NDLI: Minimizing inter-server communications by exploiting self-similarity in online social networks

Content Provider	IEEE Xplore Digital Library
Author	Hanhua Chen Hai Jin Ning Jin Tao Gu
Copyright Year	2012
Description	Author affiliation: Department of Mathematics and Computer Science, University of Southern Denmark, 5230 Odense M, Denmark (Ning Jin; Tao Gu) \|\| Services Computing Technology and System Laboratory, Cluster and Grid Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China (Hanhua Chen; Hai Jin)
Abstract	Efficiently operating on relevant data for users in large-scale online social network (OSN) systems is a challenging problem. Storage systems used by popular OSN systems often rely on key-value stores, where randomly partitioning the data of users among servers across the data centers is the defacto standard. Although by using DHTs, the random partition scheme is highly scalable for hosting a large number of users, it leads to costly inter-server communications across data centers due to the complexity of interconnection and interaction between OSN users. In this paper, we explore how to reduce the inter-server communications by retaining the simple and robust nature of OSNs. We propose a data placement solution atop OSN systems to divide users among servers according to the interaction-locality-based structure. Our approach exploits a simple, yet powerful principle of OSN interactions, self-similarity, which reveals that the inter-server communication cost is minimized under such intrinsic structure. Our algorithm avoids a significant amount of inter-server traffic as well as achieves load balance among servers across the data centers. We demonstrate the existence of self-similarity in large-scale Facebook traces including 10 million Facebook users and 24 million interaction events. We conduct comprehensive trace-driven simulations to evaluate this design exploiting the unique feature of self-similarity. Results show that our scheme significantly reduces the traffic and latency of the existing schemes.
Starting Page	1
Ending Page	10
File Size	239754
Page Count	10
File Format	PDF
ISBN	9781467324458
e-ISBN	9781467324472
e-ISBN	9781467324465
DOI	10.1109/ICNP.2012.6459977
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-10-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Facebook Communities Servers Merging Clustering algorithms Algorithm design and analysis online social networks Self-similarity interaction graph inter-server communications data center
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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