SocialCDN: Caching techniques for distributed social networks

Han, Lu; Punceva, Magdalena; Nath, Badri; Muthukrishnan, S.; Iftode, Liviu

doi:10.1109/p2p.2012.6335799

Cited by 19 publications

(5 citation statements)

References 14 publications

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“…Decentralized social online networks (DSONs) like Safebook , Peerson , My3 , Gemstone , and SODESSON , and the information distribution networks that support them such as the Social CDN also put major importance on sharing of data and while leveraging social relationships for trust and security.…”

Section: Related Workmentioning

confidence: 99%

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A social content delivery network for e‐Science

Chard

Caton

Kugler

et al. 2016

Concurrency and Computation

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Summary We are in the midst of a scientific data explosion in which the rate of data growth is rapidly increasing. While large‐scale research projects have developed sophisticated data distribution networks to share their data with researchers globally, there is no such support for the many millions of research projects generating data of interest to much smaller audiences (as exemplified by the long tail scientist). In data‐oriented research, every aspect of the research process is influenced by data access. However, sharing and accessing data efficiently as well as lowering access barriers are difficult. In the absence of dedicated large‐scale storage, many have noted that there is an enormous storage capacity available via connected peers, none more so than the storage resources of many research groups. With widespread usage of the content delivery network model for disseminating web content, we believe a similar model can be applied to distributing, sharing, and accessing long tail research data in an e‐Science context. We describe the vision and architecture of a social content delivery network – a model that leverages the social networks of researchers to automatically share and replicate data on peers' resources based upon shared interests and trust. Using this model, we describe a simulator and investigate how aspects such as user activity, geographic distribution, trust, and replica selection algorithms affect data access and storage performance. From these results, we show that socially informed replication strategies are comparable with more general strategies in terms of availability and outperform them in terms of spatial efficiency. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Related Workmentioning

confidence: 99%

“…The S‐CDN consists of social caches that enable data distribution between friends using a variety of socially aware distribution algorithms. Like our S‐CDN, the Social CDN uses social networks to form the CDN.…”

Section: Related Workmentioning

confidence: 99%

A social content delivery network for e‐Science

Chard

Caton

Kugler

et al. 2016

Concurrency and Computation

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“…SocialCDN [16] builds a collaborative cache that exploits explicit social acquaintances to aggregate peers for content distribution. This makes its approach limited to the case of distributed Online Social Networks.…”

Section: Related Workmentioning

confidence: 99%

Behave: Behavioral Cache for Web Content

Frey

Goessens

Kermarrec

2014

Distributed Applications and Interoperable Systems

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We propose Behave: a novel approach for peer-to-peer cache-oriented applications such as CDNs. Behave relies on the principle of Behavioral Locality inspired from collaborative filtering. Users that have visited similar websites in the past will have local caches that provide interesting content for one another.Behave exploits epidemic protocols to build overlapping communities of peers with similar interests. Peers in the same one-hop community federate their cache indexes in a Behavioral cache. Extensive simulations on a real data trace show that Behave can provide zero-hop lookup latency for about 50% of the content available in a DHT-based CDN.

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“…This change will bring a far-reaching impact on traditional industries of content, media, and communications. In this context, the rapid proliferation of OSNs sites is expected to reshape CDN's structure and design [37]. Investigating the geographical, structural, and temporal properties of social cascades, new CDN infrastructures will be built where cache replacement strategies will exploit these properties.…”

Section: Semantic Annotationmentioning

confidence: 99%