Abstract
Network resource allocation is the foundation for content delivery. In an online social network, prediction of social behaviors provides an indicator for resource allocation. This chapter presents strategies to enhance the performance of network resource allocation based on the prediction of social behaviors.
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©[2015] IEEE. Reprinted, with permission, from IEEE Transactions on Parallel and Distributed Systems.
References
V.K. Adhikari et al., Reverse engineering the youtube video delivery cloud, in IEEE Hot Topics in Media Delivery Workshop (2011)
E.M. Azoff, Neural Network Time Series Forecasting of Financial Markets (Wiley, 1994)
M. Arlitt, B. Krishnamurthy, P. Gill, A few chirps about twitter, in ACM Workshop on Online Social Networks (WOSN) (2008)
J. Benesty et al., Pearson correlation coefficient, in Noise Reduction in Speech Processing? (Springer, 2009), pp. 291–324
M. Cha, A. Mislove, K.P. Gummadi, A measurement-driven analysis of information propagation in the Flickr social network, in ACM International Conference on World Wide Web (WWW) (2009)
M. Cha et al., I tube, you tube, everybody tubes: analyzing the world’s largest user generated content video system, in ACM SIGCOMM (2007), pp. 1–14
S. Chen, S.A. Billings, P.M. Grant, Non-linear system identification using neural networks. Int. J. Control 51(6), 1191–1214 (1990)
B. Chun et al., Planetlab: an overlay testbed for broad-coverage services. ACM SIGCOMM Comput. Commun. Rev. 33(3), 3–12 (2003)
K. Hornik, M. Stinchcombe, H. White, Multilayer feedforward networks are universal approximators. Neural Netw. 2(5), 359–366 (1989)
R. Krishnan et al., Moving beyond end-to-end path information to optimize CDN performance, in ACM Internet Measurement Conference (IMC) (2009)
H. Kwak et al., What is twitter, a social network or a news media?, in ACM International Conference on World Wide Web (WWW) (2010)
K. Lai, D. Wang, Towards understanding the external links of video sharing sites: measurement and analysis, in ACM Network and Operating System Support for Digital Audio and Video (NOSSDAV) (2010)
H. Li, H. Wang, J. Liu, Video sharing in online social network: measurement and analysis, in ACM Network and Operating System Support for Digital Audio and Video (NOSSDAV) (2012)
Y. Liu, Y. Guo, C. Liang, A survey on peer-to-peer video streaming systems. Peer-to-peer Netw. Appl. 1(1), 18–28 (2008)
G.I. Marchuk, Numerical Methods and Applications (CRC, 1994)
R.H. Myers et al., Generalized Linear Models (Wiley, 2010)
G. Peng, CDN: content distribution network, in arXiv preprint cs/0411069 (2004)
J. Ritterman, M. Osborne, E. Klein, Using prediction markets and twitter to predict a swine flu pandemic, in 1st International Workshop on Mining Social Media (2009)
N. Savage, Twitter as medium and message. Commun. ACM 54(3), 18–20 (2011)
M. Saxena, U. Sharan, S. Fahmy, Analyzing video services in web 2.0: a global perspective, in ACM Network and Operating System Support for Digital Audio and Video (NOSSDAV) (2008)
D.F. Specht, A general regression neural network. IEEE Trans. Neural Netw. 2(6), 568–576 (1991)
G. Szabo, B.A. Huberman, Predicting the popularity of online content. Commun. ACM 53(8), 80–88 (2010)
Z. Wang et al., Guiding internet-scale video service deployment using microblog-based prediction, in IEEE International Conference on Distributed Computing Systems (INFOCOM) (2012)
Z. Wang et al., Propagation-based social-aware replication for social video contents, in ACM International Conference on Multimedia (Multimedia) (2012)
I.H. Witten, E. Frank, M.A. Hall, Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann, 2011)
D. Xu et al., Analysis of a CDN-P2P hybrid architecture for cost-effective streaming media distribution. Multimedia Syst. 11(4), 383–399 (2006)
J. Yang, S. Counts, Predicting the speed, scale, and range of information diffusion in twitter, in International AAAI Conference on Weblogs and Social Media (2010)
H. Yin et al., Design and deployment of a hybrid CDN-P2P system for live video streaming: experiences with livesky, in ACM International Conference on Multimedia (Multimedia) (2009)
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Wang, Z., Zhu, W., Yang, S. (2018). Enhancing Multimedia Network Resource Allocation Using Social Prediction. In: Online Social Media Content Delivery. SpringerBriefs in Computer Science. Springer, Singapore. https://doi.org/10.1007/978-981-10-2774-1_3
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DOI: https://doi.org/10.1007/978-981-10-2774-1_3
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