Object Management in Local Distributed Systems

Abstract

Resource management is a central issue in operating systems design; it is even more critical in distributed systems, because of the physical distribution of the resources, and thus the natural redundancy and the possibility of partial failures. In this paper, we study the resource management and sharing problems in distributed systems. After setting up a model for resource management that enables us to study and compare the different approaches, we survey the existing distributed systems and attempt to taxonomize the research results so far. Based on this investigation, we propose a new approach to resource management, which we call global object management. A logically centralized system-wide manager acts as a coordinator between different parts of the system, and is responsible for managing the top level, sharable resources in the distributed environment and making them available to the users. We argue that this approach greatly enhances system resource sharing by combining the semantic simplicity of centralized management and the reliability and availability of distributed management, and offers a number of advantages over the existing techniques.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1985
Accession Number
ADA611777

Entities

People

  • Roberto Zicari
  • Songnian Zhou

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Availability
  • California
  • Computer Networks
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Computing System Architectures
  • Engineering
  • Environment
  • Local Area Networks
  • Operating Systems
  • Reliability
  • Resource Management
  • Servers (Computer Hardware)
  • Systems Engineering

Fields of Study

  • Computer science
  • Engineering

Readers

  • Organizational Process Management (OPM).
  • Parallel and Distributed Computing.