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ABSTRACT: With recent increasing computational and data requirements of scientific
applications, the use of large clustered systems as well as distributed
resources is inevitable. Although executing large applications in these
environments brings increased performance, the automation of the process
becomes more and more challenging. While the use of complex workflow management
systems has been a viable solution for this automation process in business
oriented environments, the open source engines available for scientific
applications lack some functionalities or are too difficult to use for
non-specialists. In this work we propose an architectural model for a grid
based workflow management platform providing features like an intuitive way to
describe workflows, efficient data handling mechanisms and flexible fault
tolerance support. Our integrated solution introduces a workflow engine
component based on ActiveBPEL extended with additional functionalities and a
scheduling component providing efficient mapping between tasks and available
resources.
06/2011;
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ABSTRACT: 17th International Conference on Control Systems and Computer Science (CSCS
17), Bucharest, Romania, May 26-29, 2009. Vol. 1, pp. 401-406, ISSN: 2066-4451.
06/2011;
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International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, June 30 - July 2, 2011, Korean Bible University, Seoul, Korea; 01/2011
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12th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2010, Timisoara, Romania, 23-26 September 2010; 01/2010
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CISIS 2010, The Fourth International Conference on Complex, Intelligent and Software Intensive Systems, Krakow, Poland, 15-18 February 2010; 01/2010
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NTMS 2009, 3rd International Conference on New Technologies, Mobility and Security, 20-23 December 2009, Cairo, Egypt; 01/2009
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ABSTRACT: This paper presents an efficient agent based DAG scheduling system. The proposed system has a decentralized architecture.
It is able to manage tasks with dependencies, and bases its decisions on Grid resources’ status captured dynamically and used
at schedule time. Fault tolerance mechanisms can also be easily implemented, providing a great degree of certainty that the
schedule results will be correct and delivered before the imposed deadline. The system has been integrated and tested with
MonAlisa farms and the ApMon, which is a MonAlisa extension. The results obtained so far in the performed experiments show
that the system introduces a reasonable overhead while producing higher quality mappings than the centralized ones.
12/2007: pages 129-139;
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OTM'07: Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems, Berlin, Heidelberg; 01/2007
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Fifth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing.
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ABSTRACT: Recently there has been a great need to provide an adequate security level in Cloud Environments, as they are vulnerable to various attacks. Malicious behaviors such as Denial of Service attacks, especially when targeting large-scale data management systems, cannot be detected by typical authentication mechanisms and are responsible for drastically degrading the overall performance of such systems. In this paper we propose a generic security management framework allowing providers of Cloud data management systems to define and enforce complex security policies. This security framework is designed to detect and stop a large array of attacks defined through an expressive policy description language and to be easily interfaced with various data management systems. We show that we can efficiently protect a data storage system, by evaluating our security framework on top of the BlobSeer data management platform. We evaluate the benefits of preventing a DoS attack targeted towards BlobSeer through experiments performed on the Grid'5000 testbed.
The 25th International Conference on Advanced Information Networking and Applications (AINA-2011).