Cost-Driven Optimization of Cloud Resource Allocation for Elastic Processes

Today's extensive business process landscapes make it necessary to handle the execution of a large number of business processes and individual process steps. Especially if process steps require the invocation of resource-intensive applications or a large number of applications need to be executed concurrently, process owners may have to allocate extensive computational resources, leading to high fixed cost. In the work at hand, we propose an alternative to the provision of fixed resources, based on automatic leasing and releasing of Cloud-based computational resources. For this, we present an integrated approach which addresses the cost-driven optimization of Cloud-based computational resources for business processes in order to realize so-called Elastic Processes. Through an evaluation, we show the practical applicability and benefits of our contributions. Specifically, we find that our approach substantially reduces the cost compared to an ad hoc approach.

[1]  Iman Saleh,et al.  Adaptive Resource Management for Service Workflows in Cloud Environments , 2013, 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum.

[2]  Schahram Dustdar,et al.  Workflow Scheduling and Resource Allocation for Cloud-Based Execution of Elastic Processes , 2013, 2013 IEEE 6th International Conference on Service-Oriented Computing and Applications.

[3]  Julien Gossa,et al.  Comparing Provisioning and Scheduling Strategies for Workflows on Clouds , 2013, 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum.

[4]  Schahram Dustdar,et al.  A survey on web services composition , 2005, Int. J. Web Grid Serv..

[5]  Huilong Duan,et al.  Reinforcement learning based resource allocation in business process management , 2011, Data Knowl. Eng..

[6]  Dick H. J. Epema,et al.  Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds , 2013, Future Gener. Comput. Syst..

[7]  Ralf Steinmetz,et al.  Cost-Driven Optimization of Complex Service-Based Workflows for Stochastic QoS Parameters , 2012, 2012 IEEE 19th International Conference on Web Services.

[8]  Frank Leymann,et al.  How to adapt applications for the Cloud environment , 2012, Computing.

[9]  Christian Huemer,et al.  Towards Living Inter-organizational Processes , 2013, 2013 IEEE 15th Conference on Business Informatics.

[10]  M. Brian Blake,et al.  Decentralized Resource Coordination across Service Workflows in a Cloud Environment , 2013, 2013 Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[11]  Heiko Gewald,et al.  Risks and benefits of business process outsourcing: A study of transaction services in the German banking industry , 2009, Inf. Manag..

[12]  Srikumar Venugopal,et al.  Using reinforcement learning for controlling an elastic web application hosting platform , 2011, ICAC '11.

[13]  Rajkumar Buyya,et al.  A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments , 2010, 2010 24th IEEE International Conference on Advanced Information Networking and Applications.

[14]  G. Bruce Berriman,et al.  On the Use of Cloud Computing for Scientific Workflows , 2008, 2008 IEEE Fourth International Conference on eScience.

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

[16]  Mathias Uslar,et al.  Requirements for Smart Grid ICT-architectures , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[17]  Claudia Szabo,et al.  Evolving multi-objective strategies for task allocation of scientific workflows on public clouds , 2012, 2012 IEEE Congress on Evolutionary Computation.

[18]  Wil M. P. van der Aalst,et al.  Modelling work distribution mechanisms using Colored Petri Nets , 2007, International Journal on Software Tools for Technology Transfer.

[19]  Li-zhen Cui,et al.  A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing , 2009, 2009 IEEE International Symposium on Parallel and Distributed Processing with Applications.

[20]  Cesare Pautasso,et al.  RESTful business process management in the cloud , 2013, 2013 5th International Workshop on Principles of Engineering Service-Oriented Systems (PESOS).

[21]  Claude Godart,et al.  Bi-criteria strategies for business processes scheduling in cloud environments with fairness metrics , 2013, IEEE 7th International Conference on Research Challenges in Information Science (RCIS).

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

[23]  Valeria Cardellini,et al.  SLA-aware Resource Management for Application Service Providers in the Cloud , 2011, 2011 First International Symposium on Network Cloud Computing and Applications.

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

[25]  Wil M.P. van der Aalst,et al.  Modeling work distribution mechanisms using colored petri nets , 2005 .

[26]  Mathias Weske,et al.  Scientific Workflows: Business as Usual? , 2009, BPM.

[27]  Rizos Sakellariou,et al.  Adaptive resource configuration for Cloud infrastructure management , 2013, Future Gener. Comput. Syst..

[28]  Rajkumar Buyya,et al.  InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services , 2010, ICA3PP.

[29]  Jin-Soo Kim,et al.  Cost optimized provisioning of elastic resources for application workflows , 2011, Future Gener. Comput. Syst..

[30]  Manfred Reichert,et al.  Unleashing the Effectiveness of Process-Oriented Information Systems: Problem Analysis, Critical Success Factors, and Implications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[31]  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 .

[32]  Srikumar Venugopal,et al.  Self-Adaptive Resource Allocation for Elastic Process Execution , 2013, 2013 IEEE Sixth International Conference on Cloud Computing.

[33]  Ralf Steinmetz,et al.  Enabling cost-efficient Software Service Distribution in infrastructure clouds at run time , 2011, 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA).