Cost optimization for online social networks on geo-distributed clouds

Geo-distributed IaaS (Infrastructure-as-a-Service) clouds provide an intriguing platform to deploy Online Social Network (OSN) services. To leverage the potential of clouds, a major task of OSN providers is optimizing the monetary cost spent on cloud resource utilization while providing satisfactory Quality of Service (QoS) to OSN users. We thus study the problem of cost optimization for the dynamic OSN on multiple geo-distributed clouds over consecutive time periods, with its QoS meeting the pre-defined requirement. We model the QoS as well as the cost of an OSN, formulate the problem, and design a solution named cosplay. Our experiments with a large-scale Twitter trace show that, while always ensuring the QoS as required, cosplay can achieve superior one-time cost reduction compared with the state of the art, and can also reduce the accumulative cost significantly when continuously evaluated over 48 months with dynamics comparable to real-world OSNs.