This talk is about “how we can exploit social information in content distribution systems”
description
Transcript of This talk is about “how we can exploit social information in content distribution systems”
![Page 1: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/1.jpg)
Content Distribution based on Social Information
Rubén Cuevas, Eva Jaho, Carmen Guerrero and Ioannis StavrakakisUniversity Carlos III Madrid
National Kapodistrian University of Athens
Paris, 16th October 2008
![Page 2: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/2.jpg)
This talk is about “how we can exploit social information in content distribution
systems”
![Page 3: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/3.jpg)
Outline
Introduction SwarmTella OnMove Conclusions
![Page 4: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/4.jpg)
Introduction
![Page 5: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/5.jpg)
Does this really make sense? Success of Content Distribution Systems
P2P (Emule, BitTorrent), APLICATION LAYER MULTICAST, UGC Applications (YouTube)
Success of Social Applications Instant Messaging (MSN) Social Networks (FaceBook, LinkedIn,…)
People would use their social application for Content Distribution? Yes This makes sense No Give it up
![Page 6: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/6.jpg)
How can we use social information in Content Distribution?
Identifying those users with similar social features General
Similar profession Similar hobbies Similar interests ….
Wireless Environments Similar Mobility Pattern
And exchange contents with them
![Page 7: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/7.jpg)
Which benefits can we obtain?
Accuracy People Satisfaction Targeted Content Advertisement Retrieve contents that really fit my social
profile
Cooperation People collaborate if they get benefit from the
system
Resource Saving Avoiding flooding Avoiding downloading not desired contents
![Page 8: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/8.jpg)
Our contribution
We will present two systems that exploit Social Information in Content Distribution
SWARMTELLA (UC3M) “Exploiting Social Information in P2P Content
Distribution”
ONMOVE (UC3M and NKUA) “Exploiting Social Information for Content
Distribution in Wireless Delay Tolerant Environments”
![Page 9: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/9.jpg)
SwarmTella
![Page 10: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/10.jpg)
SwarmTella General framework for distribution of
different type of content (file-sharing, VoD Distribution and Live Streaming)
Community scenarios It can be intended as a Recomendation
System Delivery techniques based on swarming Nodes initially organized in an
unstructured p2p Distributed mechanism for building
communities based on users common interests on contents: Ranking Algorithm
![Page 11: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/11.jpg)
Ranking Algorithm
RA allows each node to identify other nodes with similar interest in a transparent way to the end user.
Each node generate a ranking of the other nodes.
Nodes with higher ranking means that have common interests to the local node.
It uses local information (light) Received search queries Swarm’s peers discovery
![Page 12: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/12.jpg)
SPPiD Secure Permanent Peer-ID (SPPiD)
The public part of a Public/Private key pair.
Transparent to the end user, generated and just used by the application
This allows to keep connection with other nodes along different sessions
Long term robust structure of the communities, long life of the IDs.
Privacity Concerns Not Secure Permanent ID KAD User Ids Skype Mail Accounts MSN, FaceBook
![Page 13: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/13.jpg)
Swarmtella Publication Mechanism
.swarmtella file with metadata of the available content.
The node with a new content generates the .swarmetella file and an ADVERTISEMENT message to be sent to the a limited number of nodes (highest ranked) in the community.
![Page 14: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/14.jpg)
Swarmtella Searching Mechanism
Multiattribute semantic query to the highest ranked nodes in the community
If it fails, then flooding algorithm in unstructured p2p (gnutella like)
![Page 15: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/15.jpg)
BW consumed
![Page 16: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/16.jpg)
Query Hit Rate
![Page 17: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/17.jpg)
Top peers and community members
content
![Page 18: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/18.jpg)
SwarmTella
Next steps: Design Details (e.g. Swarm Partition) Real workload
Pattern of Encounters in Swarms Uptime Pattern of P2P nodes Plan Crawling BT Swarms
TUDarmstadt and UC3M
Swarmtella Implementation Validation in Controlled Environment
Emulab, ModelNet
![Page 19: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/19.jpg)
OnMove
![Page 20: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/20.jpg)
A novel protocol for content distribution in wireless delay-tolerant environments
It is designed for handheld devices mobile phones, PDAs, etc…
Multiple uses: Advertisement Platform UGC Distribution Entertainment On the Road
OnMove
![Page 21: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/21.jpg)
DTN Scenario
Individual A may come in contact with individuals B, C and D in the morning for a duration of time t1.
Then she goes to the cinema and connects with other individuals for a duration of time t2.
In the evening she goes to the concert and meets other people for a duration of time t3.
t2
cinema
A B
GH
L
t3
concertA G
KMN
O
t1
university
C
B
D
A
![Page 22: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/22.jpg)
DTN Scenario (cntd.)
A retrieves contents from B,C,D at the university
A stores them
A forwards the stored contents to B,G,H,L at the cinema
A forwards the stored contents to G,K,M,N,O at the concert
t2
cinema
A B
GH
L
t3
concertA G
KMN
O
t1
university
C
B
D
A
![Page 23: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/23.jpg)
Social networks can be either studied as:
whole networks with all of the ties describing relations in a defined population, or as
egocentric networks describing the ties that one or more specific individuals have
OnMove is designed by considering egocentric or personal networks for each individual.
Social networking design of OnMove
![Page 24: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/24.jpg)
Egocentric networks involve a focal individual (ego) and the individuals (alters) to which it is linked.
We study the exchange of data of the surrounding individual with the others in the group based on social interests.
Objectives: To increase speed of content dissemination To improve accuracy of content dissemination (align content
dissemination with users’ interests)
Egocentric Networks
iegocentric network of individual i
![Page 25: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/25.jpg)
Content Exchange Procedure
When an individual comes in contact with other individuals in a social group (locality) She exchanges its social profile with the others. She has to decide from/to which node it is going to
download/upload contents.
The individual ranks the others individuals in the locality Download/Upload from/to highest ranked individual The ranking algorithm is the core of the content exchange
procedure, and should aim at increasing its effectiveness
C
B
D
AA
![Page 26: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/26.jpg)
Ranking parameters in OnMove
Social Similarity (SS): Similarity of social details (profession, interests, hobbies) of individuals
Content Accuracy (CA): Alignment of contents received by an individual from other individuals to his/her interests
Pattern of Meetings (PM): Defined by the frequency and the duration of these encounters
Connection Quality (CQ): Available bandwidth, interferences, type of connection (e.g., WiFi, Bluetooth)
![Page 27: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/27.jpg)
Ranking parameters in OnMove (cntd.)
Egocentric Betweenness Bi of individual i: Number of pairs of neighbors of i that are not directly connected to each other. Individuals with high value of egocentric betweenness have a lot
of influence in the network as a lot of other individuals depend on them to make connections with other people.
Average Egocentric Betweenness (B*):
t1
t2
t3
A
DC
B
H
LG
K
M
N
O
T
tii tB
TB
1
* )(1
![Page 28: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/28.jpg)
Ranking neighbours in OnMove
Ranking metric for each individual: A weighted average of the previous parameters
Weights for each parameter are assigned differently in different application scenarios
**
)(
iBiCA
iCQiPMiSS
BwCAw
CQwPMwSSwiRank
![Page 29: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/29.jpg)
Application scenarios
Advertisement Platform Objective: Maximize the dissemination of the
advertised content (photo, video, etc.) Relevant Parameters: B*, SS
File-Sharing on the Road: Objective: Find contents of interest to a node Relevant Parameters: SS, PM, CQ, CA
![Page 30: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/30.jpg)
OnMove
Next steps: Configuration and optimization of the ranking
algorithm mechanism in several application scenarios.
Analyzing social profiles available on current systems such as FaceBook and exporting them to OnMove.
Evaluate OnMove in a real testbed. Crawdad data (e.g. Haggle Project)
Analysis of OnMove in multihop networks
![Page 31: This talk is about “how we can exploit social information in content distribution systems”](https://reader036.fdocuments.in/reader036/viewer/2022062519/5681502f550346895dbe2777/html5/thumbnails/31.jpg)
Content Distribution based on Social Swarms
Rubén Cuevas, Eva Jaho, Rubén Cuevas, Eva Jaho, Carmen Guerrero and Ioannis StavrakakisUniversity Carlos III Madrid
National Kapodistrian University Athens
Paris, 16th October 2008