I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Characterizing residential broadband networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
FlyByNight: mitigating the privacy risks of social networking
Proceedings of the 7th ACM workshop on Privacy in the electronic society
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
PeerSoN: P2P social networking: early experiences and insights
Proceedings of the Second ACM EuroSys Workshop on Social Network Systems
Privacy, cost, and availability tradeoffs in decentralized OSNs
Proceedings of the 2nd ACM workshop on Online social networks
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
A privacy-preserving scheme for online social networks with efficient revocation
INFOCOM'10 Proceedings of the 29th conference on Information communications
Content and geographical locality in user-generated content sharing systems
Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video
Building confederated web-based services with Priv.io
Proceedings of the first ACM conference on Online social networks
The Scope for online social network aided caching in web CDNs
ANCS '13 Proceedings of the ninth ACM/IEEE symposium on Architectures for networking and communications systems
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Today, OSN sites allow users to share data using a centrally controlled web infrastructure. However, if users shared data directly from home, they could potentially retain full control over the data (i.e., what to share, whom to share with). This paper investigates the feasibility of alternative decentralized architectures that allow users to share their data directly from home. Specifically, we (a) characterize social content workloads using data gathered from the popular Flickr and YouTube social networks and (b) characterize home networks using data gathered from residential gateways deployed in a number of households. We use the data from these measurements to evaluate the potential for delivering social content directly from users' homes.