Self-adaptive large-scale SCADA system based on self-organised multi-agent systems
by Hosny A. Abbas; Samir I. Shaheen; Mohammed H. Amin
International Journal of Automation and Control (IJAAC), Vol. 10, No. 3, 2016

Abstract: This paper provides an approach for engineering present and future large-scale supervisory control and data acquisition (SCADA) systems as a type of complex industrial networks, which are characterised by their increasing complexity and high distribution. The proposed approach adopts the emerging agent technology, which has proven to be the most representative among artificial systems dealing with complexity and high distribution. Agent-based systems that have the ability to dynamically reorganise themselves will be adaptive enough to survive within their unpredictable and highly changing environments. Adaptive agent-based systems are designed to be capable to adapt themselves to unforeseen situations in an autonomous manner. Engineering modern complex, highly distributed, and large-scale SCADA systems is currently a challenging issue and agents and multi-agent systems (MAS) can provide a feasible solution to this problem. In this paper, a self-adaptive large-scale SCADA system is designed and implemented based on dynamically organised adaptive MAS. A prototype was developed and evaluated within a simulation environment for demonstrating the effect of the transparently realised dynamic reorganisation on the system-to-be performance.

Online publication date: Wed, 06-Jul-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Automation and Control (IJAAC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com