Communications of the ACM
A method for obtaining digital signatures and public-key cryptosystems
Communications of the ACM
E-Commerce Trust Metrics and Models
IEEE Internet Computing
Automated SLA Monitoring for Web Services
DSOM '02 Proceedings of the 13th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Management Technologies for E-Commerce and E-Business Applications
Compute Power Market: Towards a Market-Oriented Grid
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
Self-Adaptive and Self-Optimising Resource Monitoring for Dynamic Grid Environments
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Short Signatures from the Weil Pairing
Journal of Cryptology
Towards Competitive Web Service Market
FTDCS '07 Proceedings of the 11th IEEE International Workshop on Future Trends of Distributed Computing Systems
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
Dominant Factors for Online Trust
CW '08 Proceedings of the 2008 International Conference on Cyberworlds
Scalable middleware environment for agent-based internet applications
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Self-adaptive service level agreement monitoring in cloud environments
Multiagent and Grid Systems
Hi-index | 0.00 |
Online marketplaces are emerging in which services are provided and consumed. Parties make online agreements regarding the terms and conditions of service provisioning. For certain kinds of services, it may be necessary to know whether it is being provisioned according to the agreement. To this end, the service may be monitored. For instance, a web application service may be monitored to guarantee that the response time of the application is within acceptable limits. The decision of whether or not to monitor a service is correlated to the perceived level of risk that a violation will occur. If there is a low level of perceived risk, monitoring may not be required, and vice versa. The perceived level of risk associated with a service transaction can change over time. However, traditional monitoring techniques are not able to react to this change. This paper proposes a self-adaptive service monitor that adapts to changes in the perceived level of risk. This monitor combines a traditional service monitor with a self-monitoring protocol, referred to as passive monitoring. This monitor is implemented in the AgentScape Middleware.