Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Open, Closed, and Mixed Networks of Queues with Different Classes of Customers
Journal of the ACM (JACM)
Performance by Design: Computer Capacity Planning By Example
Performance by Design: Computer Capacity Planning By Example
Parameter inference of queueing models for IT systems using end-to-end measurements
Performance Evaluation
A Framework for Optimal Service Selection in Broker-Based Architectures with Multiple QoS Classes
SCW '06 Proceedings of the IEEE Services Computing Workshops
Service Consolidation with End-to-End Response Time Constraints
SEAA '08 Proceedings of the 2008 34th Euromicro Conference Software Engineering and Advanced Applications
Modeling response times in the Google ROADEF/EURO challenge
ACM SIGMETRICS Performance Evaluation Review
Components mobility for energy efficiency of digital home
Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
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We address the data-center consolidation problem: given a working data-center, the goal of the problem is to choose which software applications must be deployed on which servers in order to minimize the number of servers to use while avoiding the overloading of system resources and satisfying availability constraints. This in order to tradeoff between quality of service issues and data-center costs. The problem is approached through a robust model of the data-center which exploits queueing networks theory. Then, we propose two mixed integer linear programming formulations of the problem able to capture novel aspects such as workload partitioning (load-balancing) and availability issues. A simple heuristic is proposed to compute solutions in a short time. Experimental results illustrate the impact of our approach with respect to a real-world consolidation project.