The simulation of decentralized control: a hostless resource allocation model

In this article, an alternative approach to control for computing systems, with possible distributed, parallel, or multilprocess application, is proposed and evaluated through simulation. Functions normally handled by centralized controllers, schedulers, arbiters and priority schemes are accomplished through a decentral ized model of control. Resource allocation, one important control function, is resolved within a Challenge Ring (CR) in which individual computing tasks independently (or without a host, hence their interaction is called hostless) exercise algorithms to gain access to computing resources. Simulated system performance is monitored by analyzing individual task processing times, total system times, resource availability, resource utilization, and system efficiency. Our preliminary experimental results indicate that such decentralized (or hostless) models can be superior to some standard centralized (or hosted) versions. Moreover, tasks in CR networks that interact through cooperative strategies in some cases exhibit better performance. Our overall results encourage the further exploration of decentralized control models which could be useful in the continuing pursuit of alternative machine constructs (e.g. non-von Neumann architectures) and new distributed operational schemes (e.g. hostless network operating systems).

[1]  M M Waldrop,et al.  PARC Brings Adam Smith to Computing: Part computer virus and part market theory, Spawn is both an efficiency tool and a laboratory for experimental economics. , 1989, Science.

[2]  W. Randolph Franklin On an improved algorithm for decentralized extrema finding in circular configurations of processors , 1982, CACM.

[3]  Larry Rudolph,et al.  Distributed hierarchical control for parallel processing , 1990, Computer.

[4]  Ross A. Gagliano,et al.  Simulation of a market model for distributed control , 1988, ANSS '88.

[5]  Ross A. Gagliano,et al.  Modeling the cost of resource allocation in distributed control , 1990, ANSS '90.

[6]  Andrew S. Tanenbaum,et al.  Structured Computer Organization , 1976 .

[7]  M R Railey Dynamic control structures for cooperating processes , 1986 .

[8]  Allan L. Scherr Distributed Data Processing , 1978, IBM Syst. J..

[9]  Haim Mendelson,et al.  Pricing computer services: queueing effects , 1985, CACM.

[10]  Ross A. Gagliano,et al.  The simulation of a distributed control model for resource allocation and the implied pricing , 1989, ANSS '89.

[11]  Ross A. Gagliano,et al.  Mathematical modeling and Ada simulation of some synchronization processes , 1987, ANSS '87.

[12]  Philip H. Enslow What is a "Distributed" Data Processing System? , 1978, Computer.

[13]  Paul M. B. Vitányi Distributed elections in an archimedean ring of processors , 1984, STOC '84.

[14]  DuncanRalph A Survey of Parallel Computer Architectures , 1990 .

[15]  Judy Kay,et al.  A fair share scheduler , 1988, CACM.

[16]  Mahadev Satyanarayanan,et al.  Scalable, secure, and highly available distributed file access , 1990, Computer.