The complexity of large-scale systems and networks has raised unprecedented challenges for system management. Many mission critical systems are deployed by integrating thousands of heterogeneous components. The numerous software components running on these large systems often obscure the dependencies and interactions among system components dramatically increasing system complexity. Furthermore, many complex systems are not static and keep evolving with numerous changes such as software or hardware upgrades and configuration modifications. Therefore, the system scale, heterogeneity and dynamics as well as hidden dependencies all contribute to today\u2019s difficulties in complexity management. The unmanageable system complexity has significantly increased operational costs in recent years and also affected system reliability and availability.

The objective of the ASDS project is to:

1. understand the nature of system complexity, especially for large and complex systems;
2. introduce automation and intelligence into the lifecycle of system and service management including system design, deployment, operation and maintenance.

The ASDS group creates novel management technology that applies control theory, statistical learning and inference, and information theory in addition to experimental computer science methodologies to address the growing complexity in large systems and networks.

Currently the ASDS groups focuses on several research topics including system data mining and analysis, IP service management and next generation data centers.