Providing Geo-Elasticity in Geographically Distributed Clouds

Geographically distributed cloud platforms are well suited for serving a geographically diverse user base. However traditional cloud provisioning mechanisms that make local scaling decisions are not adequate for delivering best possible performance for modern web applications that observe both temporal and spatial workload fluctuations. In this paper, we propose GeoScale, a system that provides geo-elasticity by combining model-driven proactive and agile reactive provisioning approaches. GeoScale can dynamically provision server capacity at any location based on workload dynamics. We conduct a detailed evaluation of GeoScale on Amazon’s geo-distributed cloud, and show up to 40% improvement in the 95th percentile response time when compared to traditional elasticity techniques.