A multi-agent systems approach to autonomic computing

The goal of autonomic computing is to create computing systems capable of managing themselves to a far greater extent than they do today. This paper presents Unity, a decentralized architecture for autonomic computing based on multiple interacting agents called autonomic elements. We illustrate how the Unity architecture realizes a number of desired autonomic system behaviors including goal-driven self-assembly, self-healing, and real-time self-optimization. We then present a realistic prototype implementation, showing how a collection of Unity elements self-assembles, recovers from certain classes of faults, and manages the use of computational resources (e.g. servers) in a dynamic multi-application environment. In Unity, an autonomic element within each application environment computes a resource-level utility function based on information specified in that applicationýs service-level utility function. Resource-level utility functions from multiple application environments are sent to a Resource Arbiter element, which computes a globally optimal allocation of servers across the applications. We present illustrative empirical data showing the behavior of our implemented system in handling realistic Web-based transactional workloads running on a Linux cluster.

[1]  Michael P. Wellman,et al.  A Market-Based Approach to Allocating QoS for Multimedia Applications , 1996 .

[2]  Edmund H. Durfee,et al.  Toward Inquiry-Based Education Through Interacting Software Agents , 1996, Computer.

[3]  John P. Lehoczky,et al.  Practical Solutions for QoS-Based Resource Allocation , 1998, RTSS 1998.

[4]  Daniel P. Siewiorek,et al.  Practical solutions for QoS-based resource allocation problems , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[5]  S. Lalis,et al.  Market-driven service allocation in a QoS-capable environment , 1998, ICE '98.

[6]  Nicholas R. Jennings,et al.  On agent-based software engineering , 2000, Artif. Intell..

[7]  Mark S. Squillante,et al.  Internet traffic: periodicity, tail behavior, and performance implications , 2000 .

[8]  Amin Vahdat,et al.  Managing energy and server resources in hosting centers , 2001, SOSP.

[9]  Steven Tuecke,et al.  The Physiology of the Grid An Open Grid Services Architecture for Distributed Systems Integration , 2002 .

[10]  Jeffrey K. MacKie-Mason,et al.  A Market-Based Approach to Optimal Resource Allocation in Integrated-Services Connection-Oriented Networks , 2002, Oper. Res..

[11]  Craig Boutilier,et al.  Cooperative Negotiation in Autonomic Systems using Incremental Utility Elicitation , 2002, UAI.

[12]  T. Kelly Utility-Directed Allocation , 2003 .

[13]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.