QoS monitoring and dynamic trust establishment in the cloud
GPC'12 Proceedings of the 7th international conference on Advances in Grid and Pervasive Computing
Stream-based event prediction using bayesian and bloom filters
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
Security event correlation approach for cloud computing
International Journal of High Performance Computing and Networking
High volumes of event stream indexing and efficient multi-keyword searching for cloud monitoring
Future Generation Computer Systems
Scalable Monitoring System for Clouds
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Monitoring the status of running applications is a real life requirement and important research area. In particular log analysis is often required to understand how the system is behaving during execution. For example it is common for system administrators to collect and view logs from different hardware and software components to gain an understanding into system behavior, especially during activities such as problem determination. A recent research project in this area, the Run Time Correlation Engine (RTCE), provides a framework for run-time correlation of distributed log files in a scalable manner for enterprise applications. The framework has been designed for enterprise applications consisting of distributed software components and is in use in real industry environments. The purpose of this paper is to explore how the RTCE can scale for cloud computing environments where providers of cloud services will require large architectures (e.g. data centers) to deploy such services.