Autonomous decentralized resource allocation for tracking dynamic load change

System architecture is proposed to adapt computing resource to load changes of the service requests from the Internet. The architecture employs an autonomous decentralized computing scheme for resource allocation. A subsystem has a production server to process service requests and a coordination server to adapt computing resource to load changes. Coordination is executed among subsystems to calculate how many resources are needed. Three system architectures, centralized resource allocation, autonomous decentralized resource allocation with independent adaptation and autonomous decentralized resource allocation with coordinated adaptation, are compared for tracking ability through simulation. Autonomous decentralized resource allocation with coordinated adaptation shows a good tracking ability comparable to the centralized resource allocation that should be nearly optimal. Since autonomous decentralized architecture shows better performance for availability than centralized architecture, autonomous decentralized allocation achieves the best performance for overall criteria.

[1]  Ian Foster,et al.  A quality of service architecture that combines resource reservation and application adaptation , 2000, 2000 Eighth International Workshop on Quality of Service. IWQoS 2000 (Cat. No.00EX400).

[2]  Kinji Mori,et al.  A method for solving trade-off among cost for owned/borrowed resource and loss of business chances , 2004, Eighth IEEE International Symposium on High Assurance Systems Engineering, 2004. Proceedings..

[3]  Virgílio A. F. Almeida Capacity Planning for Web Services , 2002, Performance.

[4]  Ian T. Foster,et al.  The Anatomy of the Grid: Enabling Scalable Virtual Organizations , 2001, Int. J. High Perform. Comput. Appl..

[5]  Ian T. Foster,et al.  SNAP: A Protocol for Negotiating Service Level Agreements and Coordinating Resource Management in Distributed Systems , 2002, JSSPP.

[6]  Kinji Mori,et al.  Autonomous decentralized systems: Concept, data field architecture and future trends , 1993, Proceedings ISAD 93: International Symposium on Autonomous Decentralized Systems.

[7]  Rajkumar Buyya,et al.  Economic-based Distributed Resource Management and Scheduling for Grid Computing , 2002, ArXiv.

[8]  Walker,et al.  Capacity Planning for Internet Services , 2001 .

[9]  Ian T. Foster,et al.  The Community Authorization Service: Status and Future , 2003, ArXiv.

[10]  Ian Foster,et al.  The Grid 2 - Blueprint for a New Computing Infrastructure, Second Edition , 1998, The Grid 2, 2nd Edition.

[11]  Thomas P. Brisco DNS Support for Load Balancing , 1995, RFC.

[12]  Kinji Mori,et al.  Scalable Multilateral Autonomous Decentralized Community Communication Technique for Large-Scale Information Systems , 2004 .

[13]  David Abramson,et al.  The Virtual Laboratory: a toolset to enable distributed molecular modelling for drug design on the World‐Wide Grid , 2003, Concurr. Comput. Pract. Exp..

[14]  David Abramson,et al.  Virtual Laboratory: Enabling On-Demand Drug Design with the World Wide Grid , 2001, ArXiv.

[15]  Ami Marowka,et al.  The GRID: Blueprint for a New Computing Infrastructure , 2000, Parallel Distributed Comput. Pract..

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