A Hyper-Heuristic Scheduling Algorithm for Cloud

Rule-based scheduling algorithms have been widely used on many cloud computing systems because they are simple and easy to implement. However, there is plenty of room to improve the performance of these algorithms, especially by using heuristic scheduling. As such, this paper presents a novel heuristic scheduling algorithm, called hyper-heuristic scheduling algorithm (HHSA), to find better scheduling solutions for cloud computing systems. The diversity detection and improvement detection operators are employed by the proposed algorithm to dynamically determine which low-level heuristic is to be used in finding better candidate solutions. To evaluate the performance of the proposed method, this study compares the proposed method with several state-of-the-art scheduling algorithms, by having all of them implemented on CloudSim (a simulator) and Hadoop (a real system). The results show that HHSA can significantly reduce the makespan of task scheduling compared with the other scheduling algorithms evaluated in this paper, on both CloudSim and Hadoop.

[1]  Tongwen Chen,et al.  Optimal periodic scheduling of sensor networks: A branch and bound approach , 2013, Syst. Control. Lett..

[2]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[3]  Jun Zhang,et al.  An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[4]  Meikang Qiu,et al.  Online optimization for scheduling preemptable tasks on IaaS cloud systems , 2012, J. Parallel Distributed Comput..

[5]  Scott Shenker,et al.  Delay scheduling: a simple technique for achieving locality and fairness in cluster scheduling , 2010, EuroSys '10.

[6]  Balamurali Krishna Ambati,et al.  Heuristic combinatorial optimization by simulated Darwinian evolution: a polynomial time algorithm for the Traveling Salesman Problem , 2004, Biological Cybernetics.

[7]  Lin-Yu Tseng,et al.  A genetic approach to the automatic clustering problem , 2001, Pattern Recognit..

[8]  Roy D. Sleator,et al.  'Big data', Hadoop and cloud computing in genomics , 2013, J. Biomed. Informatics.

[9]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

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

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

[12]  Marty Humphrey,et al.  Auto-scaling to minimize cost and meet application deadlines in cloud workflows , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[13]  Tingwen Huang,et al.  Outsourcing Large Matrix Inversion Computation to A Public Cloud , 2013, IEEE Transactions on Cloud Computing.

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

[15]  Yong Zhao,et al.  Grid middleware services for virtual data discovery, composition, and integration , 2004, MGC '04.

[16]  Thomas Stützle,et al.  Stochastic Local Search: Foundations & Applications , 2004 .

[17]  Balasubramanie,et al.  Ant Algorithm for Grid Scheduling Powered by Local Search , 2009 .

[18]  Walter H. Kohler,et al.  A Preliminary Evaluation of the Critical Path Method for Scheduling Tasks on Multiprocessor Systems , 1975, IEEE Transactions on Computers.

[19]  Khaled M. F. Elsayed,et al.  Channel-Aware Earliest Deadline Due Fair Scheduling for Wireless Multimedia Networks , 2006, Wirel. Pers. Commun..

[20]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[21]  Albert Y. Zomaya,et al.  Profit-driven scheduling for cloud services with data access awareness , 2012, J. Parallel Distributed Comput..

[22]  Inderveer Chana,et al.  A Survey of Various Workflow Scheduling Algorithms in Cloud Environment , 2011 .

[23]  R. Buyya,et al.  A budget constrained scheduling of workflow applications on utility Grids using genetic algorithms , 2006, 2006 Workshop on Workflows in Support of Large-Scale Science.

[24]  Albert Y. Zomaya,et al.  On the Characterization of the Structural Robustness of Data Center Networks , 2013, IEEE Transactions on Cloud Computing.

[25]  Wu,et al.  Study of Smart Grid Marketing System Architecture Based on Hadoop Platform of Cloud Computing , 2012 .

[26]  Xiaorong Li,et al.  Hybrid Heuristic for Scheduling Data Analytics Workflow Applications in Hybrid Cloud Environment , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.

[27]  Jacques Carlier,et al.  Handbook of Scheduling - Algorithms, Models, and Performance Analysis , 2004 .

[28]  Mahmoud Naghibzadeh,et al.  Deadline-constrained workflow scheduling in software as a service Cloud , 2012, Sci. Iran..

[29]  Meikang Qiu,et al.  Adaptive resource allocation for preemptable jobs in cloud systems , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[30]  John Darlington,et al.  Mapping of Scientific Workflow within the e-Protein project to Distributed Resources , 2004 .

[31]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[32]  Shiyong Lu,et al.  Scheduling Scientific Workflows Elastically for Cloud Computing , 2011, 2011 IEEE 4th International Conference on Cloud Computing.

[33]  Hyun-Sup Shin,et al.  The new approach for inter-communication between guest domains on Virtual Machine Monitor , 2007, 2007 22nd international symposium on computer and information sciences.

[34]  Uday K. Chakraborty,et al.  An efficient hybrid heuristic for makespan minimization in permutation flow shop scheduling , 2009 .

[35]  Rainer Kolisch,et al.  PSPLIB - A project scheduling problem library: OR Software - ORSEP Operations Research Software Exchange Program , 1997 .

[36]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[37]  S. M. Johnson,et al.  Optimal two- and three-stage production schedules with setup times included , 1954 .

[38]  Joel J. P. C. Rodrigues,et al.  Metaheuristic Scheduling for Cloud: A Survey , 2014, IEEE Systems Journal.

[39]  Klaus H. Ecker,et al.  Scheduling Computer and Manufacturing Processes , 2001 .

[40]  Chris Fleizach CSE 262 Readings : May 11 . 2006 Task Scheduling Strategies for Workflow based Applications in Grids , 2015 .

[41]  Rajkumar Buyya,et al.  CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms , 2011, Softw. Pract. Exp..

[42]  Bin Zhang,et al.  Task Scheduling in Grid Based on Particle Swarm Optimization , 2006, 2006 Fifth International Symposium on Parallel and Distributed Computing.

[43]  Michael Devetsikiotis,et al.  Aggregated-DAG Scheduling for Job Flow Maximization in Heterogeneous Cloud Computing , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[44]  Graham Kendall,et al.  A Hyperheuristic Approach to Scheduling a Sales Summit , 2000, PATAT.

[45]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[46]  D. Daniel,et al.  A novel approach for scheduling service request in cloud with trust monitor , 2011, 2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies.

[47]  Ricki G. Ingalls,et al.  PERT scheduling with resources using qualitative simulation graphs , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[48]  Rajbir Singh Cheema,et al.  Comparison of Workflow Scheduling Algorithms in Cloud Computing , 2011 .

[49]  Lavanya Ramakrishnan,et al.  VGrADS: enabling e-Science workflows on grids and clouds with fault tolerance , 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

[50]  Rainer Kolisch,et al.  Approximate Dynamic Programming for Capacity Allocation in the Service Industry , 2010, Eur. J. Oper. Res..

[51]  Ravi Sethi,et al.  The Complexity of Flowshop and Jobshop Scheduling , 1976, Math. Oper. Res..