Towards an Understanding of Decision Complexity in IT Configuration

There exist many opportunities for deploying autonomic computing in an IT environment. The highest-value opportunities are going to be where we can reduce human decision-making complexity. Decision complexity is the complexity faced by a non-expert system administrator—the person providing IT support in a small-business environment, who is confronted by decisions during the configuration process, and is a measure of how easy or hard it is to identify the appropriate sequence of configuration actions to perform in order to achieve a specified configuration goal. To identify spots of high decision-making complexity, we need a model of decision complexity for configuring and operating computing systems. This paper extends previous work on models and metrics for IT configuration complexity by adding the concept of decision complexity. As the first step towards a complete model of decision complexity, we describe an extensive user study of decision making in a carefully-mapped analogous domain (route planning), and illustrate how the results of that study suggest an initial model of decision complexity applicable to IT configuration. The model identifies the key factors affecting decision complexity and highlights several interesting results, including the fact that decision complexity has significantly different impacts on user-perceived difficulty than on objective measures like time and error rate. We also describe some of the implications of our decision complexity model for system designers seeking to automate the decision-making and reduce the configuration complexity of their systems.

By: Bin Lin; Aaron B. Brown; Joseph L. Hellerstein

Published in: RC23901 in 2006


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