Optimizing Inter-server Communication for Online Social Networks

Distributed storage systems are the key infrastructures for hosting the user data of large-scale Online Social Networks (OSNs). The amount of inter-server communication is an important scalability indicator for these systems. Data partitioning and replication are two inter-related issues affecting t...

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Main Authors: Tang, Jing, Tang, Xueyan, Yuan, Junsong
Other Authors: School of Computer Science and Engineering
Format: Conference or Workshop Item
Language:English
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/10356/81970
http://hdl.handle.net/10220/41022
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-819702020-11-01T04:43:09Z Optimizing Inter-server Communication for Online Social Networks Tang, Jing Tang, Xueyan Yuan, Junsong School of Computer Science and Engineering School of Electrical and Electronic Engineering Interdisciplinary Graduate School (IGS) 2015 IEEE 35th International Conference on Distributed Computing Systems (ICDCS) Multi-plAtform Game Innovation Centre Online Social Networks Distributed Data Placement Distributed storage systems are the key infrastructures for hosting the user data of large-scale Online Social Networks (OSNs). The amount of inter-server communication is an important scalability indicator for these systems. Data partitioning and replication are two inter-related issues affecting the inter-server traffic caused by user-initiated read and write operations. This paper investigates the problem of minimizing the total inter-server traffic among a cluster of OSN servers through joint partitioning and replication optimization. We propose a Traffic-Optimized Partitioning and Replication (TOPR) method based on an analysis of how replica allocation affects the interserver communication. Lightweight algorithms are developed to adjust partitioning and replication dynamically according to data read and write rates. Evaluations with real Facebook and Twitter social graphs show that TOPR significantly reduces the interserver communication compared with state-of-the-art methods. NRF (Natl Research Foundation, S’pore) Accepted version 2016-07-29T06:20:38Z 2019-12-06T14:43:58Z 2016-07-29T06:20:38Z 2019-12-06T14:43:58Z 2015 Conference Paper Tang, J., Tang, X., Yuan, J. (2015). Optimizing Inter-Server Communication for Online Social Networks. In Proceedings of The 35th IEEE International Conference on Distributed Computing Systems, 215-224. https://hdl.handle.net/10356/81970 http://hdl.handle.net/10220/41022 10.1109/ICDCS.2015.30 en © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/ICDCS.2015.30]. 10 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Online Social Networks
Distributed Data Placement
spellingShingle Online Social Networks
Distributed Data Placement
Tang, Jing
Tang, Xueyan
Yuan, Junsong
Optimizing Inter-server Communication for Online Social Networks
description Distributed storage systems are the key infrastructures for hosting the user data of large-scale Online Social Networks (OSNs). The amount of inter-server communication is an important scalability indicator for these systems. Data partitioning and replication are two inter-related issues affecting the inter-server traffic caused by user-initiated read and write operations. This paper investigates the problem of minimizing the total inter-server traffic among a cluster of OSN servers through joint partitioning and replication optimization. We propose a Traffic-Optimized Partitioning and Replication (TOPR) method based on an analysis of how replica allocation affects the interserver communication. Lightweight algorithms are developed to adjust partitioning and replication dynamically according to data read and write rates. Evaluations with real Facebook and Twitter social graphs show that TOPR significantly reduces the interserver communication compared with state-of-the-art methods.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Tang, Jing
Tang, Xueyan
Yuan, Junsong
format Conference or Workshop Item
author Tang, Jing
Tang, Xueyan
Yuan, Junsong
author_sort Tang, Jing
title Optimizing Inter-server Communication for Online Social Networks
title_short Optimizing Inter-server Communication for Online Social Networks
title_full Optimizing Inter-server Communication for Online Social Networks
title_fullStr Optimizing Inter-server Communication for Online Social Networks
title_full_unstemmed Optimizing Inter-server Communication for Online Social Networks
title_sort optimizing inter-server communication for online social networks
publishDate 2016
url https://hdl.handle.net/10356/81970
http://hdl.handle.net/10220/41022
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