Publication

Cost-Optimal Outsourcing of Applications into the Clouds

Immanuel Trummer
2010
Conference Papers

Résumé

Commercial services for provisioning software components and virtual infrastructure in the cloud are emerging. For customers, this creates a multitude of possibilities for outsourcing part of the IT-stack to third parties in order to run their applications. These possibilities are associated with different running costs, so cloud customers have to determine the optimal solution. In this paper, we present and experimentally evaluate an algorithm that solves the corresponding optimization problem. We assume that applications are described as templates, fixing the deployment structure and constraining the properties of the used soft- and hardware components. Different parts of the application may be outsourced to different providers and several levels of outsourcing can be considered. However, dependencies between different parts of the application have to be respected. Our algorithm decomposes the application graph in a first step in order to discover all suitable cloud provisioning services from a registry. It determines the optimal solution by representing the problem as constraint optimization problem that can be solved by an existing solver implementation.

Source officielle

https://infoscience.epfl.ch/entities/publication/312c7c06-b330-4c49-b4b9-ea205e556a03

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Immanuel Trummer
2010
Conference Papers

Résumé

Source officielle

https://infoscience.epfl.ch/entities/publication/312c7c06-b330-4c49-b4b9-ea205e556a03

À propos de ce résultat

Concepts associés (32)

Optimization problem

In mathematics, computer science and economics, an optimization problem is the problem of finding the best solution from all feasible solutions. Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete: An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.

Constrained optimization

In mathematical optimization, constrained optimization (in some contexts called constraint optimization) is the process of optimizing an objective function with respect to some variables in the presence of constraints on those variables. The objective function is either a cost function or energy function, which is to be minimized, or a reward function or utility function, which is to be maximized.

Optimisation convexe

vignette|320x320px|Optimisation convexe dans un espace en deux dimensions dans un espace contraint L'optimisation convexe est une sous-discipline de l'optimisation mathématique, dans laquelle le critère à minimiser est convexe et l'ensemble admissible est convexe. Ces problèmes sont plus simples à analyser et à résoudre que les problèmes d'optimisation non convexes, bien qu'ils puissent être NP-difficile (c'est le cas de l'optimisation copositive). La théorie permettant d'analyser ces problèmes ne requiert pas la différentiabilité des fonctions.

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