ABSTRACT
As computing systems evolve and mature, they are also expected to grow in size and complexity. With the continuing paradigm shift towards cloud computing, these systems have already reached the stage where the human effort required to maintain them at an operational level is unsupportable. Therefore, the development of appropriate mechanisms for run-time monitoring and adaptation is essential to prevent cloud platforms from quickly dissolving into a non-reliable environment. In this paper we present our approach to enable cloud application platforms with self-managing capabilities. The approach is based on a novel view of cloud platforms as networks of distributed data sources - sensors. Accordingly, we propose utilising techniques from the Sensor Web research community to address the challenge of monitoring and analysing continuously flowing data within cloud platforms in a timely manner.
- Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I. and Zaharia, M. 2009. Above the Clouds: A Berkeley View of Cloud Computing.Google Scholar
- Barbieri, D., Braga, D., Ceri, S., Della Valle, E. and Grossniklaus, M. 2010. Stream Reasoning: Where We Got So Far. Proceedings of the 4th International Workshop on New Forms of Reasoning for the Semantic Web: Scalable and Dynamic (NeFoRS) (2010).Google Scholar
- Blair, G.S., Coulson, G. and Grace, P. 2004. Research directions in reflective middleware: the Lancaster experience. Proceedings of the 3rd workshop on Adaptive and reflective middleware (New York, NY, USA, 2004), 262--267. Google ScholarDigital Library
- Botts, M., Percivall, G., Reed, C. and Davidson, J. 2008. OGC® sensor web enablement: Overview and high level architecture. GeoSensor networks. (2008), 175--190. Google ScholarDigital Library
- Brazier, F.M.T., Kephart, J.O., Van Dyke Parunak, H. and Huhns, M.N. 2009. Agents and Service-Oriented Computing for Autonomic Computing: A Research Agenda. IEEE Internet Computing. 13, 3 (Jun. 2009), 82--87. Google ScholarDigital Library
- Calbimonte, J.-P., Jeung, H., Corcho, O. and Aberer, K. 2012. Enabling Query Technologies for the Semantic Sensor Web. International Journal On Semantic Web and Information Systems. (to appear. 2012). Google ScholarDigital Library
- Compton, M. et al. 2012. The SSN ontology of the W3C semantic sensor network incubator group. Web Semantics: Science, Services and Agents on the World Wide Web. 17, 0 (Dec. 2012), 25--32. Google ScholarDigital Library
- Dautov, R., Paraskakis, I. and Kourtesis, D. 2012. An ontology-driven approach to self-management in cloud application platforms. Proceedings of the 7th South East European Doctoral Student Conference (DSC 2012) (Thessaloniki, Greece, 2012), 539--550.Google Scholar
- Della Valle, E. 2012. Challenges, Approaches, and Solutions in Stream Reasoning.Google Scholar
- Ganek, A.G. and Corbi, T.A. 2003. The dawning of the autonomic computing era. IBM Systems Journal. 42, 1 (2003), 5--18. Google ScholarDigital Library
- Gucola, G. and Margara, A. 2011. Processing Flows of Information: From Data Stream to Complex Event Processing. ACM Computing Surveys. (2011).Google Scholar
- Hitzler, P., Krötzsch, M. and Rudolph, S. 2009. Foundations of Semantic Web Technologies. CRC Press. Google ScholarDigital Library
- Horn, P. 2001. Autonomic Computing: IBM's Perspective on the State of Information Technology. Computing Systems. 15, Jan (2001), 1--40.Google Scholar
- Huebscher, M.C. and McCann, J.A. 2008. A survey of autonomic computing-degrees, models, and applications. ACM Comput. Surv. 40, 3 (2008), 1--28. Google ScholarDigital Library
- IBM 2012. Bringing Big Data to the Enterprise. http://www-01.ibm.com/software/data/bigdata.Google Scholar
- Kephart, J.O. and Walsh, W.E. 2004. An artificial intelligence perspective on autonomic computing policies. Fifth IEEE International Workshop on Policies for Distributed Systems and Networks, 2004. POLICY 2004. Proceedings (Jun. 2004), 3--12. Google ScholarDigital Library
- Le-Phuoc, D., Dao-Tran, M., Parreira, J.X. and Hauswirth, M. 2011. A native and adaptive approach for unified processing of linked streams and linked data. Proceedings of the 10th international conference on The semantic web - Volume Part I (Berlin, Heidelberg, 2011), 370--388. Google ScholarDigital Library
- Mell, P. and Grance, T. 2009. The NIST definition of cloud computing. National Institute of Standards and Technology. 53, 6 (2009), 50.Google Scholar
- Natis, Y.V., Knipp, E., Valdes, R., Cearley, D.W. and Sholler, D. 2009. Who's Who in Application Platforms for Cloud Computing: The Cloud Specialists. Gartner Research.Google Scholar
- Oreizy, P., Gorlick, M.M., Taylor, R.N., Heimhigner, D., Johnson, G., Medvidovic, N., Quilici, A., Rosenblum, D.S. and Wolf, A.L. 1999. An architecture-based approach to self-adaptive software. IEEE Intelligent Systems and their Applications. 14, 3 (Jun. 1999), 54--62. Google ScholarDigital Library
- Russell, S.J., Norvig, P., Canny, J.F., Malik, J.M. and Edwards, D.D. 1995. Artificial intelligence: a modern approach. Prentice hall Englewood Cliffs, NJ. Google ScholarDigital Library
- Sheth, A., Henson, C. and Sahoo, S.S. 2008. Semantic sensor web. Internet Computing, IEEE. 12, 4 (2008), 78--83. Google ScholarDigital Library
- Studer, R., Benjamins, V.R. and Fensel, D. 1998. Knowledge engineering: Principles and methods. Data & Knowledge Engineering. 25, 1--2 (Mar. 1998), 161--197. Google ScholarDigital Library
Index Terms
- Addressing self-management in cloud platforms: a semantic sensor web approach
Recommendations
Towards a framework for monitoring cloud application platforms as sensor networks
With the continued growth in software environments on cloud application platforms, self-management at the Platform-as-a-Service (PaaS) level has become a pressing concern, and the run-time monitoring, analysis and detection of critical situations are ...
A vision for monitoring cloud application platforms as sensor networks
CAC '13: Proceedings of the 2013 ACM Cloud and Autonomic Computing ConferenceAutonomic management of clouds has received a lot of attention by both academia and industry putting a lot of efforts into investigation of various solutions, even though the focus has been mainly on the IaaS level, while the PaaS level being less often ...
Comparison of Several Cloud Computing Platforms
ISISE '09: Proceedings of the 2009 Second International Symposium on Information Science and EngineeringCloud computing is the development of parallel computing, distributed computing and grid computing. It has been one of the most hot research topics. Now many corporations have involved in the cloud computing related techniques and many cloud computing ...
Comments