Using object-oriented constraint satisfaction for automated configuration generation

7Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

In this paper, we describe an approach for automatically generating configurations for complex applications. Automated generation of system configurations is required to allow large-scale deployment of custom applications within utility computing environments. Our approach models the configuration management problem as an Object-Oriented Constraint Satisfaction Problem (OOCSP) that can be solved efficiently using a resolution-based theoremprover. We outline the approach and discuss both the benefits of the approach as well as its limitations, and highlight certain unresolved issues that require further work. We demonstrate the viability of this approach using an eCommerce site as an example, and provide results on the complexity and time required to solve for the configuration of such an application. © IFIP International Federation for Information Processing 2004.

References Powered by Scopus

A Machine-Oriented Logic Based on the Resolution Principle

2450Citations
N/AReaders
Get full text

Automated generation of resource configurations through policies

19Citations
N/AReaders
Get full text

On the design of constraint satisfaction problems

3Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Automatic generation of AMF compliant configurations

13Citations
N/AReaders
Get full text

A model driven approach for AMF configuration generation

11Citations
N/AReaders
Get full text

Automatic configuration generation for service high availability with load balancing

6Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Hinrich, T., Love, N., Petrie, C., Ramshaw, L., Sahai, A., & Singhal, S. (2004). Using object-oriented constraint satisfaction for automated configuration generation. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3278, 159–170. https://doi.org/10.1007/978-3-540-30184-4_14

Readers over time

‘09‘10‘12‘13‘15‘2002468

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 7

100%

Readers' Discipline

Tooltip

Computer Science 7

100%

Save time finding and organizing research with Mendeley

Sign up for free
0