A Survey on Research on the Application-Layer Traffic Optimization (ALTO) Problem
RFC 6029
| Document | Type | RFC - Informational (October 2010) Errata | |
|---|---|---|---|
| Authors | Enrico Marocco , Marco Tomsu , Volker Hilt , Ivica Rimac , Vijay K. Gurbani | ||
| Last updated | 2020-01-21 | ||
| Replaces | draft-rimac-p2prg-alto-survey | ||
| RFC stream | Internet Research Task Force (IRTF) | ||
| Formats | |||
| Stream | IRTF state | (None) | |
| Consensus boilerplate | Unknown | ||
| Document shepherd | (None) | ||
| IESG | IESG state | RFC 6029 (Informational) | |
| Action Holders |
(None)
|
||
| Telechat date | (None) | ||
| Responsible AD | Peter Saint-Andre | ||
| Send notices to | (None) |
RFC 6029
Internet Research Task Force (IRTF) I. Rimac
Request for Comments: 6029 V. Hilt
Category: Informational M. Tomsu
ISSN: 2070-1721 V. Gurbani
Bell Labs, Alcatel-Lucent
E. Marocco
Telecom Italia
October 2010
A Survey on Research on
the Application-Layer Traffic Optimization (ALTO) Problem
Abstract
A significant part of the Internet traffic today is generated by
peer-to-peer (P2P) applications used originally for file sharing, and
more recently for real-time communications and live media streaming.
Such applications discover a route to each other through an overlay
network with little knowledge of the underlying network topology. As
a result, they may choose peers based on information deduced from
empirical measurements, which can lead to suboptimal choices. This
document, a product of the P2P Research Group, presents a survey of
existing literature on discovering and using network topology
information for Application-Layer Traffic Optimization.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Research Task Force
(IRTF). The IRTF publishes the results of Internet-related research
and development activities. These results might not be suitable for
deployment. This RFC represents the consensus of the Peer-to-Peer
Research Group of the Internet Research Task Force (IRTF). Documents
approved for publication by the IRSG are not a candidate for any
level of Internet Standard; see Section 2 of RFC 5741.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc6029.
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RFC 6029 ALTO Survey October 2010
Copyright Notice
Copyright (c) 2010 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
(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Terminology . . . . . . . . . . . . . . . . . . . . . . . 4
2. Survey of Existing Literature . . . . . . . . . . . . . . . . 4
2.1. Application-Level Topology Estimation . . . . . . . . . . 5
2.2. Topology Estimation through Layer Cooperation . . . . . . 8
2.2.1. P4P Architecture . . . . . . . . . . . . . . . . . . . 9
2.2.2. Oracle-Based ISP-P2P Collaboration . . . . . . . . . . 9
2.2.3. ISP-Driven Informed Path Selection (IDIPS) Service . . 10
3. Application-Level Topology Estimation and the ALTO Problem . . 10
4. Open Issues . . . . . . . . . . . . . . . . . . . . . . . . . 12
4.1. Coordinate Estimation or Path Latencies? . . . . . . . . . 12
4.2. Malicious Nodes . . . . . . . . . . . . . . . . . . . . . 12
4.3. Information Integrity . . . . . . . . . . . . . . . . . . 12
4.4. Richness of Topological Information . . . . . . . . . . . 13
4.5. Hybrid Solutions . . . . . . . . . . . . . . . . . . . . . 13
4.6. Negative Impact of Over-Localization . . . . . . . . . . . 13
5. Security Considerations . . . . . . . . . . . . . . . . . . . 14
6. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 14
7. Informative References . . . . . . . . . . . . . . . . . . . . 14
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1. Introduction
A significant part of today's Internet traffic is generated by peer-
to-peer (P2P) applications, used originally for file sharing, and
more recently for real-time multimedia communications and live media
streaming. P2P applications pose serious challenges to the Internet
infrastructure; by some estimates, P2P systems are so popular that
they make up anywhere between 40% and 85% of the entire Internet
traffic [Karagiannis], [LightReading], [LinuxReviews], [Parker],
[Glasner].
P2P systems ensure that popular content is replicated at multiple
instances in the overlay. But perhaps ironically, a peer searching
for that content may ignore the topology of the latent overlay
network and instead select among available instances based on
information it deduces from empirical measurements, which in some
particular situations may lead to suboptimal choices. For example, a
shorter round-trip time estimation is not indicative of the bandwidth
and reliability of the underlying links, which have more of an
influence than delay for large file transfer P2P applications.
Most Distributed Hash Tables (DHT) -- the data structures that impose
a specific ordering for P2P overlays -- use greedy forwarding
algorithms to reach their destination, making locally optimal
decisions that may not turn out to be globally optimized [Gummadi].
This naturally leads to the Application-Layer Traffic Optimization
(ALTO) problem [RFC5693]: how to best provide the topology of the
underlying network while at the same time allowing the requesting
node to use such information to effectively reach the node on which
the content resides. Thus, it would appear that P2P networks with
their application-layer routing strategies based on overlay
topologies are in direct competition against the Internet routing and
topology.
One way to solve the ALTO problem is to build distributed
application-level services for location and path selection [Francis],
[Ng], [Dabek], [Costa], [Wong], [Madhyastha] in order to enable peers
to estimate their position in the network and to efficiently select
their neighbors. Similar solutions have been embedded into P2P
applications such as Vuze [Vuze]. A slightly different approach is
to have the Internet service provider (ISP) take a proactive role in
the routing of P2P application traffic; the means by which this can
be achieved have been proposed [Aggarwal], [Xie], [Saucez]. There is
an intrinsic struggle between the layers -- P2P overlay and network
underlay -- when performing the same service (routing); however,
there are strategies to mitigate this dichotomy [Seetharaman].
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This document, initially intended as a complement to RFC 5693
[RFC5693] and discussed during the creation of the IETF ALTO Working
Group, has been completed and refined in the IRTF P2P Research Group.
Its goal is to summarize the contemporary research activities on the
Application-Layer Traffic Optimization problem as input to the ALTO
working group protocol designers.
1.1. Terminology
Terminology adopted in this document includes terms such as "ring
geometry", "tree structure", and "butterfly network", borrowed from
P2P scientific literature. [RFC4981] provides an exhaustive
definition of such terminology.
Certain security-related terms are to be understood in the sense
defined in [RFC4949]; such terms include, but are not limited to,
"attack", "authentication", "confidentiality", "encryption",
"identity", and "integrity". Other security-related terms (for
example, "denial of service") are to be understood in the sense
defined in the referenced specifications.
2. Survey of Existing Literature
Gummadi et al. [Gummadi] compare popular DHT algorithms, and besides
analyzing their resilience, provide an accurate evaluation of how
well the logical overlay topology maps on the physical network layer.
In their paper, relying only on measurements independently performed
by overlay nodes without the support of additional location
information provided by external entities, they demonstrate that the
most efficient algorithms in terms of resilience and proximity
performance are those based on the simplest geometric concept (i.e.,
the ring geometry, rather than tree structures, butterfly networks,
and hybrid geometries).
Regardless of the geometrical properties of the distributed data
structures involved, interactions between application-layer overlays
and the underlying networks are a rich area of investigation. The
available literature in this field can be divided into two categories
(Figure 1): using application-level techniques to estimate topology,
and using some kind of layer cooperation to estimate topology.
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Application-layer traffic optimization
|
+--> Application-level topology estimation
| |
| +--> Coordinates-based systems
| | |
| | +--> GNP
| | |
| | +--> Vivaldi
| | |
| | +--> PIC
| |
| +--> Path selection services
| | |
| | +--> IDMaps
| | |
| | +--> Meridian
| | |
| | +--> Ono
| |
| +--> Link-layer Internet maps
| |
| +--> iPlane
|
+--> Topology estimation through layer cooperation
|
+--> P4P: Provider portal for applications
|
+--> Oracle-based ISPs and P2P cooperation
|
+--> ISP-driven informed path selection
Figure 1: Taxonomy of Solutions for the Application-Layer Traffic
Optimization Problem
2.1. Application-Level Topology Estimation
Estimating network topology information on the application layer has
been an area of active research. Early systems used triangulation
techniques to bound the distance between two hosts using a common
landmark host. In such a technique, given a cost function C, a set
of vertexes V and their corresponding edges, the triangle inequality
holds if for any triple {a, b, c} in V, C(a, c) is always less than
or equal to C(a, g) + C(b, c). The cost function C could be
expressed in terms of desirable metrics such as bandwidth or latency.
We note that the techniques presented in this section are only
representative of the sizable research in this area. Rather than
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trying to enumerate an exhaustive list, we have chosen certain
techniques because they represent an advance in the area that further
led to derivative works.
Francis et al. proposed IDMaps [Francis], a system where one or more
special hosts called tracers are deployed near an autonomous system.
The distance measured in round-trip time (RTT) between hosts A and B
is estimated as the cumulative distance between A and its nearest
tracer Ta, plus the distance between B and its nearest tracer Tb,
plus the shortest distance from Ta to Tb. To aid in scalability
beyond that provided by the client-server design of IDMaps, Ng
et al. proposed a P2P-based Global Network Positioning (GNP)
architecture [Ng]. GNP was a network coordinate system based on
absolute coordinates computed from modeling the Internet as a
geometric space. It proposed a two-part architecture: in the first
part, a small set of finite distributed hosts called landmarks
compute their own coordinates in a fixed geometric space. In the
second part, a host wishing to participate computes its own
coordinates relative to those of the landmark hosts. Thus, armed
with the computed coordinates, hosts can then determine interhost
distance as soon as they discover each other.
Both IDMaps and GNP require fixed network infrastructure support in
the form of tracers or landmark hosts; this often introduces a single
point of failure and inhibits scalability. To combat this, new
techniques were developed that embedded the network topology in a
low-dimensional coordinate space to enable network distance
estimation through vector analysis. Costa et al. introduced
Practical Internet Coordinates (PIC) [Costa]. While PIC used the
notion of landmark hosts, it did not require explicit network support
to designate specific landmark hosts. Any node whose coordinates
have been computed could act as a landmark host. When a node joined
the system, it probed the network distance to some landmark hosts.
Then, it obtained the coordinates of each landmark host and computed
its own coordinates relative to each landmark host, subject to the
constraint of minimizing the error in the predicted distance and
computed distance.
Like PIC, Vivaldi [Dabek] proposed a fully distributed network
coordinate system without any distinguished hosts. Whenever a node A
communicates with another node B, it measures the RTT to that node
and learns that node's current coordinates. Node A subsequently
adjusts its coordinates such that it is closer to, or further from, B
by computing new coordinates that minimize the squared error. A
Vivaldi node is thus constantly adjusting its position based on a
simulation of interconnected mass springs. Vivaldi is now being used
in the popular P2P application Vuze, and studies indicate that it
scales well to very large networks [Ledlie].
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Network coordinate systems require the embedding of the Internet
topology into a coordinate system. This is not always possible
without errors, which impacts the accuracy of distance estimations.
In particular, it has proved to be difficult to embed the triangular
inequalities found in Internet path distances [Ledlie]. Thus,
Meridian [Wong] abandons the generality of network coordinate systems
and provides specific distance evaluation services. In Meridian,
each node keeps track of a small fixed number of neighbors and
organizes them in concentric rings, ordered by distance from the
node. Meridian locates the closest node by performing a multi-hop
search where each hop exponentially reduces the distance to the
target. Although less general than virtual coordinates, Meridian
incurs significantly less error for closest node discovery.
The Ono project [Ono] takes a different approach and uses network
measurements from Content Distribution Networks (CDNs) such as Akamai
to find nearby peers. Used as a plugin to the Vuze bittorrent
client, Ono provides 31% average download rate improvement [Su].
Comparison of application-level topology estimation techniques, as
reported in literature. Results in terms of number of (D)imensions
and (L)andmarks, 90th percentile relative error.
+----------------+---------------+----------------+-----------------+
| GNP vs. | PIC(b) vs. | Vivaldi vs. | Meridian vs. |
| IDMaps(a) (7D, | GNP (8D, 16L) | GNP (2D, 32L) | GNP (8D, 15L) |
| 15L) | | | |
+----------------+---------------+----------------+-----------------+
| GNP: 0.50, | PIC: 0.38, | Vivaldi: 0.65, | Meridian: 0.78, |
| IDMaps: 0.97 | GNP: 0.37 | GNP: 0.65 | GNP: 1.18 |
+----------------+---------------+----------------+-----------------+
(a) Does not use dimensions or landmarks.
(b) Uses results from the hybrid strategy for PIC.
Table 1
Table 1 summarizes the application-level topology estimation
techniques. The salient performance metric is the relative error.
While all approaches define this metric a bit differently, it can be
generalized as how close a predicted distance comes to the
corresponding measured distance. A value of zero implies perfect
prediction, and a value of 1 implies that the predicted distance is
in error by a factor of two. PIC, Vivaldi, and Meridian compare
their results with that of GNP, while GNP itself compares its results
with a precursor technique, IDMaps. Because each of the techniques
uses a different Internet topology and a varying number of landmarks
and dimensions to interpret the data set, it is impossible to
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normalize the relative error across all techniques uniformly. Thus,
we present the relative error data in pairs, as reported in the
literature describing the specific technique. Readers are urged to
compare the relative error performance in each column on its own and
not draw any conclusions by comparing the data across columns.
Most of the work on estimating topology information focuses on
predicting network distance in terms of latency and does not provide
estimates for other metrics such as throughput or packet loss rate.
However, for many P2P applications latency is not the most important
performance metric, and these applications could benefit from a
richer information plane. Sophisticated methods of active network
probing and passive traffic monitoring are generally very powerful
and can generate network statistics indirectly related to performance
measures of interest, such as delay and loss rate on link-level
granularity. Extraction of these hidden attributes can be achieved
by applying statistical inference techniques developed in the field
of inferential network monitoring or network tomography subsequent to
sampling of the network state. Thus, network tomography enables the
extraction of a richer set of topology information, but at the same
time inherently increases complexity of a potential information plane
and introduces estimation errors. For both active and passive
methods, statistical models for the measurement process need to be
developed, and the spatial and temporal dependence of the
measurements should be assessed. Moreover, measurement methodology
and statistical inference strategy must be considered jointly. For a
deeper discussion of network tomography and recent developments in
the field, we refer the reader to [Coates].
One system providing such a service is iPlane [Madhyastha], which
aims at creating an annotated atlas of the Internet that contains
information about latency, bandwidth, capacity, and loss rate. To
determine features of the Internet topology, iPlane bridges and
builds upon different ideas, such as active probing based on packet
dispersion techniques to infer available bandwidth along path
segments. These ideas are drawn from different fields, including
network measurement as described by Dovrolis et al. in [Dovrolis] and
network tomography [Coates].
2.2. Topology Estimation through Layer Cooperation
Instead of estimating topology information on the application level
through distributed measurements, this information could be provided
by the entities running the physical networks -- usually ISPs or
network operators. In fact, they have full knowledge of the topology
of the networks they administer and, in order to avoid congestion on
critical links, are interested in helping applications to optimize
the traffic they generate. The remainder of this section briefly
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describes three recently proposed solutions that follow such an
approach to address the ALTO problem.
2.2.1. P4P Architecture
The architecture proposed by Xie et al. [Xie] has been adopted by the
Distributed Computing Industry Association (DCIA) P4P working group
[P4P], an open group established by ISPs, P2P software distributors,
and technology researchers, with the dual goal of defining mechanisms
to (1) accelerate content distribution and (2) optimize utilization
of network resources.
The main role in the P4P architecture is played by servers called
"iTrackers", deployed by network providers and accessed by P2P
applications (or, in general, by elements of the P2P system) in order
to make optimal decisions when selecting a peer to which the element
will connect. An iTracker may offer three interfaces:
1. Info: Allows P2P elements (e.g., peers or trackers) to get opaque
information associated to an IP address. Such information is
kept opaque to hide the actual network topology, but can be used
to compute the network distance between IP addresses.
2. Policy: Allows P2P elements to obtain policies and guidelines of
the network, which specify how a network provider would like its
networks to be utilized at a high level, regardless of P2P
applications.
3. Capability: Allows P2P elements to request network providers'
capabilities.
The P4P architecture is under evaluation with simulations,
experiments on the PlanetLab distributed testbed, and in field tests
with real users. Initial simulations and PlanetLab experiment
results [P4P] indicate that improvements in BitTorrent download
completion time and link utilization in the range of 50-70% are
possible. Results observed on Comcast's network during a field test
trial conducted with a modified version of the software used by the
Pando content delivery network (documented in RFC 5632 [RFC5632])
show average improvements in download rate in different scenarios
varying between 57% and 85%, and a 34% to 80% drop in the cross-
domain traffic generated by such an application.
2.2.2. Oracle-Based ISP-P2P Collaboration
In the general solution proposed by Aggarwal et al. [Aggarwal],
network providers offer host servers, called "oracles", that help P2P
users choose optimal neighbors.
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The oracle concept uses the following mechanism: a P2P client sends
the list of potential peers to the oracle hosted by its ISP and
receives a re-arranged peer list, ordered according to the ISP's
local routing policies and preferences. For instance, to keep the
traffic local, the ISP may prefer peers within its network, or it may
pick links with higher bandwidth or peers that are geographically
closer to improve application performance. Once the client has
obtained this ordered list, it has enough information to perform
better-than-random initial peer selection.
Such a solution has been evaluated with simulations and experiments
run on the PlanetLab testbed, and the results show both improvements
in content download time and a reduction of overall P2P traffic, even
when only a subset of the applications actually query the oracle to
make their decisions.
2.2.3. ISP-Driven Informed Path Selection (IDIPS) Service
The solution proposed by Saucez et al. [Saucez] is essentially a
modified version of the oracle-based approach described in
Section 2.2.2, intended to provide a network-layer service for
finding the best source and destination addresses when establishing a
connection between two endpoints in multi-homed environments (which
are common in IPv6 networking). Peer selection optimization in P2P
systems -- the ALTO problem in today's Internet -- can be addressed
by the IDIPS solution as a specific sub-case where the options for
the destination address consist of all the peers sharing a desired
resource, while the choice of the source address is fixed. An
evaluation performed on IDIPS shows that costs for both providing and
accessing the service are negligible.
3. Application-Level Topology Estimation and the ALTO Problem
The application-level techniques described in Section 2.1 provide
tools for peer-to-peer applications to estimate parameters of the
underlying network topology. Although these techniques can improve
application performance, there are limitations of what can be
achieved by operating only on the application level.
Topology estimation techniques use abstractions of the network
topology, which often hide features that would be of interest to the
application. Network coordinate systems, for example, are unable to
detect overlay paths shorter than the direct path in the Internet
topology. However, these paths frequently exist in the Internet
[Wang]. Similarly, application-level techniques may not accurately
estimate topologies with multipath routing.
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When using network coordinates to estimate topology information, the
underlying assumption is that distance in terms of latency determines
performance. However, for file sharing and content distribution
applications, there is more to performance than just the network
latency between nodes. The utility of a long-lived data transfer is
determined by the throughput of the underlying TCP protocol, which
depends on the round-trip time as well as the loss rate experienced
on the corresponding path [Padhye]. Hence, these applications
benefit from a richer set of topology information that goes beyond
latency, including loss rate, capacity, and available bandwidth.
Some of the topology estimation techniques used by P2P applications
need time to converge to a result. For example, current BitTorrent
clients implement local, passive traffic measurements and a tit-for-
tat bandwidth reciprocity mechanism to optimize peer selection at a
local level. Peers eventually settle on a set of neighbors that
maximizes their download rate, but because peers cannot reason about
the value of neighbors without actively exchanging data with them,
and because the number of concurrent data transfers is limited
(typically to 5-7), convergence is delayed and easily can be
sub-optimal.
Skype's P2P Voice over IP (VoIP) application chooses a relay node in
cases where two peers are behind NATs and cannot connect directly.
Measurements taken by Ren et al. [Ren] showed that the relay
selection mechanism of Skype (1) is not able to discover the best
possible relay nodes in terms of minimum RTT, (2) requires a long
setup and stabilization time, which degrades the end user experience,
and (3) is creating a non-negligible amount of overhead traffic due
to probing a large number of nodes. They further showed that the
quality of the relay paths could be improved when the underlying
network Autonomous System (AS) topology is considered.
Some features of the network topology are hard to infer through
application-level techniques, and it may not be possible to infer
them at all, e.g., service-provider policies and preferences such as
the state and cost associated with interdomain peering and transit
links. Another example is the traffic engineering policy of a
service provider, which may counteract the routing objective of the
overlay network, leading to a poor overall performance [Seetharaman].
Finally, application-level techniques often require applications to
perform measurements on the topology. These measurements create
traffic overhead, in particular, if measurements are performed
individually by all applications interested in estimating topology.
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4. Open Issues
Beyond a significant amount of research work on the topic, we believe
that there are sizable open issues to address in an infrastructure-
based approach to traffic optimization. The following is not an
exhaustive list, but a representative sample of the pertinent issues.
4.1. Coordinate Estimation or Path Latencies?
Despite the many solutions that have been proposed for providing
applications with topology information in a fully distributed manner,
there is currently an ongoing debate in the research community
whether such solutions should focus on estimating nodes' coordinates
or path latencies. Such a debate has recently been fed by studies
showing that the triangle inequality on which coordinate systems are
based is often proved false in the Internet [Ledlie]. Proposed
systems following both approaches -- in particular, Vivaldi [Dabek]
and PIC [Costa] following the former, and Meridian [Wong] and iPlane
[Madhyastha] the latter -- have been simulated, implemented, and
studied in real-world trials, each one showing different points of
strength and weaknesses. Concentrated work will be needed to
determine which of the two solutions will be conducive to the ALTO
problem.
4.2. Malicious Nodes
Another open issue common in most distributed environments consisting
of a large number of peers is the resistance against malicious nodes.
Security mechanisms to identify misbehavior are based on triangle
inequality checks [Costa], which, however, tend to fail and thus
return false positives in the presence of measurement inaccuracies
induced, for example, by traffic fluctuations that occur quite often
in large networks [Ledlie]. Beyond the issue of using triangle
inequality checks, authoritatively authenticating the identity of an
oracle, and preventing an oracle from attacks are also important.
Existing techniques -- such as Public Key Infrastructure (PKI)
[RFC5280] or identity-based encryption [Boneh] for authenticating the
identity and the use of secure multi-party computation techniques to
prevent an oracle from collusion attacks -- need to be explored and
studied for judicious use in ALTO-type solutions.
4.3. Information Integrity
Similarly, even in controlled architectures deployed by network
operators where system elements may be authenticated [Xie],
[Aggarwal],[Saucez], it is still possible that the information
returned to applications is deliberately altered, for example,
assigning higher priority to financially inexpensive links instead of
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neutrally applying proximity criteria. What are the effects of such
deliberate alterations if multiple peers collude to determine a
different route to the target, one that is not provided by an oracle?
Similarly, what are the consequences if an oracle targets a
particular node in another AS by redirecting an inordinate number of
querying peers to it causing, essentially, a Distributed Denial-of-
Service (DDoS) [RFC4732] attack on the node? Furthermore, does an
oracle broadcast or multicast a response to a query? If so,
techniques to protect the confidentiality of the multicast stream
will need to be investigated to thwart "free riding" peers.
4.4. Richness of Topological Information
Many systems already use RTT to account for delay when establishing
connections with peers (e.g., Content-Addressable Network (CAN)
[Ratnasamy], Bamboo [Rhea]). An operator can provide not only the
delay metric but other metrics that the peer cannot figure out on its
own. These metrics may include the characteristics of the access
links to other peers, bandwidth available to peers (based on
operators' engineering of the network), network policies, preferences
such as state and cost associated with intradomain peering links, and
so on. Exactly what kinds of metrics an operator can provide to
stabilize the network throughput will also need to be investigated.
4.5. Hybrid Solutions
It is conceivable that P2P users may not be comfortable with operator
intervention to provide topology information. To eliminate this
intervention, alternative schemes to estimate topological distance
can be used. For instance, Ono uses client redirections generated by
Akamai CDN servers as an approximation for estimating distance to
peers; Vivaldi, GNP, and PIC use synthetic coordinate systems. A
neutral third party can make available a hybrid layer-cooperation
service -- without the active participation of the ISP -- that uses
alternative techniques discussed in Section 2.1 to create a
topological map. This map can be subsequently used by a subset of
users who may not trust the ISP.
4.6. Negative Impact of Over-Localization
The literature presented in Section 2 shows that a certain level of
locality-awareness in the peer selection process of P2P algorithms is
usually beneficial to application performance. However, an excessive
localization of the traffic might cause partitioning in the overlay
interconnecting these peers, which will negatively affect the
performance experienced by the peers themselves.
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Finding the right balance between localization and randomness in peer
selection is an open issue. At the time of writing, it seems that
different applications have different levels of tolerance and should
be addressed separately. Le Blond et al. [LeBlond] have studied the
specific case of BitTorrent, proposing a simple mechanism to prevent
partitioning in the overlay, yet reach a high level of cross-domain
traffic reduction without adversely impacting peers.
5. Security Considerations
This document is a survey of existing literature on topology
estimation. As such, it does not introduce any new security
considerations to be taken into account beyond what is already
discussed in each paper surveyed.
Insofar as topology estimation is used to provide a solution to the
ALTO problem, the issues in Sections 4.2 and 4.3 deserve special
attention. There are efforts underway in the IETF ALTO working group
to design a protocol that protects the privacy of the peer-to-peer
users as well as the service providers. [Chen] provides an overview
of ALTO security issues, Section 11 of [Alimi] is an exhaustive
overview of ALTO security, and Section 6 of RFC 5693 [RFC5693] also
lists the privacy and confidentiality aspects of an ALTO solution.
The following references provide a starting point for general peer-
to-peer security issues: [Wallach], [Sit], [Douceur], [Castro], and
[Friedman].
6. Acknowledgments
This document is a derivative work of a position paper submitted at
the IETF RAI area/MIT workshop held on May 28th, 2008 on the topic of
Peer-to-Peer Infrastructure (P2Pi) [RFC5594]. The article on a
similar topic, also written by the authors of this document and
published in IEEE Communications [Gurbani], was also partially
derived from the same position paper. The authors thank profusely
Arnaud Legout, Richard Yang, Richard Woundy, Stefano Previdi, and the
many people that have participated in discussions and provided
insightful feedback at any stage of this work.
7. Informative References
[Aggarwal] Aggarwal, V., Feldmann, A., and C. Scheideler, "Can
ISPs and P2P users cooperate for improved
performance?", in ACM SIGCOMM Computer Communications
Review, vol. 37, no. 3.
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RFC 6029 ALTO Survey October 2010
[Alimi] Alimi, R., Ed., Penno, R., Ed., and Y. Yang, Ed.,
"ALTO Protocol", Work in Progress, July 2010.
[Boneh] Boneh, D. and M. Franklin, "Identity-Based Encryption
from the Weil Pairing", in Proceedings of the 21st
Annual International Cryptology Conference on
Advances in Cryptology, August 2001.
[Castro] Castro, M., Druschelw, P., Ganesh, A., Rowstron, A.,
and D. Wallach, "Security for Structured Peer-to-peer
Overlay Networks", in Proceedings of Symposium on
Operating Systems Design and Implementation
(OSDI'02), December 2002.
[Chen] Chen, S., Gao, F., Beijing, X., and M. Xiong,
"Overview for ALTO Security Issues", Work
in Progress, February 2010.
[Coates] Coates, M., Hero, A., Nowak, R., and B. Yu, "Internet
Tomography", in IEEE Signal Processing Magazine,
vol. 19, no. 3.
[Costa] Costa, M., Castro, M., Rowstron, A., and P. Key,
"PIC: Practical Internet coordinates for distance
estimation", in Proceedings of International
Conference on Distributed Systems 2003.
[Dabek] Dabek, F., Cox, R., Kaashoek, F., and R. Morris,
"Vivaldi: A Decentralized Network Coordinate System",
in ACM SIGCOMM: Proceedings of the 2004 conference on
Applications, technologies, architectures, and
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no. 4.
[Douceur] Douceur, J., "The Sybil Attack", in Proceedings of
the First International Workshop on Peer-to-Peer
Systems, March 2002.
[Dovrolis] Dovrolis, C., Ramanathan, P., and D. Moore, "What do
packet dispersion techniques measure?",
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Shavitt, Y., and L. Zhang, "IDMaps: A global Internet
host distance estimation service", in Proceedings of
IEEE INFOCOM 2001.
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RFC 6029 ALTO Survey October 2010
[Friedman] Friedman, A. and A. Camp, "Peer-to-Peer Security",
in The Handbook of Information Security, J. Wiley &
Sons, 2005.
[Glasner] Glasner, J., "P2P fuels global bandwidth binge",
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Shenker, S., and I. Stoica, "The impact of DHT
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Venkataramani, "iPlane: an information plane for
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distance with coordinates-based approaches",
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[Ono] "Northwestern University Ono Project", <http://
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filesharing", available
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[RFC4732] Handley, M., Ed., Rescorla, E., Ed., and IAB,
"Internet Denial-of-Service Considerations",
RFC 4732, December 2006.
[RFC4949] Shirey, R., "Internet Security Glossary, Version 2",
FYI 36, RFC 4949, August 2007.
[RFC4981] Risson, J. and T. Moors, "Survey of Research towards
Robust Peer-to-Peer Networks: Search Methods",
RFC 4981, September 2007.
[RFC5280] Cooper, D., Santesson, S., Farrell, S., Boeyen, S.,
Housley, R., and W. Polk, "Internet X.509 Public Key
Infrastructure Certificate and Certificate Revocation
List (CRL) Profile", RFC 5280, May 2008.
[RFC5594] Peterson, J. and A. Cooper, "Report from the IETF
Workshop on Peer-to-Peer (P2P) Infrastructure, May
28, 2008", RFC 5594, July 2009.
[RFC5632] Griffiths, C., Livingood, J., Popkin, L., Woundy, R.,
and Y. Yang, "Comcast's ISP Experiences in a
Proactive Network Provider Participation for P2P
(P4P) Technical Trial", RFC 5632, September 2009.
[RFC5693] Seedorf, J. and E. Burger, "Application-Layer Traffic
Optimization (ALTO) Problem Statement", RFC 5693,
October 2009.
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Authors' Addresses
Ivica Rimac
Bell Labs, Alcatel-Lucent
EMail: rimac@bell-labs.com
Volker Hilt
Bell Labs, Alcatel-Lucent
EMail: volkerh@bell-labs.com
Marco Tomsu
Bell Labs, Alcatel-Lucent
EMail: marco.tomsu@alcatel-lucent.com
Vijay K. Gurbani
Bell Labs, Alcatel-Lucent
EMail: vkg@bell-labs.com
Enrico Marocco
Telecom Italia
EMail: enrico.marocco@telecomitalia.it
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