Internet DRAFT - draft-ietf-decade-integration-example
draft-ietf-decade-integration-example
DECADE N. Zong, Ed.
Internet-Draft X. Chen
Intended status: Informational Z. Huang
Expires: January 10, 2013 Huawei Technologies
L. Chen
HP Labs
H. Liu
Yale University
July 9, 2012
Integration Examples of DECADE System
draft-ietf-decade-integration-example-06
Abstract
Decoupled Application Data Enroute (DECADE) system is an in-network
storage infrastructure which is still under discussion in IETF. This
document presents two detailed examples of how to integrate such in-
network storage infrastructure into peer-to-peer (P2P) applications
to achieve more efficient content distribution, and Application Layer
Traffic Optimization (ALTO) system to build a content distribution
platform for Content Providers (CPs).
Status of this Memo
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provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on January 10, 2013.
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Copyright (c) 2012 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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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 5
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.1. Native Application Client . . . . . . . . . . . . . . . . 6
2.2. INS Server . . . . . . . . . . . . . . . . . . . . . . . . 6
2.3. INS Client . . . . . . . . . . . . . . . . . . . . . . . . 6
2.4. INS Operations . . . . . . . . . . . . . . . . . . . . . . 6
2.5. INS System . . . . . . . . . . . . . . . . . . . . . . . . 6
2.6. INS Client API . . . . . . . . . . . . . . . . . . . . . . 6
2.7. INS-enabled Application Client . . . . . . . . . . . . . . 6
2.8. INS Service Provider . . . . . . . . . . . . . . . . . . . 6
2.9. INS Portal . . . . . . . . . . . . . . . . . . . . . . . . 6
3. INS Client API . . . . . . . . . . . . . . . . . . . . . . . . 7
4. Integration of P2P File Sharing and INS System . . . . . . . . 7
4.1. Integration Architecture . . . . . . . . . . . . . . . . . 7
4.1.1. Message Flow . . . . . . . . . . . . . . . . . . . . . 8
4.2. Concluding Remarks . . . . . . . . . . . . . . . . . . . . 10
5. Integration of P2P Live Streaming and INS System . . . . . . . 10
5.1. Integration Architecture . . . . . . . . . . . . . . . . . 10
5.1.1. Data Access Messages . . . . . . . . . . . . . . . . . 10
5.1.2. Control Messages . . . . . . . . . . . . . . . . . . . 10
5.2. Design Considerations . . . . . . . . . . . . . . . . . . 11
5.2.1. Improve Efficiency for Each Connection . . . . . . . . 11
5.2.2. Reduce Control Latency . . . . . . . . . . . . . . . . 11
6. Integration of ALTO and INS System for File Distribution . . . 12
6.1. Architecture . . . . . . . . . . . . . . . . . . . . . . . 12
6.1.1. CP Uploading Procedure . . . . . . . . . . . . . . . . 13
6.1.2. End User Downloading Procedure . . . . . . . . . . . . 14
7. Test Environment and Settings . . . . . . . . . . . . . . . . 15
7.1. Test Settings . . . . . . . . . . . . . . . . . . . . . . 15
7.2. Test Environment for P2P Live Streaming Example . . . . . 15
7.2.1. INS Server . . . . . . . . . . . . . . . . . . . . . . 16
7.2.2. P2P Live Streaming Client . . . . . . . . . . . . . . 16
7.2.3. Tracker . . . . . . . . . . . . . . . . . . . . . . . 16
7.2.4. Streaming Source Server . . . . . . . . . . . . . . . 16
7.2.5. Test Controller . . . . . . . . . . . . . . . . . . . 16
7.3. Test Environment for P2P File Sharing Example . . . . . . 17
7.3.1. INS Server . . . . . . . . . . . . . . . . . . . . . . 17
7.3.2. Vuze Client . . . . . . . . . . . . . . . . . . . . . 17
7.3.3. Tracker . . . . . . . . . . . . . . . . . . . . . . . 17
7.3.4. Test Controller . . . . . . . . . . . . . . . . . . . 17
7.3.5. HTTP Server . . . . . . . . . . . . . . . . . . . . . 18
7.3.6. PlanetLab Manager . . . . . . . . . . . . . . . . . . 18
7.4. Test Environment for Combined ALTO and INS File
Distribution System . . . . . . . . . . . . . . . . . . . 18
8. Performance Analysis . . . . . . . . . . . . . . . . . . . . . 18
8.1. Performance Metrics . . . . . . . . . . . . . . . . . . . 18
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8.1.1. P2P Live Streaming . . . . . . . . . . . . . . . . . . 18
8.1.2. P2P File Sharing . . . . . . . . . . . . . . . . . . . 19
8.1.3. Integration of ALTO and INS System for File
Distribution . . . . . . . . . . . . . . . . . . . . . 19
8.2. Results and Analysis . . . . . . . . . . . . . . . . . . . 19
8.2.1. P2P Live Streaming . . . . . . . . . . . . . . . . . . 19
8.2.2. P2P File Sharing . . . . . . . . . . . . . . . . . . . 20
8.2.3. Integrated ALTO and INS System for File
Distribution . . . . . . . . . . . . . . . . . . . . . 21
9. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 21
10. Security Considerations . . . . . . . . . . . . . . . . . . . 21
11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 21
12. References . . . . . . . . . . . . . . . . . . . . . . . . . . 21
12.1. Normative References . . . . . . . . . . . . . . . . . . . 22
12.2. Informative References . . . . . . . . . . . . . . . . . . 22
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 22
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1. Introduction
Decoupled Application Data Enroute (DECADE) system is an in-network
storage infrastructure which is still under discussion in IETF. We
implemented such in-network storage infrastructure to simulate DECADE
system including DECADE servers, DECADE clients and DECADE protocols
[I-D.ietf-decade-arch]. Therefore, in the whole draft, we use the
terms of in-network storage (INS) system, INS server, INS client, INS
operations, etc.
This draft introduces some examples of integrating INS system with
existing applications. In our example systems, the core components
include INS server and INS-enabled application client. An INS server
stores data inside the network, and thereafter manages both the
stored data and access to that data. An INS-enabled application
client including INS client and native application client uses a set
of Application Programming Interfaces (APIs) to enable native
application client to utilize INS operations such as data get, data
put, storage status query, etc.
This draft presents two detailed examples of how to integrate INS
system into peer-to-peer (P2P) applications, i.e. live streaming and
file sharing, as well as an example integration of Application Layer
Traffic Optimization (ALTO) [I-D.ietf-alto-protocol] and INS system
to support file distribution. We show how to extend native P2P
applications by designing the INS-enabled P2P clients and describing
the corresponding flows of INS-enabled data transmission. Then we
introduce the functional architecture and working flows of integrated
ALTO and INS system for file distribution of Content Providers (CPs).
Finally we illustrate the performance gain to P2P applications and
more efficient content distribution by effectively leveraging the INS
system.
Please note that the P2P applications mentioned in this draft only
represent some cases out of a large number of P2P applications, while
the INS system itself can support a variety of other applications.
Moreover, the set of APIs used in our integration examples is an
experimental implementation, which is not standard and still under
development. The INS system described in this draft is only a
preliminary functional set of in-network storage infrastructure for
applications. It is designed to test the pros and cons of INS system
utilized by P2P applications and verify the feasibility of utilizing
INS system to support content distribution. We hope our examples
would be useful for further standard protocol design, rather than to
present a solution for standardization purpose.
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2. Terminology
The following terms will be used in this document.
2.1. Native Application Client
A client running original application operations including control
and data messages defined by applications.
2.2. INS Server
A server to simulate DECADE server defined in [I-D.ietf-decade-arch].
2.3. INS Client
A client to simulate DECADE client defined in [I-D.ietf-decade-arch].
2.4. INS Operations
A set of communications between INS server and INS client to simulate
DECADE protocols defined in [I-D.ietf-decade-arch].
2.5. INS System
A system including INS servers, INS clients, and INS operations.
2.6. INS Client API
A set of APIs to enable native application client to utilize INS
operations.
2.7. INS-enabled Application Client
An INS-enabled application client includes INS client and native
application client communicating through INS client API.
2.8. INS Service Provider
An INS service provider deploys INS system and provides INS service
to applications/end users. It can be Internet Service Provider (ISP)
or other parties.
2.9. INS Portal
A functional entity operated by INS service provider to offer
applications/end users a point to access (e.g. upload, download)
files stored in INS servers.
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3. INS Client API
In order to simplify the integration of INS system with P2P
applications, we provide INS client API to native P2P clients for
accomplishing INS operations such as data get, data put, etc. On top
of the INS client API, a native P2P client can develop its own
application specific control and data distribution flows.
We currently developed the following five basic interfaces.
o Generate_Token: Generate an authorization token. An authorization
token is usually generated by an entity that is trusted by an INS
client which is sharing its data and passed to the other INS clients
for data access control. Please see [I-D.ietf-decade-arch] for more
details.
o Get_Object: Get a data object from an INS server with an
authorization token.
o Put_Object: Store a data object into an INS server with an
authorization token.
o Delete_Object: Delete a data object in an INS server explicitly
with an authorization token. Note that a data object can also be
deleted implicitly by setting a Time-To-Live (TTL) value.
o Status_Query: Query current status of an application itself,
including listing stored data objects, resource (e.g. storage space)
usage, etc.
4. Integration of P2P File Sharing and INS System
We integrate an INS client into Vuze - a BitTorrent based file
sharing application [VzApp].
4.1. Integration Architecture
The architecture of the integration of Vuze and INS system is shown
in Figure 1. An INS-enabled Vuze client uses INS client to
communicate with INS server and transmit data between itself and INS
server. It is also compatible with original Vuze signaling messages
such as peer discovery, data availability announcement, etc. Note
that the same architecture applies to the other example of
integration of P2P live streaming and INS system.
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+------------------+ +------------------+
| INS-enabled | | INS-enabled |
| Client | | Client |
|+----------------+| +---------------+ |+----------------+|
|| INS |+---| INS Server |---+| INS ||
|| Client || +---------------+ || Client ||
|| |+-----------------------+| ||
|+------+---------+| |+------+---------+|
| API | | | API | |
|+------+---------+| |+------+---------+|
|| Native Client |+-----------------------+| Native Client ||
|+----------------+| |+----------------+|
+------------------+ +------------------+
Figure 1
4.1.1. Message Flow
In order for a better comparison, we briefly show the below diagram
of the native Vuze message exchange, and then show the corresponding
diagram including the INS system.
+--------+ +--------+
| Vuze | | Vuze |
| Client1| | Client2|
+--------+ +--------+
| |
| HandShake |
|<----------------------------------->|
| BT_BitField |
|<----------------------------------->|
| BT_Request |
|------------------------------------>|
| BT_Piece |
|<------------------------------------|
| |
Figure 2
In the above diagram, one can see that the key messages for data
sharing in native Vuze are "BT_BitField", "BT_Request" and
"BT_Piece". Vuze client1 and client2 exchange "BT_BitField" messages
to announce the available data objects to each other. If Vuze
client1 wants to get certain data object from client2, it sends a
"BT_Request" message to client2. Vuze client2 then return the
requested data object to client1 by a "BT_Piece" message. Please
refer to [VzMsg] for the detailed description of Vuze messages.
As shown in the below diagram, in the integration of Vuze and INS
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system, INS client inserts itself into the Vuze client by
intercepting certain Vuze messages, and adjusting their handling to
send/receive data using the INS operations instead.
________ __________ __________ ________ _________
| Vuze | | INS | | INS | | Vuze | | INS |
|Client1| | Client1 | | Client2 | |Client2| | Server |
|_______| |_________| |_________| |_______| |_________|
| | | | |
| | HandShake | | |
|<----------|------------|---------->| |
| | BT_BitField| | |
|<----------|------------|---------->| |
| | BT_Request | | |
|-----------|----------->| | |
| | | | |
| | Redirect | | |
| |<-----------| | |
| | | Get Data | |
| |----------------------------------->|
| | |Data Object| |
| |<-----------------------------------|
| | | | |
| BT_Piece | | | |
|<----------| | | |
| | | | |
Figure 3
o Vuze client1 sends a "BT_Request" message to Vuze client2 to
request a data object as usual.
o INS client2 embedded in Vuze client2 intercepts the incoming
"BT_Request" message and then replies with a "Redirect" message which
includes INS server's address and authorization token.
o INS client1 receives the "Redirect" message and then sends an INS
message "Get Data" to the INS server to request the data object.
o INS server receives the "Get Data" message and sends the requested
data object back to INS client1 after the token check.
o INS client1 encapsulates the received data object into a "BT_Piece"
message and sends to Vuze client1.
In this example, the file to be shared is divided into many objects,
with each object being named as "filename_author_partn" where author
is the original author of the file or the user who uploads the file,
n is the sequence number of the object.
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4.2. Concluding Remarks
In this example, we feel that the INS system can effectively improve
the file sharing efficiency due to following reasons: 1) utilizing
in-network storage as the data location of the peer will achieve
statistical multiplexing gain of the data sharing; 2) shorter data
delivery path based on in-network storage could not only improve the
application performance, but avoid the potential bottleneck in the
ISP network.
5. Integration of P2P Live Streaming and INS System
We integrate an INS client into a P2P live streaming application.
5.1. Integration Architecture
The architecture of the integration of P2P live streaming application
and INS system is shown in Figure 1. An INS-enabled P2P live
streaming client uses INS client to communicate with INS server and
transmit data between itself and INS server.
5.1.1. Data Access Messages
INS client API is called whenever an INS-enabled P2P live streaming
client wants to get data objects from (or put data objects into) the
INS server. Each data object transferred between the application
client and the INS server should go through the INS client. Each
data object can be a variable-sized block to cater to different
application requirements (e.g. latency and throughput).
We use the hash of a data object's content for the name of the data
object. The name of a data object is generated and distributed by
the source streaming server in this example.
5.1.2. Control Messages
We used a lab-based P2P live streaming system for research purpose
only. The basic control messages between the native P2P live
streaming clients are similar to Vuze control protocols in the sense
that the data piece information is exchanged between the peers. The
INS-enabled P2P live streaming client adds an additional control
message for authorization token distribution, as shown as the line
between the INS clients in Figure 1. In this example, the
authorization token is generated by the INS client that is sharing
its data. By exchanging the authorization tokens, the application
clients can retrieve the data objects from the INS servers.
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5.2. Design Considerations
One essential objective of the integration is to improve the
performance of P2P live streaming application. In order to achieve
such goal, we have some important design considerations that would be
helpful to the future work of protocol development.
5.2.1. Improve Efficiency for Each Connection
In a native P2P system, a peer can establish tens or hundreds of
concurrent connections with other peers. On the other hand, it may
be expensive for an INS server to maintain many connections for a
large number of INS clients. Typically, each INS server may only
allocate and maintain M connections (in our examples, M=1) with each
INS client at a time. Therefore, we have the following design
considerations to improve the efficiency for each connection between
INS server and INS client to achieve satisfying data downloading
performance.
o Batch Request: In order to fully utilize the connection bandwidth
of INS server and reduce the overhead, an application client may
request a batch of data objects in a single request.
o Larger Data Object: Data object size in existing P2P live streaming
application may be small and thus incur large control overhead and
low transport utilization. A larger data object may be needed to
more efficiently utilize the data connection between INS server and
INS client.
5.2.2. Reduce Control Latency
In a native P2P system, a serving peer sends data objects to the
requesting peer directly. Nevertheless, in an INS system, the
serving client typically only replies with an authorization token to
the requesting client, and then the requesting client uses this token
to fetch the data objects from the INS server. This process
introduces an additional control latency compared with the native P2P
system. It is even more serious in latency sensitive applications
such as P2P live streaming. Therefore, we need to consider how to
reduce such control latency.
o Range Token: One way to reduce control latency is to use range
token. An INS-enabled P2P live streaming client may piggyback a
range token when announcing data availability to other peers,
indicating that all available data objects are accessible by this
range token. Then instead of requesting some specific data object
and waiting for the response, a peer can use this range token to
access all available data objects that it was permitted to access in
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the INS server.
6. Integration of ALTO and INS System for File Distribution
The objective of ALTO service is to give guidance to applications
about which content servers to select to improve content distribution
performance in an ISP-friendly way (e.g. reducing network usage
within the ISP). The core component of ALTO service is called ALTO
server which generates the guidance based on the ISP network
information. The ALTO protocol conveys such guidance from the ALTO
server to the applications. The detailed description of ALTO
protocol can be found in [I-D.ietf-alto-protocol].
In this example, we integrate ALTO and INS system to build a content
distribution platform for CPs.
6.1. Architecture
The integrated system allows CPs to upload files to INS servers, and
guides end users to download files from the INS servers suggested by
ALTO service. The architecture diagram is shown as below. Note that
this diagram just shows a basic set of connections between the
components. Some redirection including that the INS portal redirects
end users to the INS servers can also happen between the components.
_____________________________________________
| ________ ________ ________ ________ |
|| INS | | INS | | INS | | INS | |
||Server1 | |Server2 | |Server3 | |Servern | |
||________| |________| |________| |________| |
| \ | | / |
| \ _|______|_ / | +--------+
| INS \ | INS | / | | ALTO |
| Service | Portal |-----------------+---| Server |
| Provider |__________| | +--------+
|_____________________|______________________|
|
______|______
| CP Portal |
|_____________|
/ \
__________ / \ __________
| End User | | End User |
|__________| |__________|
Figure 4
Four key components are defined as follow.
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o INS Servers: operated by an INS service provider to store files
from CPs.
o INS Portal: operated by an INS service provider to 1) upload files
from CPs to the dedicated INS servers; 2) direct end users to the INS
servers suggested by ALTO service to download files.
o CP Portal: operated by a CP to publish the URLs of the uploaded
files for end user downloading.
o End User: End users use standard web browser with INS extensions
such that INS client APIs can be called for fetching the data from
INS servers.
6.1.1. CP Uploading Procedure
CP uploads the files into INS servers first, then gets the URLs of
the uploaded files and publishes the URLs on the CP portal for end
user downloading. The flow is shown below.
_________ _________ _________
| | | INS | | INS |
| CP | | Portal | | Server |
|_________| |_________| |_________|
| | |
| HTTP POST | |
|------------------>| |
| | Put Data |
| |----------------->|
| | Response |
| |<-----------------|
| URLs | |
|<------------------| |
| | |
Figure 5
o CP uploads the file to the INS portal site via HTTP POST message.
o INS portal distributes the file to the dedicated INS severs using
INS message "Put Data". Note that the data distribution policies
(e.g. how many copies of the data to which INS servers) can be
specified by CP. The dedicated INS servers can be also decided by
the INS service provider based on policies or system status (e.g.
INS server load). These issues are out of the scope of this draft.
In this example, the data stored in INS server is divided into many
objects, with each object being named as "filename_CPname_partn"
where CPname is the name of the CP who uploads the file, n is the
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sequence number of the object.
o When the file is uploaded successfully, CP portal will list the
URLs of the file for end use downloading.
6.1.2. End User Downloading Procedure
End users can visit the CP portal web pages and click the URLs for
downloading the desired files. The flow is shown below.
_________ ____________ _________ _________ _________
| | | | | INS | | ALTO | | INS |
| End User| | CP Portal | | Portal | | Server | | Server |
|_________| |____________| |_________| |_________| |_________|
| | | | |
| HTTP Get | | | |
|------------->| | | |
| Token | | | |
|<-------------| | | |
| | | | |
| HTTP Get | | |
|------------------------------>| | |
| | | ALTO Req | |
| | |------------>| |
| | | ALTO Resp | |
| | |<------------| |
| Optimal INS Server address | | |
|<------------------------------| | |
| | | | |
| | Get Data | |
|---------------------------------------------------------->|
| | | | |
| | Data Object | |
|<----------------------------------------------------------|
| | | | |
Figure 6
o End user visits CP portal web page, and finds the URLs for the
desired file.
o End user clicks the hyper link, CP portal returns authorization
token to the end user and redirects the end user to INS portal via
HTTP Get message.
o INS portal communicates with ALTO server to get the suggested INS
server storing the requested file. In this example, ALTO server just
selects the INS server within the same IP subset of the end user.
Please see [I-D.ietf-alto-protocol] for more details on how ALTO
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select content server.
o INS portal returns the INS server address suggested by ALTO service
to the end user.
o End user connects to the suggested INS server to get data via INS
message "Get Data" after the token check.
7. Test Environment and Settings
We conduct some tests to show the results of our integration
examples. For a better performance comparison, we ran experiments
(i.e. INS integrated P2P application v.s. native P2P application) in
the same environment using the same settings.
7.1. Test Settings
Our tests ran on a wide-spread area and diverse platforms, including
a famous commercial platform - Amazon EC2 [EC2] and a well known
test-bed - PlanetLab [PL]. The experimental settings are as follows.
o Amazon EC2: We setup INS servers in Amazon EC2 platform, including
four regions around the world - US east, US west, Europe and Asia.
o PlanetLab: We ran our P2P live streaming clients and P2P file
sharing clients (both INS-enabled and native clients) on PlanetLab on
a wild-spread area.
o Flash-crowd: Flash-crowd is an important scenario in P2P live
streaming system due to the live nature, i.e. a large number of users
join the live channel during the startup period of the event.
Therefore, we conduct experiments to test the system performance for
flash-crowd in our P2P live streaming example.
o Total supply bandwidth: Total supply bandwidth is the sum of the
capacity of bandwidth used to serve the streaming/file content, from
both servers (including source servers and INS servers) and the P2P
clients. For a fair comparison, we set the total supply bandwidth to
be the same in both tests of native and INS-enabled P2P applications.
7.2. Test Environment for P2P Live Streaming Example
In the tests, we have some functional components running in different
platforms, including INS servers, P2P live streaming clients (INS-
enabled or native), native P2P live streaming tracker, streaming
source server and test controller, as shown in below figure.
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+------------+ +------------+
| INS |----| INS |
| Server | | Server |
+-----+------+ +------+-----+ Amazon EC2
______________________|__________________|_________________
| |
+-----+------+ +------+-----+
| Streaming |----| Streaming |
| Client |\ /| Client |
+------+-----+ \/ +------+-----+ PlanetLab
_______________________|_______/\________|_________________
| / \ | Yale Lab
+--------------+ +------+-----+ +------+-----+
| Streaming | | Tracker | | Test |
| Source Server| | | | Controller |
+--------------+ +------------+ +------------+
Figure 7
7.2.1. INS Server
INS servers ran on Amazon EC2.
7.2.2. P2P Live Streaming Client
Both INS-enabled and native P2P live streaming clients ran on
PlanetLab. Each INS-enabled P2P live streaming client connects to
the dedicated INS server. In this example, we decide which client
connects to which server based on the IP address. So, it is roughly
region-based and still coarse. Each INS-enabled P2P live streaming
client uses its INS server to share streaming content to other peers.
7.2.3. Tracker
A native P2P live streaming tracker ran at Yale's laboratory and
served both INS-enabled and native P2P live streaming clients during
the test.
7.2.4. Streaming Source Server
A streaming source server ran at Yale's laboratory and served both
INS-enabled and native P2P live streaming clients during the test.
7.2.5. Test Controller
Test controller is a manager running at Yale's laboratory to control
all machines' behaviors in both Amazon EC2 and PlanetLab during the
test.
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7.3. Test Environment for P2P File Sharing Example
Functional components include Vuze client (with and without INS
client), INS servers, native Vuze tracker, HTTP server, PlanetLab
manager and test controller, as shown in below figure.
+-----------+ +-----------+
| INS |----| INS |
| Server | | Server |
+-----+-----+ +-----+-----+ Amazon EC2
______________________|________________|_________________
| |
+-----+-----+ +-----+-----+
| Vuze |----| Vuze |
| Client |\ /| Client |
+-----+-----+ \/ +-----+-----+ PlanetLab
______________________|_______/\_______|_________________
| / \ | Yale Lab
+-------------+ +------+-----+ +-----+------+ +-----------+
| HTTP Server | | Tracker | | Test | | PlanetLab |
| | | | | Controller | | Manager |
+-------------+ +------------+ +------------+ +-----------+
Figure 8
7.3.1. INS Server
INS servers ran on Amazon EC2.
7.3.2. Vuze Client
Vuze clients were divided into one seeding client and multiple
leechers. The seeding client ran at a Window 2003 server at Yale's
laboratory. Both INS-enabled and native Vuze clients (leechers) ran
on PlanetLab. INS client embedded in Vuze client was automatically
loaded and ran after Vuze client start up.
7.3.3. Tracker
Vuze software includes tracker implementation, so we didn't deploy
our own tracker. Tracker ran at Yale's laboratory and was enabled
when making a BitTorrent file. Tracker ran at the same Window 2003
server with the seeding client.
7.3.4. Test Controller
Similar to the test controller in P2P live streaming case, the test
controller in Vuze example can also control all machines' behaviors
in Amazon EC2 and PlanetLab. For example, it lists all the Vuze
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clients via GUI and controls them to download a specific BitTorrent
file. Test controller ran at the same Window 2003 server with the
seeding client.
7.3.5. HTTP Server
BitTorrent file was put in the HTTP server and the leechers retrieved
the BitTorrent file from the HTTP server after receiving the
downloading command from the test controller. We used Apache Tomcat
for HTTP server.
7.3.6. PlanetLab Manager
PlanetLab manager is a tool developed by University of Washington.
It presents a simple GUI to control PlanetLab nodes and perform
common tasks such as: 1) selecting nodes for your slice; 2) choosing
nodes for your experiment based on the information about the nodes;
3) reliably deploying you experiment files; 4) executing commands on
every node in parallel; 5) monitoring the progress of the experiment
as a whole, as well as viewing console output from the nodes.
7.4. Test Environment for Combined ALTO and INS File Distribution
System
For the integration of ALTO and INS systems for supporting file
distribution of CPs, we built 6 Linux virtual machines (VMs) with
Fedora13 operating system. ALTO server, INS portal, CP portal and
two INS servers ran on these VMs. Each VM is allocated with 4 cores
from a 16-core 1Ghz CPU, and has 2GB memory space and 10GB disk
space. CP uploaded files to the INS server via INS portal. End user
can choose desired file through the CP portal, and download it from
the optimal INS server chosen by the INS portal using ALTO service.
8. Performance Analysis
We illustrate the performance gain to P2P applications and more
efficient content distribution by effectively leveraging the INS
system. For the example of integrating ALTO and INS systems to
support file distribution of CPs, we show the feasibility of such
integration.
8.1. Performance Metrics
8.1.1. P2P Live Streaming
To measure the performance of a P2P live streaming application, we
mainly employed the following four metrics.
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o Startup delay: The duration from a peer joins the streaming channel
to the moment it starts to play.
o Piece missed rate: The number of pieces a peer loses when playing
over the total number of pieces.
o Freeze times: The number of times a peer re-buffers during playing.
o Average peer uploading rate: Average uploading bandwidth of a peer.
8.1.2. P2P File Sharing
To measure the performance of a P2P file sharing application, we
mainly employed the following three metrics.
o Download traffic: The total amount of traffic representing the
network downlink resource usage.
o Upload traffic: The total amount of traffic representing the
network uplink resource usage.
o Network resource efficiency: The ratio of P2P system download rate
to the total network (downlink) bandwidth.
8.1.3. Integration of ALTO and INS System for File Distribution
We consider some common capacity metrics for content distribution
system, i.e. the bandwidth usage of each INS server, and the total
online users supported by each INS server.
8.2. Results and Analysis
8.2.1. P2P Live Streaming
o Startup delay: In the test, INS-enabled P2P live streaming clients
startup around 35~40 seconds and some of them startup around 10
seconds. Native P2P live streaming clients startup around 110~120
seconds and less than 20% of them startup within 100 seconds.
o Piece missed rate: In the test, both INS-enabled P2P live streaming
clients and native P2P live streaming clients achieved a good
performance in piece missed rate. Only about 0.02% of total pieces
missed in both cases.
o Freeze times: In the test, native P2P live streaming clients
suffered from more freezing times than INS-enabled P2P live streaming
clients by 40%.
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o Average peer uploading rate: In the test, according to our
settings, INS-enabled P2P live streaming clients had no data upload
in their "last mile" access network, while in the native P2P live
streaming system, most peers uploaded streaming data for serving
other peers. In another word, INS system can shift uploading traffic
from clients' "last mile" to in-network devices, which saves a lot of
expensive bandwidth on access links.
8.2.2. P2P File Sharing
The test result is illustrated in below figure. We can see that
there is very few upload traffic from the INS-enabled Vuze clients,
while in the native Vuze case, the upload traffic from Vuze clients
is the same as the download traffic. Network resource usage is thus
reduced in the "last mile" in the INS-enabled Vuze case. This result
also verifies that the INS system can shift uploading traffic from
clients' "last mile" to in-network devices. Note that because not
all clients finish downloading process, there are different total
download traffic for the independent tests, as shown in below figure.
+--------------------+--------------------+--------------------+
| | | |
| | Download Traffic | Upload Traffic |
| | | |
+--------------------+--------------------+--------------------+
| | | |
| INS-Enabled Vuze | 480MB | 12MB |
| | | |
+--------------------+--------------------+--------------------+
| | | |
| Native Vuze | 430MB | 430MB |
| | | |
+--------------------+--------------------+--------------------+
Figure 9
We also found higher network resource efficiency in the INS-enabled
Vuze case where the network resource efficiency is defined as the
ratio of P2P system download rate to the total network (downlink)
bandwidth. The test result is that the network resource efficiency
of native Vuze is 65% while that of INS-enabled Vuze is 88%. A
possible reason behind the higher network resource efficiency is that
the INS server can always serve content to the peers, while in
traditional P2P applications, peer has to finish downloading content
before sharing with other peers.
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8.2.3. Integrated ALTO and INS System for File Distribution
Each INS server can supply the bandwidth usage of at most 94% of
network interface card (NIC) - e.g. 1Gbps NIC server can supply
bandwidth of 940Mbps at most. We did tests on 100Mbps and 1Gbps NIC,
and got same result of 94% bandwidth usage.
Each INS server can support about 400 online users for file
downloading simultaneously. When we tried 450 concurrent online
users, 50 users didn't start downloading on time, but wait for the
other 400 users to finish downloading.
9. Conclusion
This document presents two examples of integrating INS system into
P2P applications (i.e. P2P live streaming and Vuze) by developing
INS client API for native P2P clients. To better adopt INS system,
we found some important design considerations including efficiency
for INS connection, control latency caused by INS operations, and
developed some mechanisms to address them. We ran some tests to show
the results of our integration examples on Amazon EC2 and PlanetLab
for deploying INS servers and clients, respectively. It can be
observed from our test results that integrating INS system into
native P2P applications could achieve performance gain to P2P
applications and more network efficient content distribution. For
the example of integrating ALTO and INS system to support file
distribution of CPs, we have shown the feasibility of such
integration.
10. Security Considerations
The authorization token can be passed from one INS client to other
INS clients to authorize other INS clients to access data objects
from its INS storage. Detailed mechanisms of token based
authentication and authorization can be found in [I-D.ietf-decade-
arch].
11. IANA Considerations
This document does not have any IANA considerations.
12. References
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12.1. Normative References
[I-D.ietf-decade-arch] Alimi, R., Yang, Y., Rahman, A., Kutscher, D.,
and H. Liu, "DECADE Architecture", draft-ietf-decade-arch-07 (work in
progress), July 2012.
[I-D.ietf-alto-protocol] Alimi, R., Penno, R., and Y. Yang, "ALTO
Protocol", draft-ietf-alto-protocol-11 (work in progress), March
2012.
12.2. Informative References
[VzApp] "http://www.vuze.com"
[VzMsg] "http://wiki.vuze.com/w/Azureus_messaging_protocol"
[EC2] "http://aws.amazon.com/ec2/"
[PL] "http://www.planet-lab.org/"
Authors' Addresses
Ning Zong (editor)
Huawei Technologies
Email: zongning@huawei.com
Xiaohui Chen
Huawei Technologies
Email: risker.chen@huawei.com
Zhigang Huang
Huawei Technologies
Email: andy.huangzhigang@huawei.com
Lijiang Chen
HP Labs
Email: lijiang.chen@hp.com
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Hongqiang Liu
Yale University
Email: hongqiang.liu@yale.edu
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