This paper presents SHARP: a scalable framework for Dynamic Joint Replica Placement and Request Routing (DJRPRR) scheduling in content delivery networks. After grouping similar proxies and modeling them by a single section, we propose a hierarchical scheduling framework to greatly reduce the dimensions of the mathematical formulation. In every phase the obtained shaped formulation has an easy-solvable form and the complete optimization process is highly scalable. To verify the scalability and effectiveness of our approach, SHARP is evaluated by comprehensive experiment settings which are derived from realistic data/topology of an operational commercial CDN.
['Yi Wang', 'Chen Tian', 'Hongbo Jiang', 'Xue Liu', 'Jinhua Chen', 'Wenyu Liu']
SHARP: A Scalable Framework for Dynamic Joint Replica Placement and Request Routing Scheduling