Stephen Paul Morgan

Clockwork: A new movement in autonomic systems

Statically tuned computing systems may perform poorly when running time-varying workloads. Current work on autonomic tuning largely involves reactive autonomicity, based on feedback control. This paper identifies a new way of thinking about autonomic tuning, that is, predictive autonomicity, based on feedforward control. A general method, called Clockwork, for constructing predictive autonomic systems is proposed. The method is based on statistical modeling, tracking, and forecasting techniques borrowed from econometrics. Systems employing the method detect and subsequently forecast cyclic variations in load, estimate the impact on future performance, and use these data to self-tune, dynamically, in anticipation of need. The paper describes a prototype network-attached storage system that was built using Clockwork, demonstrating the feasibility of the method, and presents key performance measurements of the prototype, demonstrating the practicality of the methods.

Sherlock: Commercial High Assurance Network Computing Extended Abstract

IBM Research and the U.S. Department of Defense teamed to determine if governmental high assurance practices could be applied to commercially available network computers. The focus of the project was on using the thin client computing architecture to connect to trusted information domains of different classification levels at different times. Importantly, the information from a given classified domain must not migrate from its domain. Achieving this goal requires state clearing, and encrypting and authenticating all transferred data between the thin client and the trusted domain.