We study the problem of dynamic resource allocation to clustered Web applications. We extend application server middleware with the ability to automatically decide the size of application clusters and their placement on physical machines. Unlike existing solutions, which focus on maximizing resource utilization and may unfairly treat some applications, the approach introduced in this paper considers the satisfaction
of each application with a particular resource allocation and attempts to at least equally satisfy all applications. We model
satisfaction using utility functions, mapping CPU resource allocation to the performance of an application relative to its
objective. The demonstrated online placement technique aims at equalizing the utility value across all applications while also
satisfying operational constraints, preventing the over-allocation of memory, and minimizing the number of placement changes. We have implemented our technique in a leading commercial middleware product. Using this real-life testbed and a simulation
we demonstrate the benefit of the utility-driven technique as compared to other state-of-the-art techniques.
CitationCarrera, D. [et al.]. Utitily-based placement of dynamic Web applications with fairness goals. A: Network Operations and Management Symposium. "11th IEEE/IFIP Network Operations and Management Symposium". Salvador de Bahía: 2008, p. 9-16.
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