Title

Anticipatory Configuration of Resource-aware Applications

Date of Original Version

2005

Type

Conference Proceeding

Rights Management

Can archive pre-print and post-print or publisher's version/PDF

Abstract or Description

We propose an improved approach to dynamic configuration of resource-aware applications. The new anticipatory model of configuration maximizes utility based on three inputs: user preferences, application capability profiles, and resource availability. In this respect, the proposed model is similar to a model of configuration described in [2]. However, the latter addressed the dynamic nature of the problem by reacting to changes (such as decrease in resource availability), and maximized the utility in a point-wise manner. The newly proposed anticipatory approach explicitly models the duration of the task and leverages possible information about the future (such as stochastic resource availability over the expected duration of the task). We expect that the anticipatory model will improve user’s utility, conserve scarce resources, and reduce the amount of disruption to the user resulting from changes when compared to the reactive model. However, the optimization problem underlying the anticipatory model is computationally more difficult than the problem underlying the reactive model. We would like to investigate if the anticipatory approach is feasible and efficient in practice while delivering the above-mentioned improvements. In this paper, we carefully state the model of anticipatory configuration, highlight the sources of complexity in the problem, propose an algorithm to the anticipatory configuration problem, and provide a roadmap for research.

DOI

10.1145/1083091.1083102

Comments

Position paper for Seventh Workshop on Economics-Driven Software Research (EDSER-7), affiliated with the 27th Int’l Conf on Software Engineering, 2005.

This work has been funded in part by the National Science Foundation under Grant CCF-0438929, by the Sloan Software Industry Center at Carnegie Mellon, and by the High Dependability Computing Program from NASA Ames cooperative agreement NCC-2-1298.

 

Published In

EDSER '05 Proceedings of the seventh international workshop on Economics-driven software engineering research,ACM , 1-4.