Network Working Group C. Griffiths
Request for Comments: 5632 J. Livingood
Category: Informational Comcast
L. Popkin
Pando
R. Woundy
Comcast
Y. Yang
Yale
September 2009
Network Working Group C. Griffiths
Request for Comments: 5632 J. Livingood
Category: Informational Comcast
L. Popkin
Pando
R. Woundy
Comcast
Y. Yang
Yale
September 2009
Comcast's ISP Experiences in a Proactive Network Provider Participation for P2P (P4P) Technical Trial
康卡斯特的ISP在主动网络提供商参与P2P（P4P）技术试验方面的经验
Abstract
摘要
This document describes the experiences of Comcast, a large cable broadband Internet Service Provider (ISP) in the U.S., in a Proactive Network Provider Participation for P2P (P4P) technical trial in July 2008. This trial used P4P iTracker technology, which is being considered by the IETF as part of the Application Layer Transport Optimization (ALTO) working group.
本文件描述了美国大型有线宽带互联网服务提供商（ISP）Comcast在2008年7月参与P2P（P4P）技术试验中的经验。该试验使用了P4P iTracker技术，IETF将其视为应用层传输优化（ALTO）工作组的一部分。
Status of This Memo
关于下段备忘
This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.
本备忘录为互联网社区提供信息。它没有规定任何类型的互联网标准。本备忘录的分发不受限制。
Copyright Notice
版权公告
Copyright (c) 2009 IETF Trust and the persons identified as the document authors. All rights reserved.
版权所有（c）2009 IETF信托基金和确定为文件作者的人员。版权所有。
This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents in effect on the date of publication of this document (http://trustee.ietf.org/license-info). Please review these documents carefully, as they describe your rights and restrictions with respect to this document.
本文件受BCP 78和IETF信托在本文件出版之日生效的与IETF文件有关的法律规定的约束(http://trustee.ietf.org/license-info). 请仔细阅读这些文件，因为它们描述了您对本文件的权利和限制。
Table of Contents
目录
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. High-Level Details . . . . . . . . . . . . . . . . . . . . . . 3
3. Differences between the P4P iTrackers Used . . . . . . . . . . 4
3.1. P4P Fine Grain . . . . . . . . . . . . . . . . . . . . . . 4
3.2. P4P Coarse Grain . . . . . . . . . . . . . . . . . . . . . 5
3.3. P4P Generic Weighted . . . . . . . . . . . . . . . . . . . 5
4. High-Level Trial Results . . . . . . . . . . . . . . . . . . . 5
4.1. Swarm Size . . . . . . . . . . . . . . . . . . . . . . . . 6
4.2. Impact on Download Speed . . . . . . . . . . . . . . . . . 7
4.3. General Impacts on Upstream and Downstream Traffic and
Other Interesting Data . . . . . . . . . . . . . . . . . . 7
5. Important Notes on Data Collected . . . . . . . . . . . . . . 8
6. Next Steps . . . . . . . . . . . . . . . . . . . . . . . . . . 9
7. Security Considerations . . . . . . . . . . . . . . . . . . . 10
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 10
9. Informative References . . . . . . . . . . . . . . . . . . . . 10
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. High-Level Details . . . . . . . . . . . . . . . . . . . . . . 3
3. Differences between the P4P iTrackers Used . . . . . . . . . . 4
3.1. P4P Fine Grain . . . . . . . . . . . . . . . . . . . . . . 4
3.2. P4P Coarse Grain . . . . . . . . . . . . . . . . . . . . . 5
3.3. P4P Generic Weighted . . . . . . . . . . . . . . . . . . . 5
4. High-Level Trial Results . . . . . . . . . . . . . . . . . . . 5
4.1. Swarm Size . . . . . . . . . . . . . . . . . . . . . . . . 6
4.2. Impact on Download Speed . . . . . . . . . . . . . . . . . 7
4.3. General Impacts on Upstream and Downstream Traffic and
Other Interesting Data . . . . . . . . . . . . . . . . . . 7
5. Important Notes on Data Collected . . . . . . . . . . . . . . 8
6. Next Steps . . . . . . . . . . . . . . . . . . . . . . . . . . 9
7. Security Considerations . . . . . . . . . . . . . . . . . . . 10
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 10
9. Informative References . . . . . . . . . . . . . . . . . . . . 10
Comcast is a large broadband Internet Service Provider (ISP), based in the U.S., serving the majority of its customers via cable modem technology. A trial was conducted in July 2008 with Pando Networks, Yale, and several ISP members of the P4P working group, which is part of the Distributed Computing Industry Association (DCIA). Comcast is a member of the DCIA's P4P Working Group, whose mission is to work with Internet Service Providers (ISPs), peer-to-peer (P2P) companies, and technology researchers to develop "P4P" mechanisms, such as so-called "iTrackers" (hereafter P4P iTrackers), that accelerate distribution of content and optimize utilization of ISP network resources. P4P iTrackers theoretically allow P2P networks to optimize traffic within each ISP, reducing the volume of data traversing the ISP's infrastructure and creating a more manageable flow of data. P4P iTrackers can also accelerate P2P downloads for end users.
Comcast是一家大型宽带互联网服务提供商（ISP），总部位于美国，通过电缆调制解调器技术为其大多数客户提供服务。2008年7月，耶鲁大学的Pando Networks和P4P工作组的几个ISP成员进行了一次试验，P4P工作组是分布式计算行业协会（DCIA）的一部分。Comcast是DCIA P4P工作组的成员，其任务是与互联网服务提供商（ISP）、点对点（P2P）公司和技术研究人员合作开发“P4P”机制，如所谓的“iTracker”（以下简称P4P iTracker），加快内容分发，优化ISP网络资源的利用。P4P iTracker理论上允许P2P网络优化每个ISP内的流量，减少通过ISP基础设施的数据量，并创建更易于管理的数据流。P4P iTracker还可以加速最终用户的P2P下载。
P4P's iTracker technology [SIGCOMM] was conceptually discussed with the IETF at the Peer-to-Peer Infrastructure (P2Pi) Workshop held on May 28, 2008, at the Massachusetts Institute of Technology (MIT), as documented in [RFC5594]. This work was discussed in greater detail at the 72nd meeting of the IETF, in Dublin, Ireland, in the ALTO BoF (Birds of a Feather meeting) on July 29, 2008. Due to interest from the community, Comcast shared P4P iTracker trial data at the 73rd meeting of the IETF, in Minneapolis, Minnesota, in the ALTO BoF on November 18, 2008. Since that time, discussion of P4P iTrackers and alternative technologies has continued among participants of the ALTO working group.
在2008年5月28日于麻省理工学院（MIT）举行的对等基础设施（P2Pi）研讨会上，P4P的iTracker技术[SIGCOMM]与IETF进行了概念性讨论，如[RFC5594]所述。2008年7月29日，在爱尔兰都柏林举行的IETF第72次会议上，在ALTO BoF（羽毛鸟会议）上对这项工作进行了更详细的讨论。由于社区的兴趣，Comcast于2008年11月18日在明尼苏达州明尼阿波利斯的ALTO BoF举行的IETF第73次会议上分享了P4P iTracker试验数据。自那时以来，ALTO工作组的参与者继续讨论P4P iTracker和替代技术。
The P4P iTracker trial was conducted, in cooperation with Pando, Yale, and three other P4P member ISPs, from July 2 to July 17, 2008. This was the first P4P iTracker trial over a cable broadband network. The trial used a Pando P2P client, and Pando distributed a special 21-MB licensed video file in order to measure the effectiveness of P4P iTrackers. A primary objective of the trial was to measure the effects that increasing the localization of P2P swarms would have on P2P uploads, P2P downloads, and ISP networks, in comparison to normal P2P activity.
P4P iTracker试验于2008年7月2日至7月17日与Pando、耶鲁和其他三家P4P成员ISP合作进行。这是第一次通过有线宽带网络进行P4P iTracker试验。该试验使用了一个Pando P2P客户端，Pando分发了一个特殊的21MB授权视频文件，以测量P4P iTracker的有效性。该试验的一个主要目标是，与正常的P2P活动相比，测量P2P群集的本地化程度增加对P2P上传、P2P下载和ISP网络的影响。
As noted in Section 1 of [DynamicSwarmMgmt], a swarm is defined in the following way:
如[DynamicWarmmGMT]第1节所述，swarm的定义如下：
The content and the set of peers distributing it [a file] is usually called a torrent. A peer that only uploads content is called a seed, while a peer that uploads and downloads at the same time is called a leecher. The connected set of peers participating in the piece exchanges of a torrent is referred to as a swarm.
内容和分发它的对等点集[文件]通常称为torrent。只上传内容的对等方称为种子，同时上传和下载内容的对等方称为leecher。参与torrent片段交换的连接对等点集称为swarm。
There were five different swarms for the content used in the trial. The second, third, and fourth used different P4P iTrackers: Generic, Coarse Grained, and Fine Grained, all of which are described in Section 3. The fifth was a proprietary Pando mechanism. (The results of the fifth swarm, while satisfactory, are not included here since our focus is on open standards and a mechanism that may be leveraged for the benefit of the entire community of P2P clients.) Comcast deployed a P4P iTracker server in its production network to support this trial, and configured multiple iTracker files to provide varying levels of localization to clients.
试验中使用的内容有五个不同的群组。第二个、第三个和第四个使用了不同的P4P iTracker：通用、粗粒度和细粒度，所有这些都在第3节中描述。第五个是专有的潘多机制。（第五个swarm的结果虽然令人满意，但此处不包括在内，因为我们的重点是开放标准和一种可以为整个P2P客户端社区带来好处的机制。）Comcast在其生产网络中部署了一台P4P iTracker服务器以支持此试验，并配置多个iTracker文件，为客户端提供不同级别的本地化。
In the trial itself, a P2P client begins a P2P session by querying a pTracker, which runs and manages the P2P network. The pTracker occasionally queries the P4P iTracker, which in this case was maintained by Comcast, the ISP. Other ISPs either managed their own P4P iTracker or used Pando or Yale to host their P4P iTracker files. The P4P iTracker returns network topology information to the pTracker, which then communicates with P2P clients, in order to enable P2P clients to make network-aware decisions regarding peers.
在试验中，P2P客户端通过查询运行和管理P2P网络的pTracker来启动P2P会话。pTracker偶尔会查询P4P iTracker，在本例中，它是由ISP Comcast维护的。其他ISP要么管理自己的P4P iTracker，要么使用Pando或Yale托管其P4P iTracker文件。P4P iTracker将网络拓扑信息返回给pTracker，然后pTracker与P2P客户端进行通信，以使P2P客户端能够做出关于对等点的网络感知决策。
The Pando client was enabled to capture extended logging, when the version of the client included support for it. The extended logging included the source and destination IP address of all P2P transfers, the number of bytes transferred, and the start and end timestamps. This information gives a precise measurement of the data flow in the network, allowing computation of data transfer volumes as well as
当客户机版本包含对扩展日志记录的支持时，Pando客户机已启用以捕获扩展日志记录。扩展日志记录包括所有P2P传输的源和目标IP地址、传输的字节数以及开始和结束时间戳。该信息提供了网络中数据流的精确测量，允许计算数据传输量以及
data flow rates at each point in time. With standard logging, Pando captured the start and completion times of every download, as well as the average transfer rate observed by the client for the download.
每个时间点的数据流量。通过标准日志记录，Pando捕获了每次下载的开始和完成时间，以及客户端观察到的下载平均传输速率。
Pando served the data from an origin server external to Comcast's network. This server served about 10 copies of the file, after which all transfers (about 1 million downloads across all ISPs) were performed purely via P2P.
Pando从Comcast网络外部的源服务器提供数据。该服务器提供了大约10份文件副本，之后所有传输（所有ISP中约100万次下载）都完全通过P2P进行。
The P2P clients in the trial start with tracker-provided peers, then use peer exchange to discover additional peers. Thus, the initial peers were provided according to P4P iTracker guidance (90% guidance based on P4P iTracker topology and 10% random guidance), then later peers discover the entire swarm via either additional announces or peer exchange.
试验中的P2P客户端首先使用tracker提供的对等点，然后使用对等点交换来发现其他对等点。因此，最初的对等点是根据P4P iTracker指导（90%的指导基于P4P iTracker拓扑和10%的随机指导）提供的，然后对等点通过额外的通告或对等点交换发现整个群。
Given the size of the Comcast network, it was felt that in order to truly evaluate the P4P iTracker application we would need to test various network topologies that reflected its network and would help gauge the level of effort and design requirements necessary to get correct statistical data out of the trial. In all cases, P4P iTrackers were configured with automation in mind, so that any successful P4P iTracker configuration would be automatically updating, rather than manually configured on an ongoing basis. All P4P iTrackers were hosted on the same small server, and it appeared to be relatively easy and inexpensive to scale up a P4P iTracker infrastructure should P4P iTracker-like mechanisms become standardized and widely adopted.
考虑到Comcast网络的规模，我们认为为了真正评估P4P iTracker应用程序，我们需要测试反映其网络的各种网络拓扑，并帮助衡量从试验中获得正确统计数据所需的工作水平和设计要求。在所有情况下，P4P iTracker的配置都考虑了自动化，因此任何成功的P4P iTracker配置都将自动更新，而不是持续手动配置。所有P4P iTracker都托管在同一台小型服务器上，如果P4P iTracker类机制变得标准化并被广泛采用，则扩展P4P iTracker基础设施似乎相对容易且成本低廉。
The Fine Grain topology was the first and most complex P4P iTracker that we built for this trial. It was a detailed mapping of Comcast backbone-connected network Autonomous System Numbers (ASNs) to IP Aggregates, which were weighted based on priority and distance from each other. Included in this design was a prioritization of all Peer and Internet transit connected ASNs to the Comcast backbone to ensure that P4P traffic would prefer settlement-free and lower-cost networks first, and then more expensive transit links. This attempted to optimize and lower transit costs associated with this traffic. We then took the additional step of detailing each ASN and IP Aggregate into IP subnets down to Optical Transport Nodes (OTNs) where all Cable Modem Termination Systems (CMTS, as briefly defined in Section 2.6 of [RFC3083]) reside . This design gave a highly localized and detailed description of the Comcast network for the iTracker to disseminate. This design defined 1,182 P4P iTracker node
细粒度拓扑是我们为本次试验构建的第一个也是最复杂的P4P iTracker。这是Comcast主干连接网络自治系统编号（ASN）到IP聚合的详细映射，IP聚合根据优先级和彼此之间的距离进行加权。该设计包括优先考虑将所有对等和互联网传输连接的ASN连接到Comcast主干网，以确保P4P流量优先选择无结算且成本较低的网络，然后选择更昂贵的传输链路。这试图优化和降低与此流量相关的运输成本。然后，我们采取了额外的步骤，将每个ASN和IP聚合细化为IP子网，直至光传输节点（OTN），所有电缆调制解调器终端系统（CMT，如[RFC3083]第2.6节中的简要定义）都位于该节点。该设计对iTracker传播的Comcast网络进行了高度本地化和详细的描述。本设计定义了1182 P4P iTracker节点
identifiers, and resulted in a 107,357-line configuration file.
标识符，并生成107357行配置文件。
This P4P iTracker was obviously the most time-consuming to create and the most complex to maintain. Trial results indicated that this level of localization was too high, and was less effective compared to lower levels of localization.
这个P4P iTracker显然是创建最耗时、维护最复杂的。试验结果表明，这种定位水平太高，与较低的定位水平相比效果较差。
Given the level of detail in the Fine Grain design, it was important that we also enable a high-level design, which still used priority and weighting mechanisms for the Comcast backbone and transit links. The Coarse Grain design was a limited or summarized version of the Fine Grain design, which used the ASN to IP Aggregate and weighted data for transit links, but removed all additional localization data. This ensured we would get similar data sets from the Fine Grain design, but without the more detailed localization of each of the networks attached to the Comcast backbone. This design defined 22 P4P iTracker node identifiers, and resulted in a 998-line configuration file.
考虑到细粒度设计的详细程度，我们还必须启用高级别设计，该设计仍然使用Comcast主干和传输链路的优先级和权重机制。粗粒度设计是细粒度设计的一个有限或总结版本，它使用ASN-to-IP聚合和公交链路加权数据，但删除了所有附加的本地化数据。这确保了我们可以从细粒度设计中获得类似的数据集，但不需要对连接到Comcast主干网的每个网络进行更详细的本地化。此设计定义了22个P4P iTracker节点标识符，并生成了998行配置文件。
From an overall cost, complexity, risk, and effectiveness standpoint, this was judged to be the optimal P4P iTracker for Comcast. Importantly, this did not require revealing the complex, internal network topology that the Fine Grain did. Updates to this iTracker were also far simpler to automate, which will better ensure that it is accurate over time, and keeps administrative overhead relatively low. However, the differences, costs, and benefits of Coarse Grain and Generic Weighted (see below) likely merit further study.
从总体成本、复杂性、风险和有效性的角度来看，这被认为是Comcast的最佳P4P iTracker。重要的是，这不需要像细粒度那样揭示复杂的内部网络拓扑。对这个iTracker的更新也更容易自动化，这将更好地确保它随着时间的推移是准确的，并保持相对较低的管理开销。然而，粗粮和普通加权（见下文）的差异、成本和效益可能值得进一步研究。
The Generic Weighted design was a copy of the Coarse Grained design, but instead of using ISP-designated priority and weights, all weights were defaulted to pre-determined parameters that the Yale team had designed. All other data was replicated from the Coarse Grain design. Gathering and providing the information necessary to support the Generic Weighted iTracker was roughly the same level of effort as for Coarse Grain.
通用加权设计是粗粒度设计的副本，但不是使用ISP指定的优先级和权重，而是将所有权重默认为耶鲁团队设计的预定义参数。所有其他数据均从粗粒设计中复制。收集和提供支持通用加权iTracker所需的信息的工作水平与粗粒度大致相同。
Trial data was collected by Pando Networks and Yale University, and raw trial results were shared with Comcast and all of the other ISPs involved in the trial. Analysis of the raw results was performed by Pando and Yale, and these organizations delivered an analysis of the P4P iTracker trial. Using the raw data, Comcast also analyzed the trial results. Furthermore, the raw trial results for Comcast were
试验数据由Pando Networks和耶鲁大学收集，原始试验结果与Comcast和参与试验的所有其他ISP共享。Pando和耶鲁大学对原始结果进行了分析，这些组织对P4P iTracker试验进行了分析。康卡斯特还利用原始数据分析了试验结果。此外，Comcast的原始试验结果如下：
shared with Net Forecast, Inc., which performed an independent analysis of the trial for Comcast.
与Net Forecast，Inc.分享，后者对Comcast的试验进行了独立分析。
During the trial, downloads peaked at 24,728 per day, per swarm, or nearly 124,000 per day for all five swarms. The swarm size peaked at 11,703 peers per swarm, or nearly 57,000 peers for all five swarms. We observed a comparable number of downloads in each of the five swarms.
在试用期间，每群的下载量达到了每天24728次的峰值，五个群的下载量都接近每天124000次。群体规模达到峰值，每个群体有11703个对等点，或所有五个群体有近57000个对等点。我们观察到五个群组中的每一个都有相当数量的下载。
For each swarm, Table 1 below gives the number of downloads per swarm from Comcast that finished downloading, and the number of downloads from Comcast that canceled downloading before finishing.
对于每个swarm，下表1给出了Comcast完成下载的每个swarm的下载次数，以及Comcast在完成下载之前取消下载的下载次数。
Characteristics of P4P iTracker Swarms:
P4P iTracker群的特征：
+-----------+-----------+---------------+------------+--------------+
| Swarm | Completed | Cancellations | Total | Cancellation |
| | Downloads | | Attempts | Rate |
+-----------+-----------+---------------+------------+--------------+
| Random | 2,719 | 89 | 2,808 | 3.17% |
| (Control) | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P Fine | 2,846 | 64 | 2,910 | 2.20% |
| Grained | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P | 2,775 | 63 | 2,838 | 2.22% |
| Generic | | | | |
| Weight | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P | 2,886 | 52 | 2,938 | 1.77% |
| Coarse | | | | |
| Grained | | | | |
+-----------+-----------+---------------+------------+--------------+
+-----------+-----------+---------------+------------+--------------+
| Swarm | Completed | Cancellations | Total | Cancellation |
| | Downloads | | Attempts | Rate |
+-----------+-----------+---------------+------------+--------------+
| Random | 2,719 | 89 | 2,808 | 3.17% |
| (Control) | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P Fine | 2,846 | 64 | 2,910 | 2.20% |
| Grained | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P | 2,775 | 63 | 2,838 | 2.22% |
| Generic | | | | |
| Weight | | | | |
| --------- | --------- | ----------- | ---------- | ----------- |
| P4P | 2,886 | 52 | 2,938 | 1.77% |
| Coarse | | | | |
| Grained | | | | |
+-----------+-----------+---------------+------------+--------------+
Table 1: Per-Swarm Size and Cancellation Rates
表1：每群大小和取消率
The results of the trial indicated that P4P iTrackers can improve the speed of downloads to P2P clients. In addition, P4P iTrackers were effective in localizing P2P traffic within the Comcast network.
试验结果表明，P4P iTracker可以提高P2P客户端的下载速度。此外，P4P iTracker可有效地在Comcast网络中定位P2P流量。
Impact of P4P iTrackers on Downloads:
P4P iTracker对下载的影响：
+--------------+------------+------------+-------------+------------+
| Swarm | Global Avg | Change | Comcast Avg | Change |
| | bps | | bps | |
+--------------+------------+------------+-------------+------------+
| Random | 144,045 | n/a | 254,671 bps | n/a |
| (Control) | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Fine | 162,344 | +13% | 402,043 bps | +57% |
| Grained | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Generic | 163,205 | +13% | 463,782 bps | +82% |
| Weight | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Coarse | 166,273 | +15% | 471,218 bps | +85% |
| Grained | bps | | | |
+--------------+------------+------------+-------------+------------+
+--------------+------------+------------+-------------+------------+
| Swarm | Global Avg | Change | Comcast Avg | Change |
| | bps | | bps | |
+--------------+------------+------------+-------------+------------+
| Random | 144,045 | n/a | 254,671 bps | n/a |
| (Control) | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Fine | 162,344 | +13% | 402,043 bps | +57% |
| Grained | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Generic | 163,205 | +13% | 463,782 bps | +82% |
| Weight | bps | | | |
| ---------- | ---------- | ---------- | ---------- | ---------- |
| P4P Coarse | 166,273 | +15% | 471,218 bps | +85% |
| Grained | bps | | | |
+--------------+------------+------------+-------------+------------+
Table 2: Per-Swarm Global and Comcast Download Speeds
表2：每群全球和Comcast下载速度
4.3. General Impacts on Upstream and Downstream Traffic and Other Interesting Data
4.3. 对上下游交通和其他有趣数据的一般影响
An analysis of the effects of P4P iTracker use on upstream utilization and Internet transit was also interesting. It did not appear that P4P iTrackers significantly increased upstream utilization in the Comcast access network; in essence, uploading was already occurring no matter what and a P4P iTracker in and of itself did not appear to materially increase uploading for this specific, licensed content. (A P4P iTracker is not intended as a solution for the potential of network congestion to occur.) Random was 143,236 MB and P4P Generic Weight was 143,143 MB, while P4P Coarse Grained was 139,669 MB. We also observed that using a P4P iTracker reduced outgoing Internet traffic by an average of 34% at peering points. Random was 134,219 MB and P4P Generic Weight was 91,979 MB, while P4P Coarse Grained was 86,652 MB.
分析P4P iTracker的使用对上游利用率和互联网传输的影响也很有趣。P4P iTracker似乎并未显著提高Comcast接入网络中的上游利用率；本质上，无论发生什么情况，上传都已经发生，P4P iTracker本身似乎并没有实质性地增加这一特定许可内容的上传。（P4P iTracker不用于解决可能出现的网络拥塞。）Random为143236 MB，P4P通用权重为143143 MB，而P4P粗粒度为139669 MB。我们还观察到，使用P4P iTracker在对等点平均减少了34%的传出Internet流量。随机值为134219MB，P4P通用权重为91979MB，而P4P粗粒度为86652MB。
In terms of downstream utilization, we observed that the use of a P4P iTracker reduced incoming Internet traffic by an average of 80% at peering points. Random was 47,013 MB, P4P Generic Weight was 8,610 MB, and P4P Coarse Grained was 7,764 MB. However, we did notice that
在下游利用率方面，我们观察到使用P4P iTracker在对等点将传入的Internet流量平均减少80%。随机数为47013MB，P4P通用权重为8610MB，P4P粗粒度为7764MB。然而，我们确实注意到
download activity in the Comcast access network increased somewhat, from 56,030 MB for Random, to 59,765 MB for P4P Generic Weight, and 60,781 MB for P4P Coarse Grained. Note that for each swarm, the number of downloaded bytes according to logging reports is very close to the number of downloads multiplied by file size. But they do not exactly match due to log report errors and duplicated chunks. One factor contributing to the differences in access network download activity is that different swarms have different numbers of downloaders, due to random variations during uniform random assignment of downloaders to swarms (see Table 1). One interesting observation is that Random has higher cancellation rate (3.17%) than that of the guided swarms (1.77%-2.22%). Whether guided swarms achieve lower cancellation rate is an interesting issue for future research.
Comcast访问网络中的下载活动有所增加，从随机的56030 MB增加到P4P通用重量的59765 MB，以及P4P粗粒度的60781 MB。请注意，对于每个swarm，根据日志记录报告下载的字节数与下载数乘以文件大小非常接近。但由于日志报告错误和重复的数据块，它们并不完全匹配。导致接入网络下载活动差异的一个因素是，不同的群组有不同数量的下载者，这是由于在将下载者均匀随机分配给群组的过程中随机变化造成的（见表1）。一个有趣的观察结果是，随机群的对消率（3.17%）高于引导群（1.77%-2.22%）。引导群集是否能实现较低的取消率是未来研究的一个有趣问题。
Raw data is presented in this document. We did not normalize traffic volume data (e.g., upload and download) by the number of downloads in order to preserve this underlying raw data.
本文件提供了原始数据。我们没有通过下载次数来规范流量数据（例如，上传和下载），以保留这些底层原始数据。
We also recommend that readers not focus too much on the absolute numbers, such as bytes downloaded from internal sources and bytes downloaded from external sources. Instead, we recommend readers focus on ratios such as the percentage of bytes downloaded that came from internal sources in each swarm. As a result, the small random variation between number of downloads of each swarm does not distract readers from important metrics like shifting traffic from external to internal sources, among other things.
我们还建议读者不要过于关注绝对数字，例如从内部源下载的字节和从外部源下载的字节。相反，我们建议读者关注比率，例如每个swarm中来自内部源的下载字节的百分比。因此，每个swarm的下载数量之间的微小随机变化不会分散读者对重要指标的注意力，例如将流量从外部来源转移到内部来源等。
We also wish to note that the data was collected from a sample of the total swarm. Specifically, there were some peers running older versions of the Pando client that did not implement the extended transfer logging. For those nodes, which participated in the swarms but did not report their data transfers, we have download counts. The result of this is that, for example, the download counts generated from the standard logging are a bit higher than the download counts generated by the extended logging. That being said, over 90% of downloads were by peers running the newer software, which we believe shows that the transfer records are highly representative of the total data flow.
我们还希望指出，这些数据是从整个蜂群的样本中收集的。具体来说，有些运行较旧版本的Pando客户端的对等机没有实现扩展传输日志记录。对于那些参与群集但未报告其数据传输的节点，我们有下载计数。这样做的结果是，例如，标准日志生成的下载计数略高于扩展日志生成的下载计数。也就是说，超过90%的下载是由运行较新软件的同行完成的，我们认为这表明传输记录高度代表了整个数据流。
In terms of which analysis was performed from the standard logging compared to extended logging, all of the data flow analysis was performed using the extended logging. Pando's download counts and performance numbers were generated via standard logging (i.e., all peers report download complete/cancel, data volumes, and measured download speed on the client). Yale's download counts and
与扩展日志相比，标准日志执行的分析，所有数据流分析都是使用扩展日志执行的。Pando的下载计数和性能数字是通过标准日志记录生成的（即，所有对等方报告下载完成/取消、数据量和客户端上测量的下载速度）。耶鲁大学的下载量和
performance numbers were derived via extended logging (e.g., by summing the transfer records, counting IP addresses reported, etc.).
性能数字是通过扩展日志记录（例如，通过对传输记录求和、计算报告的IP地址等）得出的。
One benefit of having two data sources is that we can compare the two. In this case, the two approaches both reported comparable impacts.
拥有两个数据源的一个好处是我们可以比较这两个数据源。在这种情况下，两种方法都报告了类似的影响。
One objective of this document is to share with the IETF community the results of one P4P iTracker trial in a large broadband network, given skepticism regarding the benefits to P2P users as well as to ISPs. From the perspective of P2P users, P4P iTrackers potentially deliver faster P2P downloads. At the same time, ISPs can increase the localization of swarms, enabling them to reduce bytes flowing over transit points, while also delivering an optimized P2P experience to customers. However, an internal analysis of varying levels of P4P iTracker adoption by ISPs leads us to believe that, while P4P iTracker-type mechanisms are valuable on a single ISP basis, the value of P4P iTrackers increases dramatically as many ISPs choose to deploy it.
鉴于对P2P用户和ISP的益处持怀疑态度，本文件的一个目的是与IETF社区分享一个大型宽带网络中P4P iTracker试验的结果。从P2P用户的角度来看，P4P iTracker可能提供更快的P2P下载。与此同时，ISP可以提高群集的本地化程度，使它们能够减少通过中转点的字节流，同时也为客户提供优化的P2P体验。然而，对ISP采用P4P iTracker的不同级别的内部分析使我们相信，虽然P4P iTracker类型的机制在单个ISP基础上是有价值的，但随着许多ISP选择部署P4P iTracker，P4P iTracker的价值会急剧增加。
We believe these results can inform the technical discussion in the IETF over how to use P4P iTracker mechanisms. Should such a mechanism be standardized, the use of ISP-provided P4P iTrackers should probably be an opt-in feature for P2P users, or at least a feature of which they are explicitly aware of and which has been enabled by default in a particular P2P client. In this way, P2P users could choose to opt-in either explicitly or by their choice of P2P client in order to choose to use the P4P iTracker to improve performance, which benefits both the user and the ISP at the same time. Importantly in terms of privacy, the P4P iTracker makes available only network topology information, and would not in its current form enable an ISP, via the P4P iTracker, to determine which P2P clients were downloading any specific content, whether to determine, for example, if content was a song or a movie or even the title.
我们相信这些结果可以为IETF中关于如何使用P4P iTracker机制的技术讨论提供信息。如果这样一种机制被标准化，ISP提供的P4P iTracker的使用可能是P2P用户的一种选择加入功能，或者至少是他们明确知道并在特定P2P客户端中默认启用的一种功能。通过这种方式，P2P用户可以选择显式加入，也可以通过选择P2P客户端来选择使用P4P iTracker来提高性能，这对用户和ISP都有好处。重要的是，就隐私而言，P4P iTracker仅提供网络拓扑信息，并且其当前形式不允许ISP通过P4P iTracker确定哪些P2P客户端正在下载任何特定内容，例如，是否确定内容是歌曲或电影，甚至是标题。
It is also possible that a P4P iTracker type of mechanism, in combination with a P2P cache, could further improve P2P download performance, which merits further study. In addition, this was a limited trial that, while very promising, indicates a need for additional technical investigation and trial work. Such a follow-up study should explore the effects of P4P iTrackers when more P2P client software variants are involved, with larger swarms, and with additional and more technically diverse content (file size, file type, duration of content, etc.).
P4P iTracker类型的机制与P2P缓存相结合也可能进一步提高P2P下载性能，这值得进一步研究。此外，这是一次有限的试验，虽然很有希望，但表明需要进行额外的技术调查和试验工作。这样的后续研究应该探索P4P iTracker在涉及更多P2P客户端软件变体、更大的群组以及更多且技术上更多样化的内容（文件大小、文件类型、内容持续时间等）时的效果。
This document does not propose any kind of protocol, practice or standard.
本文件未提出任何协议、惯例或标准。
The experiment did show that an ISP can improve performance without exposing fine-grained details about network structure, which might otherwise be a security concern (see Section 3.1 (P4P Fine Grain) and Section 3.2 (P4P Coarse Grain). Section 6 (Next Steps) mentions that the opt-in architecture allows P2P users to maintain privacy.
实验确实表明，ISP可以在不暴露网络结构的细粒度细节的情况下提高性能，否则可能会引起安全问题（参见第3.1节（P4P细粒度）和第3.2节（P4P粗粒度）。第6节（下一步）提到，选择加入架构允许P2P用户维护隐私。
Other security aspects were not considered in the experiment, which focused on performance measurements.
实验中没有考虑其他安全方面，主要关注性能度量。
The authors wish to acknowledge the hard work of all of the P4P working group members, and specifically the focused efforts of the teams at both Pando and Yale for the trial itself. Finally, the authors recognize and appreciate Peter Sevcik and John Bartlett of NetForecast, Inc., for their valued independent analysis of the trial results.
作者希望感谢P4P工作组所有成员的辛勤工作，特别是Pando和耶鲁大学的团队为试验本身所做的集中努力。最后，作者感谢NetForecast，Inc.的Peter Sevcik和John Bartlett对试验结果进行了有价值的独立分析。
[DynamicSwarmMgmt] Carlsson, N. and G. Dan, "Dynamic Swarm Management for Improved BitTorrent Performance", USENIX 8th International Workshop on Peer-to-Peer Systems, March 2009, <http://www.usenix.org/events/iptps09/tech/full_papers/ dan/dan_html/>.
[DynamicWarmmGMT]Carlsson，N.和G.Dan，“动态群集管理提高BitTorrent性能”，USENIX第八届对等系统国际研讨会，2009年3月<http://www.usenix.org/events/iptps09/tech/full_papers/ dan/dan_html/>。
[RFC3083] Woundy, R., "Baseline Privacy Interface Management Information Base for DOCSIS Compliant Cable Modems and Cable Modem Termination Systems", RFC 3083, March 2001.
[RFC3083]Woundy，R.，“符合DOCSIS标准的电缆调制解调器和电缆调制解调器终端系统的基线隐私接口管理信息库”，RFC 3083，2001年3月。
[RFC5594] Peterson, J. and A. Cooper, "Report from the IETF Workshop on Peer-to-Peer (P2P) Infrastructure, May 28, 2008", RFC 5594, July 2009.
[RFC5594]Peterson，J.和A.Cooper，“IETF对等（P2P）基础设施研讨会报告，2008年5月28日”，RFC 55942009年7月。
[SIGCOMM] Xie, H., Yang, Y., Krishnamurthy, A., Liu, Y., and A. Silberschatz, "ACM SIGCOMM 2008 - P4P: Provider Portal for Applications", Association for Computing Machinery SIGCOMM 2008 Proceedings, August 2008, <http://ccr.sigcomm.org/online/files/p351-xieA.pdf>.
[SIGCOMM]谢，H.，杨，Y.，Krishnamurthy，A.，刘，Y.，和A.Silberschatz，“ACM SIGCOMM 2008-P4P：应用程序提供商门户”，计算机械协会SIGCOMM 2008年会议记录，2008年8月<http://ccr.sigcomm.org/online/files/p351-xieA.pdf>.
Authors' Addresses
作者地址
Chris Griffiths Comcast Cable Communications One Comcast Center 1701 John F. Kennedy Boulevard Philadelphia, PA 19103 US
克里斯·格里菲斯康卡斯特有线通信一康卡斯特中心美国宾夕法尼亚州费城肯尼迪大道1701号，邮编：19103
EMail: chris_griffiths@cable.comcast.com
URI: http://www.comcast.com
EMail: chris_griffiths@cable.comcast.com
URI: http://www.comcast.com
Jason Livingood Comcast Cable Communications One Comcast Center 1701 John F. Kennedy Boulevard Philadelphia, PA 19103 US
美国宾夕法尼亚州费城约翰·F·肯尼迪大道1701号康卡斯特一号康卡斯特有线通信中心Jason Livingood
EMail: jason_livingood@cable.comcast.com
URI: http://www.comcast.com
EMail: jason_livingood@cable.comcast.com
URI: http://www.comcast.com
Laird Popkin Pando Networks 520 Broadway Street 10th Floor New York, NY 10012 US
美国纽约州纽约市百老汇大街520号10楼莱尔德·波普金·潘多网络公司，邮编：10012
EMail: laird@pando.com
URI: http://www.pando.com
EMail: laird@pando.com
URI: http://www.pando.com
Richard Woundy Comcast Cable Communications 27 Industrial Avenue Chelmsford, MA 01824 US
美国马萨诸塞州切姆斯福德工业大道27号Richard Woundy Comcast电缆通信公司01824
EMail: richard_woundy@cable.comcast.com
URI: http://www.comcast.com
EMail: richard_woundy@cable.comcast.com
URI: http://www.comcast.com
Richard Yang Yale University 51 Prospect Street New Haven, CT 06520 US
理查德·杨耶鲁大学美国CT纽黑文前景街51号06520
EMail: yry@cs.yale.edu
URI: http://www.cs.yale.edu
EMail: yry@cs.yale.edu
URI: http://www.cs.yale.edu