Network Working Group I. Rimac
Internet-Draft V. Hilt
Intended status: Informational M. Tomsu
Expires: June 24, 2010 V. Gurbani
Bell Labs, Alcatel-Lucent
E. Marocco
Telecom Italia
December 21, 2009
A Survey on Research on the Application-Layer Traffic Optimization
(ALTO) Problem
draft-irtf-p2prg-alto-survey-02
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Abstract
A significant part of the Internet traffic today is generated by
peer-to-peer (P2P) applications used traditionally 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.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
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
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 17
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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 realtime multimedia communications and live media
streaming. P2P applications are posing serious challenges to the
Internet infrastructure; by some estimates, P2P systems are so
popular that they make up anywhere between 40% to 85% of the entire
Internet traffic [Meeker], [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 structure that imposes
a specific ordering for P2P overlays -- use greedy forwarding
algorithms to reach their destination, making locally optimal
decisions that may not turn 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 Azureus [Azureus]. A slightly different
approach is to have the Internet service provider (ISP) take a pro-
active 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].
This document, initially intended as a complement to RFC 5693
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[RFC5693] and discussed during the creation of the IETF ALTO Working
Group, has been completed and refined in the IRTF P2P Research Group.
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 hypercubes, tree structures and
butterfly networks).
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 taxonomixed in two
categories (Figure 1): using application-level techniques to estimate
topology and through some kind of layer cooperation.
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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
Taxonomy of solutions for the application-layer traffic optimization
problem.
Figure 1
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.
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We note that the techniques presented in this section are only
representative of the sizable research in this area. Rather than
trying to enumerate an exhaustive list, we have chosen certain
techniques because they represent and 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 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 the 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 systems without any distinguished hosts. Whenever a node
A communicates with another node B, it measures the round trip time
(RTT) to that node and learns that node's current coordinates. 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 it's position
based on a simulation of interconnected mass springs. Vivaldi is now
being used in the popular P2P application Azureus and studies
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indicate that it scales well to very large networks [Ledlie].
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 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 network (CDN) like Akamai to
find nearby peers. Used as a plugin to the Azureus 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) Using 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
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different Internet topology and a varying number of landmarks and
dimensions to interpret the data set, it is impossible to 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 increasing complexity of a potential information
plane and introducing 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 a 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
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critical links, are interested in helping applications to optimize
the traffic they generate. The remainder of this section briefly
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] have been adopted by
the 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 accelerate content distribution and
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 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 experiments
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 application.
2.2.2. Oracle-based ISP-P2P Collaboration
In the general solution proposed by Aggarwal et al. [Aggarwal],
network providers host servers, called "oracles", that help P2P users
choose optimal neighbours.
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The mechanism is fairly simple: a P2P user sends the list of
potential peers to the oracle hosted by its ISP, which ranks such a
list based on its local policies. For instance, the ISP can prefer
peers within its network, to prevent traffic from leaving its
network; further, it can pick higher bandwidth links, or peers that
are geographically closer. Once the application has obtained an
ordered list, it is up to it to establish connections with a number
of peers it can individually choose, but it has enough information to
perform an optimal choice.
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 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 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, 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
the number of concurrent data transfers is limited (typically to
5-7), convergence is delayed and easily can be sub-optimal.
Skype's P2P VoIP application chooses a relay node in cases where two
peers are behind NATs and cannot connect directly. Ren et al. [Ren]
measured that the relay selection mechanism of Skype is (1) 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 (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 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. An example for such a features are 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, 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 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. Exploration of
existing techniques -- such as public key infrastructure or identity-
based encryption for authenticating the identity and the use of
secure multi-party computation techniques to prevent an oracle from
collusion attacks -- need to be studied for judicious use in {ALTO}-
type of 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 cheap (monetary-wise) 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 DDoS 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
multi-cast 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., CAN, Bamboo). 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 operator's engineering of its network), network policies,
and preferences such as state and cost associated with intradomain
peering links, and so on. Exactly what kinds of metrics can an
operator 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
toplogical 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 the application performance. However, an
excessive localization of the traffic might cause partitioning in the
overlay interconnecting peers, which will negatively affect the
performance experienced by the peers themselves.
Finding the right balance between localization and randomness in peer
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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 reaching a high level of cross-
domain traffic reduction without adversely impacting peers.
5. Security Considerations
This draft is a survey of existing literature on topology estimation.
As such, it does not introduce any new security considerations to be
taken in account beyond what is already discussed in each paper
surveyed.
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). The article "A Survey of
Research on the Application-Layer Traffic Optimization Problem and
the Need for Layer Cooperation" appeared on IEEE Communications
Magazine, Vol. 47, No. 8 was also partially derived from the same
paper. The authors thank profusely Arnaud Legout 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. Scheidler, "Can ISPs
and P2P systems co-operate for improved performance?".
[Azureus] "Azureus BitTorrent Client", .
[Coates] Coates, M., Hero, A., Nowak, R., and B. Yu, "Internet
Tomography".
[Costa] Costa, M., Castro, M., Rowstron, A., and P. Key, "PIC:
Practical Internet coordinates for distance estimation".
[Dabek] Dabek, F., Cox, R., Kaashoek, F., and R. Morris, "Vivaldi:
A Decentralized Network Coordinate System".
[Dovrolis]
Dovrolis, C., Ramanathan, P., and D. Moore, "What do
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packet dispersion techniques measure?".
[Francis] Francis, P., Jamin, S., Jin, C., Jin, Y., Raz, D.,
Shavitt, Y., and L. Zhang, "IDMaps: A global Internet host
distance estimation service".
[Glasner] Glasner, J., "P2P fuels global bandwidth binge",
.
[Gummadi] Gummadi, K., Gummadi, R., Gribble, S., Ratnasamy, S.,
Shenker, S., and I. Stoica, "The impact of DHT routing
geometry on resilience and proximity".
[Karagiannis]
Karagiannis, T., Broido, A., Brownlee, N., Claffy, K., and
M. Faloutsos, "Is P2P dying or just hiding?".
[LeBlond] Le Blond, S., Legout, A., and W. Dabbous, "Pushing
BitTorrent Locality to the Limit".
[Ledlie] Ledlie, J., Gardner, P., and M. Seltzer, "Network
Coordinates in the Wild".
[LightReading]
LightReading, "Controlling P2P traffic", .
[LinuxReviews]
linuxReviews.org, "Peer to peer network traffic may
account for up to 85% of Interneta??s bandwidth usage",
.
[Madhyastha]
Madhyastha, H., Isdal, T., Piatek, M., Dixon, C.,
Anderson, T., Krishnamurthy, A., and A. Venkataramani.,
"iPlane: an information plane for distributed services".
[Meeker] Meeker, M. and D. Joseph, "The State of the Internet, Part
3", .
[Ng] Ng, T. and H. Zhang, "Predicting internet network distance
with coordinates-based approaches".
[Ono] "Northwestern University Ono Project",
.
[P4P] "DCIA P4P Working group",
.
[Padhye] Padhye, J., Firoiu, V., Towsley, D., and J. Kurose,
"Modeling TCP throughput: A simple model and its empirical
validation".
[Parker] Parker, A., "The true picture of peer-to-peer
filesharing", .
[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.
[Ren] Ren, S., Guo, L., and X. Zhang, "ASAP: An AS-aware peer-
relay protocol for high quality VoIP".
[Saucez] Saucez, D., Donnet, B., and O. Bonaventure,
"Implementation and Preliminary Evaluation of an ISP-
Driven Informed Path Selection".
[Seetharaman]
Seetharaman, S., Hilt, V., Hofmann, M., and M. Ammar,
"Preemptive Strategies to Improve Routing Performance of
Native and Overlay Layers".
[Su] Su, A., Choffnes, D., Kuzmanovic, A., and F. Bustamante,
"Drafting behind Akamai (travelocity-based detouring)".
[Wang] Wang, G., Zhang, B., and T. Ng, "Towards Network Triangle
Inequality Violation Aware Distributed Systems".
[Wong] Wong, B., Slivkins, A., and E. Sirer, "Meridian: A
lightweight network location service without virtual
coordinates".
[Xie] Xie, H., Krishnamurthy, A., Silberschatz, A., and Y. Yang,
"P4P: Explicit Communications for Cooperative Control
Between P2P and Network Providers",
.
Rimac, et al. Expires June 24, 2010 [Page 16]
Internet-Draft ALTO Survey December 2009
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
Rimac, et al. Expires June 24, 2010 [Page 17]