Deadline constraint heuristic-based genetic algorithm for workflow scheduling in cloud

Task scheduling and resource allocation are the key challenges of cloud computing. Compared with grid environment, data transfer is a big overhead for cloud workflows. So, the cost arising from data transfers between resources as well as execution costs must also be taken into account during scheduling based upon user's Quality of Service QoS constraints. In this paper, we present Deadline Constrained Heuristic based Genetic Algorithms HGAs to schedule applications to cloud resources that minimise the execution cost while meeting the deadline for delivering the result. Each workflow's task is assigned priority using bottom-level b-level and top-level t-level. To increase the population diversity, these priorities are then used to create the initial population of HGAs. The proposed algorithms are simulated and evaluated with synthetic workflows based on realistic workflows. The simulation results show that our proposed algorithms have a promising performance as compared to Standard Genetic Algorithm SGA.

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

[2]  Yong Zhao,et al.  Cloud Computing and Grid Computing 360-Degree Compared , 2008, GCE 2008.

[3]  Amir Masoud Rahmani,et al.  A novel task scheduling in multiprocessor systems with genetic algorithm by using elitism stepping method , 2008 .

[4]  Samee Ullah Khan,et al.  Multi-level hierarchic genetic-based scheduling of independent jobs in dynamic heterogeneous grid environment , 2012, Inf. Sci..

[5]  Ian J. Taylor,et al.  Workflows and e-Science: An overview of workflow system features and capabilities , 2009, Future Gener. Comput. Syst..

[6]  Wenhua Zeng,et al.  Grid Workflow Scheduling based on improved genetic algorithm , 2010, 2010 International Conference On Computer Design and Applications.

[7]  Nirwan Ansari,et al.  A Genetic Algorithm for Multiprocessor Scheduling , 1994, IEEE Trans. Parallel Distributed Syst..

[8]  Ke Liu,et al.  Scheduling algorithms for instance-intensive cloud workflows , 2009 .

[9]  Sakshi Kaushal,et al.  Cloud Computing Security Issues and Challenges: A Survey , 2011, ACC.

[10]  Sakshi Kaushal,et al.  Deadline and Budget Distribution based Cost- Time Optimization Workflow Scheduling Algorithm for Cloud , 2012 .

[11]  Rajkumar Buyya,et al.  Workflow scheduling algorithms for grid computing , 2008 .

[12]  Ciprian Dobre,et al.  Genetic algorithm for DAG scheduling in Grid environments , 2009, 2009 IEEE 5th International Conference on Intelligent Computer Communication and Processing.

[13]  Fatma A. Omara,et al.  Genetic algorithms for task scheduling problem , 2010, J. Parallel Distributed Comput..

[14]  Xiao Liu,et al.  A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-Intensive Cost-Constrained Workflows on a Cloud Computing Platform , 2010, Int. J. High Perform. Comput. Appl..

[15]  Suraj Pandey,et al.  Scheduling and management of data intensive application workflows in grid and cloud computing environments , 2010 .

[16]  Mei-Hui Su,et al.  Characterization of scientific workflows , 2008, 2008 Third Workshop on Workflows in Support of Large-Scale Science.

[17]  Adnan Fida,et al.  Workflow scheduling for service oriented cloud computing , 2008 .

[18]  Dennis Gannon,et al.  Workflows for e-Science, Scientific Workflows for Grids , 2014 .

[19]  Tao Guo,et al.  An iterative heuristic for scheduling grid workflows with budget constraints , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[20]  Rajkumar Buyya,et al.  A Taxonomy of Workflow Management Systems for Grid Computing , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[21]  Rajkumar Buyya,et al.  Scheduling scientific workflow applications with deadline and budget constraints using genetic algorithms , 2006, Sci. Program..

[22]  Rajkumar Buyya,et al.  Workflow Engine for Clouds , 2011, CloudCom 2011.

[23]  Xiao Liu,et al.  A market-oriented hierarchical scheduling strategy in cloud workflow systems , 2011, The Journal of Supercomputing.

[24]  Thomas M. Keane,et al.  Multi-heuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed system , 2010, J. Parallel Distributed Comput..

[25]  Amir Masoud Rahmani,et al.  A Novel Genetic Algorithm for Static Task Scheduling in Distributed Systems , 2009 .

[26]  Calvin J. Ribbens,et al.  Hybrid Computing - Where HPC meets grid and Cloud Computing , 2011, Future Gener. Comput. Syst..

[27]  M. Larkin,et al.  Websites , 2001 .

[28]  Yong Wang,et al.  A novel deadline and budget constrained scheduling heuristics for computational grids , 2011 .

[29]  Xiao Liu,et al.  An Algorithm in SwinDeW-C for Scheduling Transaction-Intensive Cost-Constrained Cloud Workflows , 2008, 2008 IEEE Fourth International Conference on eScience.

[30]  Rajkumar Buyya,et al.  Cost-based scheduling of scientific workflow applications on utility grids , 2005, First International Conference on e-Science and Grid Computing (e-Science'05).

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

[32]  Nawwaf N. Kharma,et al.  A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks , 2011, J. Parallel Distributed Comput..

[33]  Amandeep Verma,et al.  Scheduling using improved genetic algorithm in cloud computing for independent tasks , 2012, ICACCI '12.

[34]  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 .