Cart (Loading....) | Create Account
Close category search window
 

DPAC: an object-oriented distributed and parallel computing framework for manufacturing applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Srinivasa Raghavan, N.R. ; Manage. Studies, Indian Inst. of Sci., Bangalore, India ; Waghmare, T.

Parallel and distributed computing infrastructures are increasingly being embraced in the context of manufacturing applications, including real-time scheduling. We present the design and implementation of one such framework that can work on the Internet, with applications in manufacturing. The architecture, DPAC (distributed and parallel computing framework), has the goal of harnessing the Internet's vast, growing computational capacity for ultra-large, coarse-grained parallel applications. The idea is to bring together diverse, heterogeneous, geographically distributed computing environments in order to attack large-scale computing problems. We present a scalable and fault-tolerant architecture in DPAC and the results of running performance experiments. DPAC is implemented on the interoperable, increasingly secure, and ubiquitous platform Java. The unique feature of DPAC is that it frees application developers from concerns about complex interprocess communication and fault tolerance among Internet-worked hosts and supports piecework and branch-and-bound computational models. We describe an implementation and present case studies showing the effectiveness in solving complex combinatorial optimization problems in the context of manufacturing systems.

Published in:

Robotics and Automation, IEEE Transactions on  (Volume:18 ,  Issue: 4 )

Date of Publication:

Aug 2002

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.