JOURNAL ARTICLE

GeoScale: Providing Geo-Elasticity in Distributed Clouds

Abstract

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 well suited for temporal and spatial workload fluctuations seen by modern web applications. In this paper, we argue the need of geo-elasticity and present GeoScale, a system to provide geo-elasticity in distributed clouds. We describe GeoScale's model-driven proactive provisioning approach and conduct an initial evaluation of GeoScale on Amazon's distributed EC2 cloud. Our results show up to 31% improvement in the 95th percentile response time when compared to traditional elasticity techniques.

Keywords:
Provisioning Elasticity (physics) Cloud computing Computer science Workload Distributed computing Scaling Computer network Operating system Mathematics

Metrics

6
Cited By
3.32
FWCI (Field Weighted Citation Impact)
19
Refs
0.93
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Peer-to-Peer Network Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications

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