全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Merging Agents and Cloud Services in Industrial Applications

DOI: 10.1155/2014/124872

Full-Text   Cite this paper   Add to My Lib

Abstract:

A novel idea to combine agent technology and cloud computing for monitoring a plant floor system is presented. Cloud infrastructure has been leveraged as the main mechanism for hosting the data and processing needs of a modern industrial information system. The cloud offers unlimited storage and data processing in a near real-time fashion. This paper presents a software-as-a-service (SaaS) architecture for augmenting industrial plant-floor reporting capabilities. This reporting capability has been architected using networked agents, worker roles, and scripts for building a scalable data pipeline and analytics system. 1. Introduction Industrial automation has come a long way from the early days of electromechanical systems to the distributed, modular, and intelligent control of applications that we have today where the automation controllers feature multicore processors, rich set of capabilities, and so forth, pushing the envelope. Improvements on the hardware and features are not enough as the increasing complexity of applications and information require a different paradigm, one that promotes the collaboration of distributed autonomous agent platforms. It is believed that agents will provide the foundation for a collaborative approach to a supervisory control layer with autonomous capabilities and access to vast amounts of information with higher-order responsible in the decision making layers of the automation enterprise [1, 2]. Agents are triggered when an event that requires complex computation occurs in the physical world. Agents have to do with business intelligence rules and a mix of device- and system-level information. Now that data can be stored in the so called big data storage, how to merge the agent capabilities with the cloud in a harmonious information processing system is one of the challenges of this work. A lot of research has been conducted in agent-based cloud computing applications [3, 4]. A self-organized agent-based service composition framework is discussed which uses agent-based problem solving techniques such as acquaintance networks and contract net protocol [5]. This method can be used in scenarios involving incomplete information about cloud participants. The solution described in this paper also leverages the contract net protocol to solve multiagent event handling tasks. In [6] a multiagent model for social media service based on intelligence virtualization rules is discussed. Intelligence multiagent for resource virtualization (IMAV) manages cloud computing resources in real-time and adjusts the resources according to

References

[1]  F. P. Maturana, R. J. Staron, D. L. Carnahan, and K. A. Loparo, “Distributed control concepts for future power grids,” in Proceedings of the IEEE Energytech, pp. 1–6, Cleveland, Ohio, USA, 2013.
[2]  F. P. Maturana, R. J. Staron, D. L. Carnahan, and K. A. Loparo, “Agent-based test bed simulator for powergrid modeling and control,” IEEE Energytech, 2012.
[3]  W. Xu, B. Wang, and J. Huang, “Cloud computing and its key techniques,” in Proceedings of the IEEE International Conference on Computer Science and Automation Engineering (CSAE '11), pp. 404–410, Shanghai, China, June 2011.
[4]  P. Patel, A. Ranabahu, and A. Sheth, “Service level agreement in cloud computing,” http://corescholar.libraries.wright.edu/.
[5]  S. Hamza, K. Okba, and B. Aicha-Nabila, “A new cloud computing framework based on mobile agents for web services discovery and selection,” in Proceedings of the 13th International Arab Conference on Information Technology, 2012.
[6]  M. Kim, H. Lee, H. Yoon, J. I. Kim, and H. S. Kim, IMAV: An Intelligent Multi-Agent Model Based on Cloud Computing for Resource Virtualization, International Association of Computer Science and Information Technology (IACSIT), 2013.
[7]  J. O. Gutierrez-Garcia and K.-M. Sim, “Self-organizing agents for service composition in cloud computing,” in Proceedings of the 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom '10), pp. 59–66, Indianapolis, Ind, USA, November-December 2010.
[8]  “Data Management: Rockwell Factory Historian,” Rockwell Automation, 2013, http://www.rockwellautomation.com/rockwellsoftware/data/historian/overview.page.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133