Abstract
Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well as infrastructure. A cloud is the type of a parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a cloud require adaptive service-based software, which has the capability of monitoring the system status change, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize resources on cloud computing. RTM monitors application software through library instrumentation as well as underlying hardware through performance counter optimizing its computing configuration based on the analyzed data.
This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) support program supervised by the NIPA (National IT Industry Promotion Agency (NIPA-2010-C1090-1011-0009)) and OPERA Software Architecture Project.
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.
References
Feng, W., Balaji, P.: Tools and Environments for Multicore and Many-Core Architectures. IEEE Computer 42(12), 26–27 (2009)
Schneider, S., Yeom, J., Nikolopoulous, D.: Programming Multiprocessors with Explicitly Managed Memory Hierarchies. IEEE Computer 42(12), 28–34 (2009)
Multi-core processor (2009), http://en.wikipedia.org/wiki/Multi-core_processor
Bell, S., Edwards, B., Amann, J., Conlin, R., Joyce, K., Leung, V., MacKay, J., Reif, M., Bao, L., Brown, J., Mattina, M., Miao, C.-C., Ramey, C., Wentzlaff, D., Anderson, W., Berger, E., Fairbanks, N., Khan, D., Montenegro, F., Stickney, J., Zook, J.: TILE64 Processor: A 64-Core SoC with Mesh Interconnect. In: Proc. IEEE International Solid-State Circuits Conference (ISSCC), pp. 88–98 (2008)
Tilera Corporation (2010), http://www.tilera.com/
Peng, J., Zhang, X., Lei, Z., Zhang, B., Zhang, W., Li, Q.: Comparison of Several Cloud Computing Platforms. In: International Symposium on Information Science and Engineering, pp. 23–27 (2009)
Hill, Z., Humphrey, M.: A Quantitative Analysis of High Performance Computing with Amazon’s EC2 Infrastructure: The Death of the Local Cluster? In: 10th IEEE/ACM International Conference on Grid Computing, pp. 26–33 (2009)
Chiba, T., Burger, M., Kielmann, T., Matsuoka, S.: Dynamic Load-Balanced Multicast for Data-Intensive Applications on Clouds. In: 10th IEEE/ACM International Conference on Cluster, Cloud, and Grid Computing, pp. 5–14 (2010)
Message Passing Interface Forum, MPI: A Message Passing Interface Standard (2009), http://www.mpi-forum.org/docs/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kang, M., Kang, DI., Yun, M., Park, GL., Lee, J. (2010). Design for Run-Time Monitor on Cloud Computing. In: Kim, Th., Stoica, A., Chang, RS. (eds) Security-Enriched Urban Computing and Smart Grid. SUComS 2010. Communications in Computer and Information Science, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16444-6_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-16444-6_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16443-9
Online ISBN: 978-3-642-16444-6
eBook Packages: Computer ScienceComputer Science (R0)