A minimized makespan scheduler with multiple factors for Grid computing systems

Most scheduling heuristics applied to Heterogeneous Computing (HC) focus on the search of a minimum makespan, instead of the reduction of cost. However, relevant studies presume that HC is based on high-speed bandwidth and communication time has ignored. Furthermore, in response to the appeal for a user-pay policy, when a user submits a job to a Grid environment for computation each implementation of a job would be charged. Therefore, the Apparent Tardiness Cost Setups-Minimum Completion Time (ATCS-MCT) scheduling heuristic considers both makespan and cost, and it composes of execution time, communication time, weight and deadline factors. This study simulates experiments in a dynamic environment, due to the nature of Grid computing being dynamic. The ATCS-MCT is compared to frequent solutions by five scheduling heuristics. This study indicates that the ATCS-MCT achieves a similarly smaller makespan, and lower cost than Minimum Completion Time (MCT) scheduling heuristic, which is the benchmark of on-line mapping.

[1]  E. Ilavarasan,et al.  Performance Effective Task Scheduling Algorithm for Heterogeneous Computing System , 2005, The 4th International Symposium on Parallel and Distributed Computing (ISPDC'05).

[2]  David P. Anderson,et al.  SETI@home: an experiment in public-resource computing , 2002, CACM.

[3]  Ladislau Bölöni,et al.  A comparison study of static mapping heuristics for a class of meta-tasks on heterogeneous computing systems , 1999, Proceedings. Eighth Heterogeneous Computing Workshop (HCW'99).

[4]  R. F. Freund,et al.  Dynamic Mapping of a Class of Independent Tasks onto Heterogeneous Computing Systems , 1999, J. Parallel Distributed Comput..

[5]  Selim G. Akl,et al.  Scheduling Algorithms for Grid Computing: State of the Art and Open Problems , 2006 .

[6]  John Levine,et al.  A fast, effective local search for scheduling independent jobs in heterogeneous computing environments , 2003 .

[7]  Jin Suk Kim,et al.  An Online Scheduling Algorithm for Grid Computing Systems , 2003, GCC.

[8]  Yacine Atif,et al.  To Schedule or to Execute: Decision Support and Performance Implications , 2004, Real-Time Systems.

[9]  Min-You Wu,et al.  A high-performance mapping algorithm for heterogeneous computing systems , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[10]  David Abramson,et al.  Economic models for resource management and scheduling in Grid computing , 2002, Concurr. Comput. Pract. Exp..

[11]  Ladislau Bölöni,et al.  A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems , 2001, J. Parallel Distributed Comput..

[12]  X. Chao,et al.  Operations scheduling with applications in manufacturing and services , 1999 .

[13]  Viktor K. Prasanna,et al.  Heterogeneous computing: challenges and opportunities , 1993, Computer.

[14]  Deborah Estrin,et al.  Advances in network simulation , 2000, Computer.

[15]  Hsin-An Chen.  On the design of task scheduling in the heterogeneous computing environments , 2005, PACRIM. 2005 IEEE Pacific Rim Conference on Communications, Computers and signal Processing, 2005..

[16]  Changjun Jiang,et al.  Resource Scheduling Algorithms for Grid Computing and Its Modeling and Analysis Using Petri Net , 2003, GCC.

[17]  Atakan Dogan,et al.  Static Mapping Heuristics for Tasks with Hard Deadlines in Real-Time Heterogeneous Systems , 2004, ISCIS.

[18]  Kenichi Hagihara,et al.  A comparison among grid scheduling algorithms for independent coarse-grained tasks , 2004, 2004 International Symposium on Applications and the Internet Workshops. 2004 Workshops..