Enabling social applications via decentralized social data management

Nicolas Kourtellis; Jeremy Blackburn; Cristian Borcea; Adriana Iamnitchi

doi:10.1145/2700057

Enabling social applications via decentralized social data management

Nicolas Kourtellis, Jeremy Blackburn, Cristian Borcea, Adriana Iamnitchi

Computer Science

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

An unprecedented information wealth produced by online social networks, further augmented by location/collocation data, is currently fragmented across different proprietary services. Combined, it can accurately represent the social world and enable novel socially aware applications. We present Prometheus, a socially aware peer-to-peer service that collects social information from multiple sources into a multigraph managed in a decentralized fashion on user-contributed nodes, and exposes it through an interface implementing nontrivial social inferences while complying with user-defined access policies. Simulations and experiments on PlanetLab with emulated application workloads show the system exhibits good end-to-end response time, low communication overhead, and resilience to malicious attacks.

Original language	English (US)
Article number	1
Journal	ACM Transactions on Internet Technology
Volume	15
Issue number	1
DOIs	https://doi.org/10.1145/2700057
State	Published - Feb 1 2015

All Science Journal Classification (ASJC) codes

Computer Networks and Communications

Keywords

Decentralized social graph
Distributed systems
P2P networks
Social inferences
Social sensors
Socially aware data management

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10.1145/2700057

Cite this

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AB - An unprecedented information wealth produced by online social networks, further augmented by location/collocation data, is currently fragmented across different proprietary services. Combined, it can accurately represent the social world and enable novel socially aware applications. We present Prometheus, a socially aware peer-to-peer service that collects social information from multiple sources into a multigraph managed in a decentralized fashion on user-contributed nodes, and exposes it through an interface implementing nontrivial social inferences while complying with user-defined access policies. Simulations and experiments on PlanetLab with emulated application workloads show the system exhibits good end-to-end response time, low communication overhead, and resilience to malicious attacks.

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Enabling social applications via decentralized social data management

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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