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Load-balanced migration of social media to content clouds

Published: 01 June 2011 Publication History

Abstract

Social networked applications have been more and more popular, and have brought great challenges to the network engineering, particularly the huge demands of bandwidth and storage for social media. The recently emerged content clouds shed light on this dilemma. Towards the migration to clouds, partitioning the social contents has drawn significant interests from the literature. Yet the existing works focus on preserving the social relationship only, while an important factor, user access pattern, is largely overlooked.
In this paper, by examining a large collection of YouTube video data, we first demonstrate that partitioning the network entirely based on social relationship would lead to unbalanced partitions in terms of access. We further analyze the role of social relationship in the social media applications, and conclude that user access pattern should be taken into account and social relationship should be dynamically preserved. We formulate the problem as a constrained k-medoids clustering problem, and propose a novel Weighted Partitioning Around Medoids (wPAM) solution. We present a dissimilarity/similarity metric to facilitate the preservation of the social relationship. We compare our solution with other state-of-the-art algorithms, and the preliminary results show that it significantly decreases the access deviation in each cloud server, and flexibly preserves the social relationship.

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  • (2018)Dependency- and similarity-aware caching for HTTP adaptive streamingMultimedia Tools and Applications10.1007/s11042-016-4308-z77:1(1453-1474)Online publication date: 1-Jan-2018
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cover image ACM Conferences
NOSSDAV '11: Proceedings of the 21st international workshop on Network and operating systems support for digital audio and video
June 2011
138 pages
ISBN:9781450307772
DOI:10.1145/1989240
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 June 2011

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Author Tags

  1. clustering
  2. content cloud
  3. social network

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Cited By

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  • (2018)Analysis of cloud services in agriculture through internet of things and big dataIndian Journal of Science and Technology10.17485/ijst/2018/v11i19/12322211:19(1-4)Online publication date: 1-May-2018
  • (2018)Comparison of Different Research Works in Leak Detection and Localization to Design and Implementation of WSN Architecture2018 3rd International Conference and Workshops on Recent Advances and Innovations in Engineering (ICRAIE)10.1109/ICRAIE.2018.8710440(1-6)Online publication date: Nov-2018
  • (2018)Dependency- and similarity-aware caching for HTTP adaptive streamingMultimedia Tools and Applications10.1007/s11042-016-4308-z77:1(1453-1474)Online publication date: 1-Jan-2018
  • (2018)Propagation-Based Social Video Content ReplicationOnline Social Media Content Delivery10.1007/978-981-10-2774-1_4(57-83)Online publication date: 1-Aug-2018
  • (2017)Cost aware caching and streaming scheduling for efficient cloud based TV2017 IEEE International Conference on Communications (ICC)10.1109/ICC.2017.7997150(1-6)Online publication date: May-2017
  • (2016)Selective Data Replication for Online Social Networks with Distributed DatacentersIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2015.248526627:8(2377-2393)Online publication date: 13-Jul-2016
  • (2016)Dispersing Instant Social Video Service Across Multiple CloudsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2015.241494127:3(735-747)Online publication date: 1-Mar-2016
  • (2016)Network server load balancing using consensus-based control algorithm2016 IEEE Industrial Electronics and Applications Conference (IEACon)10.1109/IEACON.2016.8067394(291-296)Online publication date: Nov-2016
  • (2016)IntroductionSocial Video Content Delivery10.1007/978-3-319-33652-7_1(1-6)Online publication date: 3-Jun-2016
  • (2015)Cost-Minimizing Dynamic Migration of Content Distribution Services into Hybrid CloudsIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2014.237183126:12(3330-3345)Online publication date: 1-Dec-2015
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