WSC '05 Proceedings of the 37th conference on Winter simulation
Combining Different Multi-tenancy Patterns in Service-Oriented Applications
EDOC '09 Proceedings of the 2009 IEEE International Enterprise Distributed Object Computing Conference (edoc 2009)
Feedback-Control-Based Performance Regulation for Multi-Tenant Applications
ICPADS '09 Proceedings of the 2009 15th International Conference on Parallel and Distributed Systems
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
A Framework for Optimized Distribution of Tenants in Cloud Applications
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
An Effective Heuristic for On-line Tenant Placement Problem in SaaS
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Multi-tenant SaaS applications: maintenance dream or nightmare?
Proceedings of the Joint ERCIM Workshop on Software Evolution (EVOL) and International Workshop on Principles of Software Evolution (IWPSE)
The SPOSAD Architectural Style for Multi-tenant Software Applications
WICSA '11 Proceedings of the 2011 Ninth Working IEEE/IFIP Conference on Software Architecture
Towards modeling a variable architecture for multi-tenant SaaS-applications
Proceedings of the Sixth International Workshop on Variability Modeling of Software-Intensive Systems
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The cloud computing paradigm enables the provision of costefficient IT-services by leveraging economies of scale and sharing data center resources efficiently among multiple independent applications and customers. However, the sharing of resources leads to possible interference between users and performance problems are one of the major obstacles for potential cloud customers. Consequently, it is one of the primary goals of cloud service providers to have different customers and their hosted applications isolated as much as possible in terms of the performance they observe. To make different offerings, comparable with regards to their performance isolation capabilities, a representative metric is needed to quantify the level of performance isolation in cloud environments. Such a metric should allow to measure externally by running benchmarks from the outside treating the cloud as a black box. In this paper, we propose three different types of novel metrics for quantifying the performance isolation of cloud-based systems and a simulation-based case study applying these metrics in the context of a Softwareas-a-Service (SaaS) scenario where different customers (tenants) share one single application instance. We consider four different approaches to achieve performance isolation and evaluate them based on the proposed metrics. The results demonstrate the effectiveness and practical usability of the proposed metrics in quantifying the performance isolation of cloud environments.