Performance-Efficient Service Deployment and Scheduling Methods for Composite Cloud Services

Cloud computing and services have greatly changed the way how people develop and use software, and also raised a lot of new research issues. In this paper, we investigate two such important issues, service deployment and service request scheduling, for composite cloud services in dynamic cloud environments. We present load-aware service deployment approaches for dynamic workload and a service request scheduling method based on task ranking mechanisms. The proposed approaches can effectively improve the execution efficiency of composite cloud services in dynamic cloud environments. A wide range of simulation experiments have been conducted to evaluate the proposed approaches. The experimental results show that our approaches outperform the previous methods in the literature significantly in terms of average service response time.

[1]  Yinong Chen,et al.  Service-Oriented Computing and Web Software Integration: From Principles to Development , 2011 .

[2]  Radu Prodan,et al.  Taxonomies of the Multi-Criteria Grid Workflow Scheduling Problem , 2008 .

[3]  Yogesh L. Simmhan,et al.  Reactive Resource Provisioning Heuristics for Dynamic Dataflows on Cloud Infrastructure , 2015, IEEE Transactions on Cloud Computing.

[4]  Filip De Turck,et al.  Graph partitioning algorithms for optimizing software deployment in mobile cloud computing , 2013, Future Gener. Comput. Syst..

[5]  Andrzej Kochut,et al.  Dynamic Placement of Virtual Machines for Managing SLA Violations , 2007, 2007 10th IFIP/IEEE International Symposium on Integrated Network Management.

[6]  Nguyen Hong Son,et al.  Load balancing algorithm based on estimating finish time of services in cloud computing , 2016, 2016 18th International Conference on Advanced Communication Technology (ICACT).

[7]  S. Padmavathi,et al.  Dynamic Resource Allocation Scheme in Cloud Computing , 2015 .

[8]  Kuo-Chan Huang,et al.  Service deployment strategies for efficient execution of composite SaaS applications on cloud platform , 2015, J. Syst. Softw..

[9]  Yinong Chen,et al.  Service-Oriented Computing and Software Integration in Computing Curriculum , 2014, 2014 IEEE International Parallel & Distributed Processing Symposium Workshops.

[10]  Meng Wang,et al.  Consolidating virtual machines with dynamic bandwidth demand in data centers , 2011, 2011 Proceedings IEEE INFOCOM.

[11]  Bernd Freisleben,et al.  Multi-objective Scheduling of BPEL Workflows in Geographically Distributed Clouds , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[12]  Quanwang Wu,et al.  Broker-based SLA-aware composite service provisioning , 2014, J. Syst. Softw..

[13]  Kuo-Chan Huang,et al.  Revenue maximisation for scheduling deadline-constrained mouldable jobs on high performance computing as a service platforms , 2018, Int. J. High Perform. Comput. Netw..

[14]  Maolin Tang,et al.  Composite SaaS Placement and Resource Optimization in Cloud Computing Using Evolutionary Algorithms , 2012, 2012 IEEE Fifth International Conference on Cloud Computing.

[15]  Dimosthenis Kyriazis,et al.  Dynamic, behavioral-based estimation of resource provisioning based on high-level application terms in Cloud platforms , 2014, Future Gener. Comput. Syst..

[16]  Mohammad Kazem Akbari,et al.  Dynamic Resource Provisioning in Cloud Computing: A Heuristic Markovian Approach , 2013, CloudComp.

[17]  El-Ghazali Talbi,et al.  Cost Minimization of Service Deployment in a Public Cloud Environment , 2013, 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum.

[18]  Eugene Ciurana,et al.  Google App Engine , 2009 .

[19]  Jian Zhang,et al.  Research on Open SaaS Software Architecture Based on SOA , 2010, 2010 International Symposium on Computational Intelligence and Design.

[20]  Stephen John Turner,et al.  DynaSched: a dynamic Web service scheduling and deployment framework for data-intensive Grid workflows , 2010, ICCS.

[21]  Edmundo Roberto Mauro Madeira,et al.  Load Balancing for Internet Distributed Services Using Limited Redirection Rates , 2011, 2011 5th Latin-American Symposium on Dependable Computing.

[22]  George S. Fishman,et al.  Discrete-event simulation , 2001 .

[23]  Samir Tata,et al.  Approximate Placement of Service-Based Applications in Hybrid Clouds , 2012, 2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[24]  Kuo-Chan Huang,et al.  Task ranking and allocation in list-based workflow scheduling on parallel computing platform , 2014, The Journal of Supercomputing.

[25]  Rajkumar Buyya,et al.  Dynamically scaling applications in the cloud , 2011, CCRV.

[26]  Souheil Khaddaj,et al.  Cloud Computing: Resource Management and Service Allocation , 2013, 2013 12th International Symposium on Distributed Computing and Applications to Business, Engineering & Science.

[27]  Junliang Chen,et al.  A Game Theory of Cloud Service Deployment , 2013, 2013 IEEE Ninth World Congress on Services.

[28]  George S. Fishman,et al.  Discrete-Event Simulation : Modeling, Programming, and Analysis , 2001 .

[29]  References , 1971 .