Multi-level Elasticity Control of Cloud Services

Fine-grained elasticity control of cloud services has to deal with multiple elasticity perspectives quality, cost, and resources. We propose a cloud services elasticity control mechanism that considers the service structure for controlling the cloud service elasticity at multiple levels, by firstly defining an abstract composition model for cloud services and enabling multi-level elasticity control. Secondly, we define mechanisms for solving conflicting elasticity requirements and generating action plans for elasticity control. Using the defined concepts and mechanisms we develop a runtime system supporting multiple levels of elasticity control and validate the resulted prototype through experiments.

[1]  Zhenhuan Gong,et al.  PRESS: PRedictive Elastic ReSource Scaling for cloud systems , 2010, 2010 International Conference on Network and Service Management.

[2]  Daniel Moldovan,et al.  SYBL: An Extensible Language for Controlling Elasticity in Cloud Applications , 2013, 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing.

[3]  Schahram Dustdar,et al.  Design by Units: Abstractions for Human and Compute Resources for Elastic Systems , 2012, IEEE Internet Computing.

[4]  Adam Silberstein,et al.  Benchmarking cloud serving systems with YCSB , 2010, SoCC '10.

[5]  Yike Guo,et al.  Principles of Elastic Processes , 2011, IEEE Internet Computing.

[6]  Andreas Menychtas,et al.  ElaaS: An Innovative Elasticity as a Service Framework for Dynamic Management across the Cloud Stack Layers , 2012, 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems.

[7]  Xiaohui Gu,et al.  CloudScale: elastic resource scaling for multi-tenant cloud systems , 2011, SoCC.

[8]  Raman Kazhamiakin,et al.  Adaptation of Service-Based Applications Based on Process Quality Factor Analysis , 2009, ICSOC/ServiceWave Workshops.

[9]  Surajit Chaudhuri,et al.  Proceedings of the 11th ACM Symposium on Cloud Computing , 2010 .

[10]  Annapaola Marconi,et al.  Multi-layered Monitoring and Adaptation , 2011, ICSOC.

[11]  Jie Yang,et al.  A Profile-Based Approach to Just-in-Time Scalability for Cloud Applications , 2009, 2009 IEEE International Conference on Cloud Computing.

[12]  Wolfgang Rosenstiel,et al.  Proceedings of the 8th ACM international conference on Autonomic computing , 2011, ICAC 2011.

[13]  Calton Pu,et al.  Automated control for elastic n-tier workloads based on empirical modeling , 2011, ICAC '11.

[14]  Jin Tong,et al.  NIST Cloud Computing Reference Architecture , 2011, 2011 IEEE World Congress on Services.

[15]  Ioannis Konstantinou,et al.  Automated, Elastic Resource Provisioning for NoSQL Clusters Using TIRAMOLA , 2013, 2013 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing.

[16]  Calton Pu,et al.  The Impact of Soft Resource Allocation on n-Tier Application Scalability , 2011, 2011 IEEE International Parallel & Distributed Processing Symposium.