETF. Emil Ivov, Rohan Mahy, Anthony Bryan,
Stanislav Shalunov, Laird Popkin, Stefano Previdi, Reinaldo Penno,
Dimitri Papadimitriou, Sebastian Kiesel, Greg DePriest, and many
others provided insightful discussions, specific comments, and much
needed corrections.
Jan Seedorf and Sebastian Kiesel are partially supported by the NAPA-
WINE project (Network-Aware P2P-TV Application over Wise Networks,
http://www.napa-wine.org), a research project supported by the
European Commission under its 7th Framework Program (contract no.
214412). The views and conclusions contained herein are those of the
authors and should not be interpreted as necessarily representing the
official policies or endorsements, either expressed or implied, of
the NAPA-WINE project or the European Commission.
Thanks in particular to Richard Yang for several reviews.
9. Informative References
[ACM.bottleneck]
Akella, A., Seshan, S., and A. Shaikh, "An Empirical
Evaluation of WideArea Internet Bottlenecks",
Proceedings of ACM SIGCOMM, October 2003.
[ACM.fear]
Karagiannis, T., Rodriguez, P., and K. Papagiannaki,
"Should ISPs fear Peer-Assisted Content Distribution?",
ACM USENIX IMC, Berkeley 2005.
[ACM.ispp2p]
Aggarwal, V., Feldmann, A., and C. Scheideler, "Can ISPs
and P2P systems co-operate for improved performance?",
ACM SIGCOMM Computer Communications Review (CCR), 37:3,
pp. 29-40.
[ACM.ono] Choffnes, D. and F. Bustamante, "Taming the Torrent: A
practical approach to reducing cross-ISP traffic in P2P
systems", Proceedings of ACM SIGCOMM, August 2008.
[ALTO-REQS]
Kiesel, S., Popkin, L., Previdi, S., Woundy, R., and Y.
Yang, "Application-Layer Traffic Optimization (ALTO)
Requirements", Work in Progress, April 2009.
[PATH-SEL]
Saucez, D. and B. Donnet, "The case for an informed path
selection service", Work in Progress, February 2008.
[RFC3031] Rosen, E., Viswanathan, A., and R. Callon, "Multiprotocol
Label Switching Architecture", RFC 3031, January 2001.
[RFC3260] Grossman, D., "New Terminology and Clarifications for
Diffserv", RFC 3260, April 2002.
[WWW.p4p.overview]
Xie, H., Krishnamurthy, A., Silberschatz, A., and R. Yang,
"P4P: Explicit Communications for Cooperative Control
Between P2P and Network Providers",
<http://www.dcia.info/documents/P4P_Overview.pdf>.
[WWW.wired.fuel]
Glasner, J., "P2P Fuels Global Bandwidth Binge",
April 2005, <http://www.wired.com>.
Authors' Addresses
Jan Seedorf
NEC Laboratories Europe, NEC Europe Ltd.
Kurfuersten-Anlage 36
Heidelberg 69115
Germany
Phone: +49 (0) 6221 4342 221
EMail: jan.seedorf@nw.neclab.eu
URI: http://www.nw.neclab.eu
Eric W. Burger
Neustar Inc.
46000 Center Oak Plaza
Sterling, VA 20166-6579
USA
Phone:
Fax: +1 530 267 7447
EMail: eburger@standardstrack.com
URI: http://www.standardstrack.com