Can Peer-to-Peer File-sharing be of Help for Research Communities ?

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Can Peer-to-Peer File-sharing be of Help for
Research Communities ?

• Julita Vassileva
• Computer Science Department (MADMUC Lab)
• University of Saskatchewan

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Outline

• Motivation
• Problems user participation, trust
• Motivating user participation
• User modelling
• Reward with better QofS
• Social awareness (visualization)
• Ensuring trust
• Conclusions

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Motivation

• Need a search engine for locally stored papers
• Web links disappear, protected sites
• Hard disks too large
• Why P2P?
• Harvest the resources of a community of users
• Advantages of a distributed approach vs
  centralized

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What is a P2P System?
GNUTELLA
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COMTELLA

• A P2P (Gnutella based) system for file sharing
  and service
• users share academic papers, code snippets
• Non-centralized digital library for a research
  group / class
• Can be downloaded from
• http//bistrica.usask.ca/madmuc/news.htm

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Vassileva J. (2002) Supporting Peer-to-Peer User
Communities, in R. Meersman, Z. Tari et al.
(Eds.) "On the Move to Meaningful Internet
Systems 2002 CoopIS, DOA, and ODBASE"
Coordinated International Conferences
Proceedings, Irvine, Springer LNCS 2519,
230-247. Vassileva, J. (2002) Motivating
Participation in Peer to Peer Communities,in
P.Peta, R.Tolksdorf, F. Zambonelli (Eds.)
Engineering Societies in theAgents World III,
Proceedings of the 3rd International Workshop
ESAW'02,Madrid, Springer LNAI 2577,
141-155. Bretzke H., Vassileva J. (2003)
Motivating Cooperation in Peer to Peer Networks,
in P.Brusilovsky, A. Corbett, F.De Rosis (eds.)
Proceedings of the 9th International Conference,
on User Modelling, UM03, Johnstown, PA,Springer
LNCS, 218-227.
Lingling Sun Graduate student
Christopher Cox NSERC Summer 2002 project
Helen Bretzke CRA-W and NSERC Summer 2002
project
Yamini Upadrashta Graduate student
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Problems

• User Participation
• critical mass needed
• most users are free-riders
• why do people contribute?
• satisfies a need (is useful)
• doesnt cost (effort, money, inconvenience)
• there is some incentive (money, glory, power)
• serves a greater cause (e.g. cancer research,
  SETI_at_home, etc.)

• Trust
• sure that contributing wont cause harm
• able to identify trustworthy peers

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First condition system must be useful

• Allow searching own files
• Any file stored on disk can be found with
  Comtella
• Shared files can be stored anywhere on disk
• Integration with other tools
• With Browser (e.g. IE, Netscape, Mozilla, etc.)
• allows viewing files directly from Comtella
• prompts the user to share papers when a PDF file
  opened
• With Word Processor (e.g. MS Word)
• generating lists of references automatically
• Additional functionality
• Adding annotations and ratings to papers

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Levels of participation

• Bring new files
• Provide disk space / processor time
• Dispatch requests
• Stay on-line
• Use and quit

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How to motivate participation?

• Why do people offer their time and resources?
• Different people have different motivations

• Some are altruists

• Some would help their friends and hope to make
  new friends through helping

• Some seek glory

• Some would expect better service

• Some seek high marks

• or money

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Incentives

• Micro-payments for each transaction?

Shirky says it wont ever work (e.g.
Mojo-nation) Flat rates work better (e.g.
Internet, cable) How to map virtual currency
into real money?
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How to motivate participation?

• Why do people offer their time and resources?
• Different people have different motivations

• Some are altruists (for the cause)

• Some would help their friends and hope to make
  new friends through helping

• Some seek glory

• Some would expect better service

• Some seek high marks

• or money

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Know your user!
Modelling

• User Type Altruist? Socialist? Utilitarian?
• User Interests What does she search / need?
• User Relationships and Community Who shares
  interest with the user? Potential friends and
  foes.

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Modelling user interests

• Define a taxonomy of subject categories (e.g. ACM
  subject index)
• Keep track of the categories of queries (? user
  interests)
• Keep track of resources offered by the user in
  each interest category
• Update user level of interest in each
  sub-category using reinforcement learning
• Cluster users in interest-based groups

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Computing user interests

• Reinforcement learning
• The users strength of interest S in an area a is
  calculated based on how frequently and how
  recently the user has searched in this area.
• Sa(et, t) i Sa(e t-1, t-1) (1 - i)
  et
• where et Î 0, 1 is calculated as et 1/ d, and
• d 1 level_distance between the level of the
  sub-area of the query and the level of the area a
  in the ontology hierarchy. Currently, the
  ontology hierarchy has only 2 levels, so et 0.5

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Modelling user relationships

• Monitor whose files the user chooses, the quality
  of the files (does the user keep the files), and
  who downloads files offered by the user
• Represent each user relationship
• For each area of interest
• Strength how successful service was given
  (reinforcement learning used, similar to user
  interests)
• Balance reciprocity of services used/ given
• Adapt P2P topology form a neighborhood for
  search using the best relationships (friends)
  in the area of search

Gnutella
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Computing the balance of a relationship

• BXY (N X?Y - N Y?X ) / (N X?Y N Y?X )
• BXY Î -1, 1
• N X?Y - number of times X took from Y
• N Y?X - number of times Y took from X

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Modelling user type

• Monitor users actions regarding file sharing,
  relative time spent on-line, acts of interrupting
  service, total balance of users giving / taking
• Update a number in -1, 1 representing users
  cooperativeness
• Motivational actions in the interface triggered
  by passing certain thresholds

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Computing user type

• The measure of user cooperativeness at time t
  C(wt, t) i C(w t-1, t-1) (1 - i) wt,
• w ? -1,0) ? (0,1 represent the weight of
  evidence, where w lt 0 is a selfish act while w gt
  0 is an altruistic act.
• overallBalance (1/n)SY (BXY)
• userType (C(wt, t) overallBalance) /2
• If userType is in -1, -0.5) then user is
  selfish, if it is in -0.5) ? ( 0.5 then user is
  reciprocal, and if it is in (0.5, 1 then user is
  altruistic.

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Rewarding relationships

• People who share a lot of useful files and behave
  cooperatively will have more friends
• Friends are treated differently
• Transfers not interrupted
• Queries processed with priority
• Queries are propagated farther
• Queries sent to friends in the area
• Higher chance of having relevant files
• Faster responses
• Better quality of files
• People with more friends get better Quality of
  Service!

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Evaluation results - simulation

• Comparing the round trip time obtained for
  queries without a friends list with
  the round trip time for queries with friends
  list

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Evaluation results user experiment
8 users over a week
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Summary of results

• The simulation results show that peers obtain
  results faster when searching for files in
  categories for which they have friends
• The user evaluation still underway
• Does the QoS reward motivate participation?

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Social awareness
In isolation, selfishness is logical
To gain perspective, users needfeedback about
their social environment
In cities, the sidewalks provide the right kinds
and numbers of interactions from which
neighborhoods emerge.
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A matter of scale

• Provides visual feedback
• Resolves scale
• Attractive interesting

An astronomical metaphor
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Views of the community

• Connectivity (currently reachable peers)
• Ranking of peers by contribution
• number of shared files
• balance of relationships
• Papers shared by each peer
• Interests of each peer

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Architecture
Introducing a non-vital server or many servers
Server

• Collect info. from peers
• Generate community views

Server
Server
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Ranking of peers based on contribution
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Shared interests
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Personalized views

• Who are my friends in this area?
• How strong is my relationship with them?
• How much have they contributed?
• Do I owe them or do they owe me?
• Which files do they share?
• What have they been searching for / downloading
  recently?

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Trust

• We already model the strength of relationships
  between users
• Based on counting downloads /uploads
• We can incorporate an explicit measure of the
  quality of resource
• Idea Let users
• Rate their resources (quality of paper)
• Add annotations (summaries) of papers

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Immediate benefit

• Learning effect compiling reviews of articles
• Visualization of document ranking in given
  category of interest top 10 list
• Professor / Boss will know who has read and
  annotated paper and who has not ? could have a
  motivation effect on participation.

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Reputation

• Global reputation of peers can be computed
• Ranking of peers based on
• how many highly rated papers they share
• how many times they have introduced a new paper
  in the system that has become highly rated
• how the users ratings correlate with those of
  their peers and with high-rank peers
• Emergence of Power peers
• What extra rights will they have (reward)?
• Could have a motivational effect, as in
  Slashdot.com

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Community views

• Connectivity (currently reachable peers)
• What are these peers interested in / sharing
• Ranking of peers by contribution
• Shared interest clusters
• Personalized views (who are my friends?)
• Ranking of resources (papers)
• Reputation of peers

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Updating trust in peers

• Relationships ? subjective trust in the source of
  the paper (the other peer)
• Trust depends on the evaluation criteria of the
  peer
• Compare own rating of paper with the rating given
  by the source
• If ratings are sufficiently close,
  increase trust in source, else decrease trust
• Trust depends on category of interest
• Combined trust measures for peers?
• Peers share their trust measures (gossip)

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Trust and reputation

• Yao Wang
• Ph.D. student
• Wang Y., Vassileva J. (to appear) Bayesian
  Network-Based Trust Model, Proc. of IEEE/ WIC
  International Conference on Web Intelligence (WI
  2003), October 13-17, 2003, Halifax, Canada.
• (best paper award nominee)

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Applying a Bayesian network trust model to
COMTELLA
T
File quality
Paper category (subject area)
Reliability (download)
Paper rating
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Future work

• Incorporating a trust reputation mechanism into
  Comtella
• to protect from malicious file-sharers
• to ensure that users share papers with
  appropriate peers and benefit most from their
  articles and comments

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take-home messages

• Motivating user participation is crucial
• Building in mechanisms for trust and reputation

• Encouraging contribution
• building relationships
• Rewards by better quality of service
• reputation / visibility
• Techniques
• Modeling user interests, relationships, user
  type
• Creating community awareness through
  visualization

• Will allow users to find reputable sources
• May protect community from malicious or
  irresponsible peers