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Transcript of My PhD thesis defense presentation
Improving Content Delivery and Service Discovery in Networks
Thesis Defense
Suman Srinivasan
Advisor: Professor Henning Schulzrinne
Feb 5, 2016
Problem Statement: Summary
• The age of mobile and video is here
• Internet and IP architectures were not designed to optimally handle:• Large numbers of mobile devices at the edge• Large volume of multimedia traffic over TCP/IP
• We need smarter network infrastructure and architectures to • Better transport video and other multimedia
content• Over IP or other protocols• To mobile devices and other client devices
Improving Content Delivery and Service Discovery in Networks 2
Problem Statement I: Mobile
• Smartphone and mobile usage is growing dramatically
• Global handset data usage could exceed 20 petabytes by 2017 – TechCrunch
• In some countries, mobile traffic as a percentage of total internet traffic is already higher than 50% -MarketingLand
Improving Content Delivery and Service Discovery in Networks 3
Problem Statement II: Video
• Separately, the consumption of video content online is also increasing
• Research company Sandvine reports that over 70.4% of peak period traffic in North America is “real-time entertainment” (2015)• Of this, more than 54% is from just two
sources: Netflix and Youtube
• Source: Recode
Improving Content Delivery and Service Discovery in Networks 4
Contributions in My Thesis
1. Analyze data usage and working of core protocols (DNS, HTTP, service discovery) and video traffic
2. Implementation of new software and networking architectures
3. Designed new protocols and architectures to handle increasing data at network core
4. Architected research prototypes for content-centric networking
Improving Content Delivery and Service Discovery in Networks 5
In My Talk Today
• Opportunistic Networks• 7DS application suite• BonAHA library
• Content Delivery Networks• On-path CDN• ActiveCDN
• Content Centric Networks• CCNxServ
• Internet video viewing: analysis• JWPlayer’s video data set
• Will not cover• mDNS service discovery
traffic analysis and implementation improvements
• IPv6 as a content centric network protocol
• Both of these are explained in more detail in thesis
Improving Content Delivery and Service Discovery in Networks 6
Opportunistic Networks7DS & BonAHA
Improving Content Delivery and Service Discovery in Networks 7
7DS Application Suite
• Scenario: mobile devices without Internet connectivity need to exchange useful information
• Solution: 7DS application suite• 7DS = Seven Degrees of Separation
• Use local peer-to-peer wireless networks to exchange information
• Once wireless 7DS network set up, it could be used for any purpose• Getting web pages from peers; sending e-mails; file transfer
• Suman Srinivasan, Arezu Moghadam, Se Gi Hong, Henning G Schulzrinne, "7DS - Node Cooperation andInformation Exchange in Mostly Disconnected Networks", IEEE ICC 2007, Glasgow, Scotland, Jun 2007.• Arezu Moghadam, Suman Srinivasan, Henning Schulzrinne, "7DS - A Modular Platform to Develop MobileDisruption-tolerant Applications", IEEE NGMAST 2008, Wales, UK, September 2008.
Improving Content Delivery and Service Discovery in Networks 8
7DS: Establishing a Connection
Establishing the connection
zeroconf
Improving Content Delivery and Service Discovery in Networks 9
7DS: Get Data
Get available data from peers
Improving Content Delivery and Service Discovery in Networks 10
Design
• Peer-to-peer network set up using zeroconf service discovery• Protocol enables devices to discover each other without a DHCP server
• Proxy server serves content• If connected to Internet, functions normally• If not connected, works in “7DS mode”: connects to peers to get information
• Search engine• Allows node to search its own database for necessary information
• Multicast querying system• Allows nodes to query other peer nodes in local network• Searches can be for files or keywords
• Transport System• To forward e-mail
Improving Content Delivery and Service Discovery in Networks 11
Query Multicast Engine
• Used to actually exchange information among peers
• Requesting peer broadcasts a query to the network
• Responding peers reply if they have information
• Send encoded string with list of matching items
• Requesting peer retrieves suitable information
Improving Content Delivery and Service Discovery in Networks 12
BonAHA Library
• 7DS is only one of a new class of applications• “Ad-hoc/Mobile-P2P applications” that run in opportunistic networks
• Applications in such a network need to• Be aware of network transitions & state/metadata of other nodes• Can’t rely on client-server or stable infrastructure environments
• BonAHA library = Bonjour for Ad-Hoc Applications• Aims to be a framework that solves these problems
• Application examples• Group chat; File transfer; File synchronization; Local multiplayer games
• Suman Srinivasan, Arezu Moghadam, Henning Schulzrinne, "BonAHA: Service Discovery Framework forMobile Ad-Hoc Applications", IEEE Consumer Communications & Networking Conference 2009 (CCNC'09),Las Vegas, USA, January 2009.
Improving Content Delivery and Service Discovery in Networks 13
BonAHA framework
Node 2
Node 1
key21 = value21
key22 = value22
key23 = value23
key24 = value24
key11 = value11
key12 = value12
key13 = value13
key14 = value14
[2] node1.get(key13)
[1] node1.register()
[3] data =node1.fileGet(
value13);
Improving Content Delivery and Service Discovery in Networks 14
Code: LocationFinder
• Very simple, impractical application• Only for providing a quick code
sample
• Scenario• Two nodes meet each other
• Lack global knowledge of location
• Each can find out other’s last location information and update their own location
Improving Content Delivery and Service Discovery in Networks 15
Compare: Bonjour Code
Improving Content Delivery and Service Discovery in Networks 16
BonAHA Applications
BBS application
• Runs on iPod/iPhone
• Allows users to upload “posts”
• Other users can pick up “posts” and share their own
• Information on events, etc that they are interested in sharing
• Kiwoon Sung, Suman Srinivasan, Henning Schulzrinne, "BBS-ONE: Bulletin Board and Forum System for MobileOpportunistic Networks", IEEE WCNIS 2010, June 2010.
Improving Content Delivery and Service Discovery in Networks 17
Related Work
• Proem (2001)• Runs on “peerlet engine”• No public documentation of API
• JXTA Java library• Excellent for P2P• Heavyweight for our goals
• Peer2Me (2004)• File transfer on Bluetooth
• LightPeers• Sep 2007 PhD dissertation (B.
Christensen)• Similar model to BonAHA
• “Application”: Each application has its own GUID that identifies it
• “Session”: A group of nodes registered as running the application
• Code• Application app = new Application(appid);
• lpconn = new Connection(app);
• ses = lpconn.CreateSession();
• List<Session> sessions = lpconn.GetSessionList();
Improving Content Delivery and Service Discovery in Networks 18
Related Work
• LightPeers: differences with BonAHA• PING packet sent every second to search for peers
• In Bonjour, there is exponential backoff
• No library-daemon interface• LP “server” listens to packets
• Reimplementation of entire architecture + service discovery
• Bump app for iPhone and Android• Physically “bump” two phones to transfer data
• Actually connects to Bump server and transmits location info
• Fundamentally different architecture
Improving Content Delivery and Service Discovery in Networks 19
Content Delivery NetworksOn-Path CDN and ActiveCDN
Improving Content Delivery and Service Discovery in Networks 20
Content Delivery Networks (CDNs)
• Used by pretty much all major publishers today to deliver content to end users• Publishers offload their data to a CDN network,
which delivers content to the user
• CDNs cache content in network to get multimedia content to end user faster• Peering agreements with ISPs
• Co-located or closely located servers
• Involves some redirection
• DNS redirection: most commonly used
• The “Akamai model”
• Youtube uses HTTP redirection
• Requires setting up CDN node in advance
Wikipedia
Improving Content Delivery and Service Discovery in Networks 21
DNS redirection: CNN Video callflows
$ host ht.cdn.turner.com
ht.cdn.turner.com is an alias for vid.cnn.com.edgesuite.net.
vid.cnn.com.edgesuite.net is an alias for a1320.g.akamai.net.
a1320.g.akamai.net has address 96.17.77.82
a1320.g.akamai.net has address 96.17.77.83
HTTP request for
Flash player
HTTP request for
ad video
HTTP request for
content video
ht.cdn.turner.com is actually an alias for an Akamai server
Improving Content Delivery and Service Discovery in Networks 22
On-Path Content Distribution Networks
• Any node on path can serve content from cache• No redirection using HTTP/DNS
• Less traffic on the network; highly localized caching
• Reduced delay for end users and service providers
• Suman Srinivasan, Ivica Rimac, Volker Hilt, Moritz Steiner, Henning Schulzrinne, "Unveiling the content-centric features of TCP", IEEE ICC 2011, Kyoto, Japan, June 2011.
Improving Content Delivery and Service Discovery in Networks 23
On-path CDN: three possible architectures
• Initial design: came up with three possible architectures• #1. UDP signaling
• #2. UDP signaling and TCP SYN interception
• #3. TCP SYN interception, modifying SYN packet and proxy acting as a NAT
• Final implementation was of #3: a proxy that intercepted SYN and acted as a NAT
• Volker Hilt, Ivica Rimac, Suman Srinivasan,Moritz Steiner, "Method For Providing On-PathContent Distribution", January 2010
Improving Content Delivery and Service Discovery in Networks 24
TCP SYN packets and in-network termination
ProxyBrowser
End-user computerNetSerV router #1 NetSerV router #n
URL requestModified TCP SYN
Name resolution
Forwarded in direction of origin server
Modified TCP SYN
Has content
Sends TCP
SYN-ACK
TCP SYN-ACK
TCP ACK
TCP traffic
#C, #O, sp, 80#C, #O, sp, 80
+ URL
#C, #O, sp, 80
+ URL
#C, #N, sp, 80 + URL rewrite info
#C, #N, sp, 80
#C, #N, sp, 80
Add URL to TCP SYN
Modify #N to #O (incoming)
Modify #O to #N (outgoing)
#C = client IP
#O = origin server
#N = NetServ node
sp = source port Improving Content Delivery and Service Discovery in Networks 25
Screenshots : On-Path CDN Signaling
Proxy: adds host
payload to SYN
packet
On-Path CDN app:
Adds host/node info
to SYN-ACK packet
Browser set up
to use our proxy
server for its
network
connections.
Improving Content Delivery and Service Discovery in Networks 26
Delay Analysis – Round Trip Time (RTT)
0
100
200
300
400
500
600
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91 94 97 100
CNN CNN Akamai Lucent WWW London direct
CNN server Akamai server ALU edge node ALU in-network node
Measurements performing using traceroute / scapy / apachebench
Dela
y i
n m
illise
conds
Percentile of packets
Improving Content Delivery and Service Discovery in Networks 27
ActiveCDN: dynamic CDN deployment using NetServ
• Similar to on-path CDN: “pop up” CDN nodes along content path• On-path CDN is user-driven• ActiveCDN is publisher driven
• Dynamic content migration• Publisher driven: sends signal to routers
• Built on NetServ• Next-generation network virtualization platform• Built at IRT lab
• Working• Users request content from publisher’s server• Publisher sends content, along with signal to
NetServ nodes• NetServ nodes on path download ActiveCDN
module, install it and prime the content• When second user requests, ActiveCDN node
caches and displays content from its node
Improving Content Delivery and Service Discovery in Networks 28
Related Work
• Layer 4/7 switches [Web Switch, 2011], also known as web or content switches: similar functionality, used primarily for caching repeatedly requested content. • Need to keep track of every TCP connection that they are routing. Impractical in a
large network.
• TCP interception has been enabled by some router vendors (Cisco, Juniper)• Initially introduced to allow systems to reduce TCP SYN-flooding attacks• Has also been used for a variety of other purposes, such as speeding up content
delivery on wireless networks, such as with NetBouncer [Thomas et al., 2003]
• CoralCDN [Freedman et al., 2004]: content is served from P2P nodes that join and leave the network. • Request made for http://<website.com>.nyud.net• DNS requests resolved by a Coral DNS server, checks for HTTP proxies near client• User redirected to a Coral node near the user that contains the content.
Improving Content Delivery and Service Discovery in Networks 29
• Content Centric Networks: content is a first class citizen, not hosts• As opposed to IP networks, which relies on hosts (IP addresses, domain names)
• CCNs usually involve “clean slate” architectures
• i3 [Kannan et al., 2004], OCALA [Joseph et al., 2006] and Data-Oriented Network Architecture (DONA) [Koponen et al., 2007]• Naming overlays that work on top of the existing Internet architectures.
• Address the issue of Internet naming and name resolution by allowing a client to request content by name, rather than using a host address.
• Content-Centric Networking (CCN) [Jacobson et al., 2009b] aims at treating content as a primitive for routing requests to the destination.• Make a request for ccnx://content ; get result from network
Related Work: Content Centric Networks
Improving Content Delivery and Service Discovery in Networks 30
CCNxServ: Service layer on CCNx
• CCNx handles content
• But users need services in addition to content
• CCNxServ aims to extend CCNx to add a service layer on top of CCNx
• Service modules are packaged as CCNx content
• Requested as ccnx://content+service
• Suman Srinivasan, Amandeep Singh, Dhruva Batni, Jae WooLee, Henning Schulzrinne, Volker Hilt, Gerald Kunzmann,"CCNxServ: Dynamic Service Scalability in Information-CentricNetworks", IEEE ICC 2012, Ottawa, Canada, June 2012.
Improving Content Delivery and Service Discovery in Networks 31
Real World Video ConsumptionAnalysis done at JWPlayer
Improving Content Delivery and Service Discovery in Networks 32
Real World Video Consumption
• Worked at JWPlayer from 2011 to 2013• Internet video startup based on NYC• Raised $20M Series D in Jan 2016 / TechCrunch• Used by sites such as KickStarter, The Guardian,
Washington Post, etc• “Over half a billion videos are watched on JW Player
video player every day” – JW Player Blog, Dec 2015
• Presenting summary of findings in this presentation: more in the full dissertation
• Dataset when I was working at JWPlayer (2013) • Serving close to 5 billion streams monthly from
videos embedded in 2 million domains • Engagement data on 40 million streams (JW hosting)
Improving Content Delivery and Service Discovery in Networks 33
JWPlayer Analytics 1.0 Architecture
• Industry presentation• At HBaseCon 2013
• How we built a real-time analytics platform at JWPlayer using Hadoop and HBase• 16 billion events a month• 156 million unique viewers• 1 billion video streams• 30 million hours of video watched
• Presentation available on my SlideShare
Improving Content Delivery and Service Discovery in Networks 34
Distribution of Video Play by Top Countries
• Distribution for the top 100 videos (by stream count)• By country where viewer is located
• We look at the top 10 countries of viewership, for top 100 videos
• We want to find the popularity distribution of popular videos across country• Are videos universally popular
around the world?
Improving Content Delivery and Service Discovery in Networks 35
Distribution of Video Play by Top Countries
• Distribution of video play across top 10 countries of viewership
• Most videos are primarily popular in one country
• Top country accounts for 80% of viewership (in median)• Doesn’t account for language
regions
• Viral popularity of content: restricted to country?
Improving Content Delivery and Service Discovery in Networks 36
Distribution of Video Play by Top Regions
• OK, so video popularity distribution is heavily skewed towards one country
• But how about popularity distribution within a country?
• Is it similarly skewed? Or more evenly distributed?
• We look at distribution for the top 100 videos across regions / states for the #1 country for each video.
Improving Content Delivery and Service Discovery in Networks 37
Distribution of Video Play by Top Regions
• When we break down data a bit further by states / regions within top country
• Distribution is a bit more even.
• Between 25%-50% of the traffic is from the top region / state
• But a bit more evenly distributed across other regions / states
• So within a country: distribution is more evenly distributed across states / regions
Improving Content Delivery and Service Discovery in Networks 38
Other Analysis
• Video popularity• Popularity distribution based on time of day / week• Popularity distribution based on time of day / week by country
• Video length• Popularity based on length of video• Video length viewed across different countries, devices, bandwidth quality
• Popularity distribution across domains (Zip-f? Power law? Linear?)
• Usage across desktop, mobile and tablet devices
• State transitions in engagement data• How many people watch a video all the way to the end?• How many people keep skipping portions of the video?
Improving Content Delivery and Service Discovery in Networks 39
Related Work
• Gill et all [Gill et al., 2007] measured Youtube traffic at edge of a campus network• Network characterization and caching analysis of video traffic based on the Youtube
video popularity seen at the edge of the network. • Regional popularity similar to theirs. Ours is from the “center” as a provider gives us
greater insight into global traffic patterns across the world. • Our findings apply not only to one edge network, but are pretty similar to those seen
across the world
• [Adhikari et al., 2010] measures YouTube statistics at an ISP• The authors find that YouTube employs a location-agnostic, load-balanced method
for delivering video content. • Analyze the early-exit routing of YouTube traffic in ISP network, and find that
YouTube traffic has what they call a “locality bias” (videos showing popularity mostly within a region.)
Improving Content Delivery and Service Discovery in Networks 40
Conclusion
Improving Content Delivery and Service Discovery in Networks 41
Conclusions
• The Internet envisioned 40 years ago in the 1970s is vastly different from what its being used for today.• Rise of powerful handheld / mobile devices
• Consumption of large volumes of data, due to multimedia content
• Need solutions at three layers: networking, application, library
• My dissertation covered some possible solutions, as well as analysis• Opportunistic networks: 7DS, BonAHA
• Content delivery: On-path CDN, ActiveCDN
• Content centric networks: CCNxServ
• Real world video traffic patterns: performed while at JWPlayer
Improving Content Delivery and Service Discovery in Networks 42
List of peer-reviewed publications• Conferences
• Suman Srinivasan, Amandeep Singh, Dhruva Batni, Jae Woo Lee, Henning Schulzrinne, Volker Hilt, Gerald Kunzmann, "CCNxServ: Dynamic Service Scalability in Information-Centric Networks", IEEE ICC 2012, Ottawa, Canada, June 2012.
• Suman Srinivasan, Ivica Rimac, Volker Hilt, Moritz Steiner, Henning Schulzrinne, "Unveiling the content-centric features of TCP", IEEE ICC 2011, Kyoto, Japan, June 2011.
• Jae Woo Lee, Roberto Francescangeli, Jan Janak, Suman Srinivasan, Salman Abdul Baset, Henning Schulzrinne, Zoran Despotovic, Wolfgang Kellerer, "NetServ: Active Networking 2.0", IEEE ICC 2011, Kyoto, Japan, June 2011.
• Kiwoon Sung, Suman Srinivasan, Henning Schulzrinne, "BBS-ONE: Bulletin Board and Forum System for Mobile Opportunistic Networks", IEEE WCNIS 2010, Beijing, China, June 2010.
• Suman Srinivasan, Jae Woo Lee, Eric Liu, Mike Kester, Henning Schulzrinne, Volker Hilt, Srini Seetharaman, Ashiq Khan, "NetServ: Dynamically Deploying In-network Services", ACM ReArch'09 (CoNEXT workshop), December 2009.
• Se Gi Hong, Suman Srinivasan, Henning Schulzrinne, "Measurements of Multicast Service Discovery in a Campus Wireless Network", IEEE Globecom 2009, December 2009.
• Suman Srinivasan, Arezu Moghadam, Henning Schulzrinne, "BonAHA: Service Discovery Framework for Mobile Ad-Hoc Applications", IEEE Consumer Communications & Networking Conference 2009 (CCNC'09), Las Vegas, USA, January 2009.
• Arezu Moghadam, Suman Srinivasan, Henning Schulzrinne, "7DS - A Modular Platform to Develop Mobile Disruption-tolerant Applications", IEEE NGMAST 2008, Wales, UK, September 2008.
• Se Gi Hong, Suman Srinivasan, Henning Schulzrinne, "Accelerating Service Discovery in Ad-hoc Zero Configuration Networking", IEEE Conference on Global Communications (GLOBECOM), Washington D.C., Nov 2007.
• Suman Srinivasan, Arezu Moghadam, Se Gi Hong, Henning G Schulzrinne, "7DS - Node Cooperation and Information Exchange in Mostly Disconnected Networks", IEEE International Conference on Communications (ICC), Glasgow, Scotland, Jun 2007.
• Posters
• Suman Srinivasan, Henning Schulzrinne, "IPv6 Addresses as Content Names in Information-Centric Networking",USENIX ATC 2011 - Poster session, Portland, OR, Jun 2011.
• Suman Srinivasan, Dhruva Batni, Volker Hilt, Henning Schulzrinne, "Dynamic Service Scalability in Information-Centric Networks", USENIX ATC 2011 - Poster session, Portland, OR, Jun 2011.
• Suman Srinivasan, Henning Schulzrinne, "BonSwing: A GUI Framework for Ad-Hoc Applications Using Service Discovery", ACM CoNEXT Student Workshop, New York, Dec 2007.
• Patents
• Volker Hilt, Ivica Rimac, Suman Srinivasan, Moritz Steiner, "Method For Providing On-Path Content Distribution", January 2010
• Henning Schulzrinne, Suman Srinivasan, "Methods And Media For Exchanging Data Between Nodes Of Disconnected Networks", 2008
Improving Content Delivery and Service Discovery in Networks 43
Backup Slides
Improving Content Delivery and Service Discovery in Networks 44
7DS: Check with Peers
Internet
No Internet connection: Check with peers
Improving Content Delivery and Service Discovery in Networks 45
7DS, BonAHA: Technical details
Columbia?
SRV : query._7ds._udp
TXT : columbia
TXT : news
TXT : new york
Times Square?
SRV : query._7ds._udp
TXT : deals
TXT : times square
TXT : weather
“Here is the result for times square”“Here is the result for
columbia”
Improving Content Delivery and Service Discovery in Networks 46
7DS Architecture
Web user
interface
Transport
Agent
Bulletin
Board
Multicast
Website
Exchange
Web
server
Proxy
server
CachingLogging Configuration
Data
structures
Service
discovery
File
synchronization
Components
Support
services
APIs
Searching
DatabaseXML Parsing
Improving Content Delivery and Service Discovery in Networks 47
7DS Search Engine
• Provides ability to query self for results
• Searches the cache index using Swish-e library
• Presents results in any of three formats: HTML, XML and plain text
• Similar in concept to Google Desktop
Improving Content Delivery and Service Discovery in Networks 48
BonAHA Applications
Group chat• Allows users to discover peers in
local network and chat• Rooms can be set up for private
chats
File Sharing• Users can share files with each
other by dragging and dropping files onto peers’ computers
• Handles peers entering and leaving network
Improving Content Delivery and Service Discovery in Networks 49
CDN HTTP redirection: Youtube Callflows
Original HTTP
request for video
HTTP 301 redirect
to Google Video
server (CDN)
HTTP 301 redirect
to IP address
Improving Content Delivery and Service Discovery in Networks 50
On-path CDN: TCP SYN packets
ProxyBrowser
End-user computerNetSerV router #1 NetSerV router #n
URL requestModified TCP SYN
Name resolution
Forwarded in direction of origin server
Modified TCP SYN
Has content
Sends TCP
SYN-ACK
TCP SYN-ACK
TCP ACK
TCP traffic
Improving Content Delivery and Service Discovery in Networks 51
On-path CDN: Packet trace using Wireshark
Modified SYN packet sent
out successfully
Successful HTTP connection set up
Improving Content Delivery and Service Discovery in Networks 52
On-path CDN: Performance Analysis SetupHow do we know what impact on-path CDNs have?
• Can it reduce delays?
Did a simple RTT analysis
Measurement of round-trip time delays
• CNN server
• Akamai media server
• ALU edge server
• ALU internal node
Traceroute graph generated using Python Scapy’s
traceroute tools
Other ALU nodes
CNN server Akamai server
ALU edge node
ALU in-network node
Improving Content Delivery and Service Discovery in Networks 53
NetServ overview
• Modularization• Building Blocks
• Service Modules
• Virtual services framework• Security, Portability
• NSF FIND four-year project• Columbia University
• Bell Labs
• Deutsche Telekom, DoCoMo Europe
Extensible architecture for core network services
No more ossification in NGIImproving Content Delivery and Service Discovery in Networks 54
ActiveCDN: GENI demo
• NetServ was chosen as one of nine nationwide research projects for NSF GENI testbed
• Demo’d at NSF GENI 2010
• User 1 requests content, gets it directly from server• Meanwhile publisher sends
notification to NetServ node to install module
• User 2 requests content, gets the processed content (with watermark) from NetServ node
Improving Content Delivery and Service Discovery in Networks 55
Content Centric Networking (CCNx)
• Described briefly in related work for CDNs
• Based on Van Jacobson’s (Xerox PARC) work on CCNs• “Can we create a network architecture based
on named data instead of named hosts?”
• Content, instead of URLs• Allows for content mobility, caching, etc.
• Client makes a request for ccnx://content , gets the data without worrying about which node it is on
Improving Content Delivery and Service Discovery in Networks 56
CCNxServ: Architecture
1. Application requests a service on some content
2. CCNxServ converts request into request for content and service module
3. Fetches content and module, and runs the service module to content
4. Puts serviced / processed content back into CCNx space for future requests
Improving Content Delivery and Service Discovery in Networks 57
CCN over IPv6
• CCNx requires a complete modification of underlying network: no more IP
• Rather than modify complete underlying IP network: why not re-use existing IPv6 network?
• IPv6 can hold 2^128 addresses: carve up address space to handle domains, URLs and content requests
• Suman Srinivasan, Henning Schulzrinne, "IPv6 Addresses as Content Names in Information-CentricNetworking", USENIX ATC 2011 - Poster session, Portland, OR, Jun 2011.
Improving Content Delivery and Service Discovery in Networks 58
Related Work
• SCAFFOLD [Freedman et al., 2010]: multiple service instances represented by one common name• Specific service represented through serviceIDs and selected through anycast routing through service routers.
• MILNGENI (million-node GENI) [University of Washington, 2011]: services can be deployed and run on top of many end-systems that are connected via the experimental GENI testbed. • Attempt to deal with the problem of addressing content and making content requests efficient, but operate
on top of the IP layer and require host-to-host communication.
• Service-centric networking (SCN) [Braun et al., 2011]: build a network that runs with services as the primary construct, rather than content. • Superset of CCNx: modification of underlying CCNx implementation.• CCNxServ: builds a service platform on top of only CCNx, implements a fully service-oriented networking
architecture on top of a pure ICN stack.
• SoCCeR [Shanbhag et al., 2011]: build a service layer on top of CCNx. • Control layer to manipulate the underlying routing layer in CCNx, thereby performing distributed best-service
selection using an ant colony optimization approach.
Improving Content Delivery and Service Discovery in Networks 59
• Data movement towards services• Volley [Agarwal et al., 2010]: automate application data placement across data
centers efficiently. • PADS [Belaramani et al., 2009]: a data plane mechanism for transmitting data and
maintaining consistency in large distributed applications and data centers. • Time-shifted TV [Li and Simon, 2011] uses CCNx to improve localized and cooperative
caching using content routers.
• Separation of ID and content name• [Atkinson et al., 2010] and [Dannewitz et al., 2010] aim to preserve privacy of
content names in the network. Almost all of these would require some sort of credential validation to be done on the network.
• LISP (Location/ID Separation Protocol) [Farinacci, 2013] and [IETF, ] is an IETF proposal that deals with a naming system that would configure host-names and machine network address identifiers and map them to locators.
Related Work
Improving Content Delivery and Service Discovery in Networks 60
• Yu et al [Yu et al., 2006] study weekly access patterns of usage and infer arrival rates of video viewers as well as metrics such as session length, popularity and popularity distribution of popular content. • Done at the content provider. Similar to ours for most metrics such as weekly access
patterns, popularity distribution, etc, with the only difference being in total number of data points.
• Their study was done in early 2006, and ours is more current (2012) and at a time when Internet video is more mature.
• Due to video engagement data, in addition to raw video loads, we are able to measure much more interesting trends such as user engagement (such as transition between play, stop, seek and progress states), which gives us more insight into the interplay between the viewer, the provider and the network.
• Costa et al [Costa et al., 2004] study usage patterns of video viewership. • Data is several years old (2004).
Related Work
Improving Content Delivery and Service Discovery in Networks 61
JWPlayer Video: Play by Hour by Country
• Video plays across country of viewing by hour of day
• Traffic patterns are very similar across countries• Video consumption dips
significantly during wee hours of the morning (esp. 4-5 AM)
• Picks up during waking hours, stays steady for most of the day
• Goes up slightly during night time, particularly before / after dinner?
Improving Content Delivery and Service Discovery in Networks 62