An architecture to evaluate Scalability, Adaptability and Accuracy in cloud monitoring systems

In a cloud computing environment, multiple resources need to be properly managed to improve resource utilization and offer predictable performance to customers. One essential management function that gains a special importance in the context of clouds is monitoring. Nowadays, cloud monitoring solutions need to meet several requirements such as Scalability, Accuracy, and Adaptability. In This paper, we proposed an architecture to evaluate Scalability, Accuracy, and Adaptability in cloud monitoring systems based on local filters. The results show a mutual influence among these requirements. Moreover, the proposed architecture is simplified and the filtering methods show promising results to Scalability and Adaptability.

[1]  José Luis Vázquez-Poletti,et al.  Provisioning data analytic workloads in a cloud , 2013, Future Gener. Comput. Syst..

[2]  J. Ticehurst.  Cacti , 1983 .

[3]  William Stallings,et al.  SNMP, SNMPv2, SNMPv3, and RMON 1 and 2 , 1999 .

[4]  Raouf Boutaba,et al.  Cloud computing: state-of-the-art and research challenges , 2010, Journal of Internet Services and Applications.

[5]  Jesús Montes,et al.  GMonE: A complete approach to cloud monitoring , 2013, Future Gener. Comput. Syst..

[6]  Christine Morin,et al.  Snooze: A Scalable and Autonomic Virtual Machine Management Framework for Private Clouds , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[7]  Vanish Talwar,et al.  A flexible architecture integrating monitoring and analytics for managing large-scale data centers , 2011, ICAC '11.

[8]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[9]  David H. Bailey,et al.  The NAS parallel benchmarks summary and preliminary results , 1991, Proceedings of the 1991 ACM/IEEE Conference on Supercomputing (Supercomputing '91).

[10]  Marty Humphrey,et al.  A quantitative analysis of high performance computing with Amazon's EC2 infrastructure: The death of the local cluster? , 2009, 2009 10th IEEE/ACM International Conference on Grid Computing.

[11]  Randy H. Katz,et al.  A view of cloud computing , 2010, CACM.

[12]  Carlos Becker Westphall,et al.  Toward an architecture for monitoring private clouds , 2011, IEEE Communications Magazine.

[13]  George Pavlou,et al.  Monitoring, aggregation and filtering for efficient management of virtual networks , 2011, 2011 7th International Conference on Network and Service Management.

[14]  Nico d'Heureuse,et al.  Towards holistic multi-tenant monitoring for virtual data centers , 2010, 2010 IEEE/IFIP Network Operations and Management Symposium Workshops.

[15]  Benny Rochwerger,et al.  Monitoring Service Clouds in the Future Internet , 2010, Future Internet Assembly.

[16]  Alexandru Iosup,et al.  A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing , 2009, CloudComp.

[17]  Antonio Pescapè,et al.  Cloud monitoring: A survey , 2013, Comput. Networks.

[18]  Vanish Talwar,et al.  Monalytics: online monitoring and analytics for managing large scale data centers , 2010, ICAC '10.

[19]  Alessandro Bassi,et al.  Management Architecture and Systems for Future Internet Networks , 2009, Future Internet Assembly.

[20]  Lisandro Zambenedetti Granville,et al.  Network and Services Monitoring: A Survey in Cloud Computing Environments , 2012, ICON 2012.