Device Resource Monitoring System in Wireless Grids
ACT '09 Proceedings of the 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies
Scalable Run-Time Correlation Engine for Monitoring in a Cloud Computing Environment
ECBS '10 Proceedings of the 2010 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
P&P: A Combined Push-Pull Model for Resource Monitoring in Cloud Computing Environment
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Establishing Trust in Cloud Computing
IT Professional
Markov Chain Based Monitoring Service for Fault Tolerance in Mobile Cloud Computing
WAINA '11 Proceedings of the 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications
State Monitoring in Cloud Datacenters
IEEE Transactions on Knowledge and Data Engineering
A Novel Approach to QoS Monitoring in the Cloud
CCP '11 Proceedings of the 2011 First International Conference on Data Compression, Communications and Processing
Establishing Trust in Hybrid Cloud Computing Environments
TRUSTCOM '11 Proceedings of the 2011IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications
CloudSense: continuous fine-grain cloud monitoring with compressive sensing
HotCloud'11 Proceedings of the 3rd USENIX conference on Hot topics in cloud computing
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In the current cloud computing scenario, the need for establishing an SLA is essential. There is an even stronger necessity for monitoring whether the QoS mentioned in the SLA is met by the service provider. The next big issue is the trust on the service provider. Even though the providers pledge to meet the agreed upon QoS, there is a desideratum for a trust model which will give a quantitative measure of the trust to the requester before choosing a service provider. In this paper, we portray a novel approach which will monitor the QoS, negating the drawbacks associated with the existing techniques. The amount of monitoring data sent over the network is reduced by employing a derived and state monitoring approach. Based on the monitoring results, trust is established dynamically by making use of the Markov Chain model. The proposed approach is implemented using a web based system which will elucidate its use in real time. We believe that our dynamic trust establishment technique will be munificent in supporting the way trust management will be viewed in future.