Prometheus: User-Controlled P2P Social Data Management for Socially-aware Applications Nicolas Kourtellis, Joshua Finnis, Paul Anderson, Jeremy Blackburn, Cristian Borcea * , Adriana Iamnitchi Department of Computer Science and Engineering, USF * Department of Computer Science, NJIT ACM/IFIP/USENIX 11 th International Middleware Conference, 2010
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Prometheus: User-Controlled P2P Social Data Management for Socially-aware Applications
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Prometheus: User-Controlled P2PSocial Data Management
for Socially-aware Applications
Nicolas Kourtellis, Joshua Finnis,Paul Anderson, Jeremy Blackburn,Cristian Borcea*, Adriana Iamnitchi
Department of Computer Science and Engineering, USF*Department of Computer Science, NJIT
ACM/IFIP/USENIX 11th International Middleware Conference, 2010
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Social and Socially-aware Applications
Applications may contain user profiles, social networks, history of social interactions, location, collocation
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Problems with Current Social Information Management Application specific:
Need to input data for each new application Cannot benefit from information
aggregation across applications Typically, data are owned by applications:
users don't have control over their data Hidden incentives to have many "friends":
social information not accurate
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Our Solution: Prometheus P2P social data management service:
Receives data from social sensors that collect application-specific social information
Represents social data as decentralized social graph Exposes API to share social information with
applications according to user access control policies
SOCIAL SENSORS
SOCIALLY-AWARE APPS
CallCensor
Foursquare`
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PROMETHEUS
Loopt
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Outline
Motivation Social Graph Management API and Access Control Prototype Implementation Evaluation over PlanetLab Summary Future Work
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How is the Social Graph Populated? Social sensors report edge information to
Prometheus:<ego, alter, activity, weight>
Applications installed by user on personal devices Aggregate & analyze history of user's interactions with
other users Two types of social ties:
Object-centric: use of similar resources Examples: tagging communities on Delicious,
repeatedly being parts of the same BitTorrent swarms People-centric: pair-wise or group relationships
Examples: friends on Facebook, same company name on LinkedIn, collocation from mobile phones
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Social Graph Representation Multi-edged, directed, weighted, labeled graph
Each edge → a reported social activity Weight → interaction intensity Directionality reflects reality
Allows for fine-grain privacy Prevents social data manipulation
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Decentralized Graph Storage Each user has a set of trusted peers in the P2P network
Peers it owns & peers owned by trusted users Each user’s sub-graph stored on all its trusted peers
Improved availability in face of P2P churn P2P multicast used to synchronize information among