Public Cloud Storage-Assisted Mobile Social Video Sharing: A Supermodular Game Approach

Mobile social video sharing enables mobile users to create ultra-short video clips and instantly share them with social friends, which poses significant pressure to the content distribution infrastructure. In this paper, we propose a public cloud-assisted architecture to tackle this problem. In particular, by motivating mobile users to upload videos to the local public cloud to serve requests, and, therefore, having a permission to access friends’ videos stored in the cloud, our method can alleviate the traffic burden to the social service providers, while reducing the service latency of mobile users. First, we present a general framework to model the information diffusion and utility function of each user on the proposed architecture, and formulate the problem as a decentralized social utility maximization game. Second, we show that this problem is a supermodular game and there exists at least one socially aware Nash equilibrium (SNE). We then develop two decentralized algorithms to solve this problem. The first algorithm can find an SNE with less computation complexity, and the second algorithm can find the Pareto-optimal SNE with better performance. Finally, through extensive experiments, we demonstrate that the overall system performance can be significantly improved by exploiting the selflessness among social friends.

[1]  Yonggang Wen,et al.  Toward Optimal Deployment of Cloud-Assisted Video Distribution Services , 2013, IEEE Transactions on Circuits and Systems for Video Technology.

[2]  Yonggang Wen,et al.  Cloud Mobile Media: Reflections and Outlook , 2014, IEEE Transactions on Multimedia.

[3]  Yonggang Wen,et al.  Budget-Efficient Viral Video Distribution Over Online Social Networks: Mining Topic-Aware Influential Users , 2018, IEEE Transactions on Circuits and Systems for Video Technology.

[4]  Bo Li,et al.  Scaling social media applications into geo-distributed clouds , 2012, 2012 Proceedings IEEE INFOCOM.

[5]  Athina Markopoulou,et al.  Minimizing Peak Load from Information Cascades: Social Networks Meet Cellular Networks , 2016, IEEE Transactions on Mobile Computing.

[6]  H. Vincent Poor,et al.  From Technological Networks to Social Networks , 2013, IEEE Journal on Selected Areas in Communications.

[7]  Feng Wang,et al.  Understand Instant Video Clip Sharing on Mobile Platforms: Twitter's Vine as a Case Study , 2014, NOSSDAV.

[8]  Yu Gu,et al.  Watch global, cache local: YouTube network traffic at a campus network: measurements and implications , 2008, Electronic Imaging.

[9]  John C. S. Lui,et al.  Analysis of Adaptive Incentive Protocols for P2P Networks , 2009, IEEE INFOCOM 2009.

[10]  Xu Chen,et al.  A social group utility maximization framework with applications in database assisted spectrum access , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[11]  Antonio Ortega,et al.  Scalable proxy caching of video under storage constraints , 2002, IEEE J. Sel. Areas Commun..

[12]  David K. Y. Yau,et al.  Incentive and Service Differentiation in P2P Networks: A Game Theoretic Approach , 2006, IEEE/ACM Transactions on Networking.

[13]  Ravi Sundaram,et al.  WebCloud: Recruiting Social Network Users to Assist in Content Distribution , 2012, 2012 IEEE 11th International Symposium on Network Computing and Applications.

[14]  Haiying Shen,et al.  Selective Data replication for Online Social Networks with Distributed Datacenters , 2013, 2013 21st IEEE International Conference on Network Protocols (ICNP).

[15]  Xuelong Li,et al.  Joint Content Replication and Request Routing for Social Video Distribution Over Cloud CDN: A Community Clustering Method , 2016, IEEE Transactions on Circuits and Systems for Video Technology.

[16]  Ben Y. Zhao,et al.  Exploiting locality of interest in online social networks , 2010, CoNEXT.

[17]  Ke Xu,et al.  SNACS: Social Network-Aware Cloud Assistance for Online Propagated Video Sharing , 2015, 2015 IEEE 8th International Conference on Cloud Computing.

[18]  Ulas C. Kozat,et al.  Utilizing Social Influence in Content Distribution Networks , 2011, 2011 IEEE International Conference on Communications (ICC).

[19]  Yonggang Wen,et al.  Reducing Operational Costs in Cloud Social TV: An Opportunity for Cloud Cloning , 2014, IEEE Transactions on Multimedia.

[20]  K. J. Ray Liu,et al.  Game-Theoretic Pricing for Video Streaming in Mobile Networks , 2012, IEEE Transactions on Image Processing.

[21]  Hai Jin,et al.  Minimizing Inter-Server Communications by Exploiting Self-Similarity in Online Social Networks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[22]  Jian Huang,et al.  Community based effective social video contents placement in cloud centric CDN network , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).

[23]  Jun Li,et al.  Multi-objective data placement for multi-cloud socially aware services , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[24]  Cory Hill,et al.  f4: Facebook's Warm BLOB Storage System , 2014, OSDI.

[25]  He Chen,et al.  Pricing and Resource Allocation via Game Theory for a Small-Cell Video Caching System , 2016, IEEE Journal on Selected Areas in Communications.

[26]  Lifeng Sun,et al.  Propagation-based social-aware replication for social video contents , 2012, ACM Multimedia.

[27]  K. J. Ray Liu,et al.  Cooperative peer-to-peer streaming: An evolutionary game-theoretic approach , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[28]  Jian Huang,et al.  Social TV analytics: a novel paradigm to transform TV watching experience , 2014, MMSys '14.

[29]  Wenzhong Li,et al.  Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing , 2015, IEEE/ACM Transactions on Networking.

[30]  Xuelong Li,et al.  Toward an SDN-enabled big data platform for social TV analytics , 2015, IEEE Network.

[31]  Yonggang Wen,et al.  Minimizing monetary cost via cloud clone migration in multi-screen cloud social TV system , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[32]  Pablo Rodriguez,et al.  The little engine(s) that could: scaling online social networks , 2012, TNET.

[33]  Junsong Yuan,et al.  Optimizing Inter-server Communication for Online Social Networks , 2015, 2015 IEEE 35th International Conference on Distributed Computing Systems.

[34]  Xu Chen,et al.  Personalized location privacy in mobile networks: A social group utility approach , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[35]  Lixin Gao,et al.  The impact of YouTube recommendation system on video views , 2010, IMC '10.

[36]  Krishna P. Gummadi,et al.  On word-of-mouth based discovery of the web , 2011, IMC '11.