Abstract
In order to process task stream, a distributed computing platform was put forward. The hardware of the platform includes one control terminal, multi computing nodes, one storage array and one fiber optic switch. The software of the platform includes DBMS, control software and tasks. The transaction process of the platform includes n (n ≥ 1) tasks, and each task belongs to a specific level. There are data dependences among the tasks, namely that the output data of the previous task is the input data of the following task. The transaction starts from the first level task, and then to the second, the third, …, at last to the nth level task. After the nth level task finished and output result data, the transaction comes to the end. The platform is applicable to the science computing that is characterized by a task stream composed of multi tasks, such as remote sensing data processing and complex electromagnetism analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Zhang, X., Li, H., Liu, Y.: The Research of Optimal Algorithm for Task Scheduling Underground Wireless Network Based on Distributed Computing. In: 2010 International Conference on Manufacturing Automation (ICMA), Hong Kong, pp. 151–155 (2010)
Jakovits, P., Srirama, S.N., Kromonov, I.: Stratus: A Distributed Computing Framework for Scientific Simulations on the Cloud. In: IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems (HPCC-ICESS), Liverpool, pp. 1053–1059 (2012)
Xu, G., Lu, F., Yu, H., Xu, Z.: A Distributed Parallel Computing Environment for Bioinformatics Problems. In: Sixth International Conference on Grid and Cooperative Computing, Los Alamitos, CA, pp. 593–599 (2007)
Hawick, K.A., James, H.A., Maciunas, K.J., et al.: Geostationary-Satellite Imagery Applications on Distributed, High-Performance Computing. In: High Performance Computing on the Information Superhighway, Seoul, pp. 50–55 (1997)
Hifi, M., Saadi, T., Haddadou, N.: High Performance Peer-to-Peer Distributed Computing with Application to Constrained Two-Dimensional Guillotine Cutting Problem. In: 19th Euromicro International Conference on Parallel, Distributed and Network-Based Processing, Ayia Napa, pp. 552–559 (2011)
Liu, H., Sorensen, S.-A., Nazir, A.: On-Line Automatic Resource Selection in Distributed Computing. In: IEEE International Conference on Cluster Computing and Workshops, New Orleans, LA, pp. 1–9 (2009)
Souza Ramos, D., Watershed, T.L.A.: Watershed: A High Performance Distributed Stream Processing System. In: 23rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Vitoria, Espirito Santo, pp. 191–198 (2011)
Chen, L., Agrawal, G.: Self-Adaptation in a Middleware for Processing Data Streams. In: 2004 International Conference on Autonomic Computing, pp. 292–293 (2004)
Slawinska, M., Slawinski, J., Sunderam, V.: Unibus: Aspects of Heterogeneity and Fault Tolerance in Cloud Computing. In: 2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and PhD Forum (IPDPSW), Atlanta, GA, pp. 1–10 (2010)
Obaidat, M.S., Bedi, H., Bhandari, A., Bosco, M.S.D.: Design and Implementation of a Fault Tolerant Multiple Master Cloud Computing System. In: 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing (iThings/CPSCom), Dalian, pp. 82–88 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Weiyan, X., Wenqing, H., Dong, L., Youyi, D. (2013). A Distributed Computing Platform for Task Stream Processing. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-53932-9_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-53931-2
Online ISBN: 978-3-642-53932-9
eBook Packages: Computer ScienceComputer Science (R0)