Utility functions in autonomic systems

Utility functions provide a natural and advantageous framework for achieving self-optimization in distributed autonomic computing systems. We present a distributed architecture, implemented in a realistic prototype data center, that demonstrates how utility functions can enable a collection of autonomic elements to continually optimize the use of computational resources in a dynamic, heterogeneous environment. Broadly, the architecture is a two-level structure of independent autonomic elements that supports flexibility, modularity, and self-management. Individual autonomic elements manage application resource usage to optimize local service-level utility functions, and a global arbiter allocates resources among application environments based on resource-level utility functions obtained from the managers of the applications. We present empirical data that demonstrate the effectiveness of our utility function scheme in handling realistic, fluctuating Web-based transactional workloads running on a Linux cluster.

[1]  Ivan E. Sutherland,et al.  A futures market in computer time , 1968, Commun. ACM.

[2]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[3]  A. Mas-Colell,et al.  Microeconomic Theory , 1995 .

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

[5]  Douglas S. Reeves,et al.  Dynamic resource allocation based on measured QoS , 1996 .

[6]  Riccardo Bettati,et al.  A Three-Pass Establishment Protocol for Real-Time Multiparty Communication , 1997 .

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

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

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

[10]  Michael Anthony Bauer,et al.  Issues in Managing Soft QoS Requirements in Distributed Systems Using a Policy-Based Framework , 2001, POLICY.

[11]  Providing absolute differentiated services for real-time applications in static-priority scheduling networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

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

[13]  Peter Braun,et al.  A policy based QoS management system for the IntServ/DiffServ based Internet , 2002, Proceedings Third International Workshop on Policies for Distributed Systems and Networks.

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

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

[16]  Emil C. Lupu,et al.  An adaptive policy based management framework for differentiated services networks , 2002, Proceedings Third International Workshop on Policies for Distributed Systems and Networks.

[17]  Keith Cheverst,et al.  Utilising the event calculus for policy driven adaptation on mobile systems , 2002, Proceedings Third International Workshop on Policies for Distributed Systems and Networks.

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

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

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

[21]  Wei Jin,et al.  USENIX Association Proceedings of USITS ’ 03 : 4 th USENIX Symposium on Internet Technologies and Systems , 2003 .

[22]  Claudio Bartolini,et al.  Market-Based Resource Allocation for Utility Data Centers , 2003 .

[23]  Prashant J. Shenoy,et al.  Dynamic resource allocation for shared data centers using online measurements , 2003, IWQoS'03.

[24]  Xiaoyun Zhu,et al.  Statistical service assurances for applications in utility grid environments , 2004, Perform. Evaluation.

[25]  Steve R. White,et al.  Unity: experiences with a prototype autonomic computing system , 2004 .