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Morariu O.,Polytechnic University of Bucharest | Morariu C.,Cloud Troopers Intl | Borangiu T.,Polytechnic University of Bucharest
Studies in Computational Intelligence | Year: 2014

Service orientation of holonic manufacturing systems represents a major milestone in increasing efficiency, flexibility and standardization for manufacturing enterprises. SOA governance assures the capability for dynamic composition of services at runtime without human intervention, allowing the system to automatically align itself to the business drivers. In this context there is a need for accurate and real time monitoring of the shop floor activities during the manufacturing process. This paper presents a shop floor monitoring solution based on distributed multi-agent system architecture capable of real time data collection and presentation for production tracking. The solution provides a monitoring portal where system administrators can track key performance indicators in real time. The paper discusses the strategies for handing the monitoring data in real time and also long term, focusing on the consolidation of information in persistent data structures. © 2014 Springer International Publishing Switzerland.

Morariu O.,Polytechnic University of Bucharest | Morariu C.,Cloud Troopers Intl
UPB Scientific Bulletin, Series C: Electrical Engineering | Year: 2015

Guidance vision is applied as an advanced motion control method, which provides flexibility when integrating robots in intelligent manufacturing cells with unstructured environment the paper develops a methodology for on-line implementing vision-based robot control strategies that use robot-object models a priori learned, and are on-line checked for collision-free grasping based on the models of the gripper's fingerprints. Experiments have been carried out on a development platform using a Cobra s850 SCARA robot with compact Adept controller and vision extension.

Morariu O.,Polytechnic University of Bucharest | Borangiu T.,Polytechnic University of Bucharest | Morariu C.,Cloud Troopers Intl
Proceedings - International Workshop on Database and Expert Systems Applications, DEXA | Year: 2013

Cloud computing represents at this point the standard delivery method for the infrastructure and platform of next generation applications. The emergence of a wide range of commercial cloud services have changed not only the way code is written and maintained, but also the way it is executed. Private clouds play an important role in this new service delivery model being designed to provide computing capacity within the organization premises either standalone or in a hybrid model. As resources of the private cloud are limited, QoS assurance becomes an important challenge. This paper presents the design of a monitoring solution that integrates several open source tools and can assure QoS for private clouds. The solution is implemented for IBM CloudBurst 2.1 and IBM TSAM product stack and can monitor a wide range of services, from CPU and memory load to J2EE services and HTTP statistics generate real time alerts and provide integration with a Jira based issue tracking tools. The overall solution provides a closed loop QoS system for private clouds that is able to prevent a large set of issues and provide real time diagnostic data for root cause analysis. © 2013 IEEE.

Morariu O.,Polytechnic University of Bucharest | Morariu C.,Cloud Troopers Intl | Borangiu T.,Polytechnic University of Bucharest
UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science | Year: 2014

The large scale emergence of cloud platforms induce the tendency to virtualize application workloads that traditionally ran on physical machines. At the same time, cloud providers advertise unlimited resources available to the customers at any time for a fixed price. These factors create the opportunity for customers to easily scale up and down the infrastructure depending on the real time requirements, reducing the overall costs for providing the service. Cloud platforms today provide a threshold trigger mechanism that can trigger provisioning or de-provisioning of additional resources. This paper argues that the threshold approach is not enough for some real life application scaling requirements and introduces a predictive mechanism that allows accurate and proactive provisioning of workloads. The prediction algorithm is based on the observation that for some applications a usage pattern exists, and this usage pattern is repetitive. This paper presents the usage pattern identified in a large scale travel booking application and the execution of the algorithm on this data. The algorithm tested using IBM CloudBurst 2.1 deployment using a benchmark application and results are discussed.

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