Dynamic Predictive Algorithms for Seamless Scaling of Social Media Applications in Multi-Provider Clouds


Grant Data
Project Title
Dynamic Predictive Algorithms for Seamless Scaling of Social Media Applications in Multi-Provider Clouds
Principal Investigator
Dr Wu, Chuan   (Principal investigator)
Co-Investigator(s)
Dr Lin Xiaojun   (Co-Investigator)
Dr Li Zongpeng   (Co-Investigator)
Duration
42
Start Date
2012-12-01
Completion Date
2016-05-31
Amount
905425
Conference Title
Presentation Title
Keywords
Optimization, Cloud computing, Social media application, Algorithm design
Discipline
Network
Panel
Engineering (E)
Sponsor
RGC General Research Fund (GRF)
HKU Project Code
HKU 717812E
Grant Type
General Research Fund (GRF)
Funding Year
2012/2013
Status
On-going
Objectives
1) [Joint Optimization Framework]: We formulate an optimization problem for optimal social media service deployment over the long run, which models various charging plans and inter-connection conditions of different cloud data centers; 2) [Demand Prediction]: We build an analytical model to describe information propagation following social connections and content correlations, and use the model to predict future content demand from each region; 3) [Dynamic Algorithm Design]: We design dynamic algorithms pursuing long-term optimality of the optimization problem, by exploiting forecasted demands and problem-specific structures. We will carry out extensive theoretical analysis to show their effectiveness; 4) [Implementation and Evaluation]: We realize and evaluate our algorithms using large-scale experiments on a distributed cloud testbed we are building, as well as in public clouds such as Amazon EC2.