An energy-efficient process clustering assignment algorithm for distributed system

Abstract This paper proposes a distributed assignment algorithm for selecting the optimal energy consumption during process execution, idling, and transmission in a distributed system. Selection criteria are based on identifying candidate processing units that are suitable for minimizing idle energy in task scheduling. The proposed algorithm tries to mimic as close to real situation as possible by assuming that each processing unit has multiple capabilities to execute different tasks with different characteristics. Task scheduling can be flexibly carried out to attain optimal energy consumption without any restrictions as those of comparative algorithms. Thus, the energy required by each processing unit varies considerably depending on the schedule. Experimental results show that the proposed algorithm yields the lowest idle, total energy consumption, and satisfactory execution energy. The extraneous transmission energy is a trade-off for scheduling flexibility.

[1]  Sandeep K. S. Gupta,et al.  Energy Proportionality and the Future: Metrics and Directions , 2010, 2010 39th International Conference on Parallel Processing Workshops.

[2]  M. Bozyigit,et al.  Energy Aware Dynamic Server Selection and Task Allocation , 2008, 2008 23rd International Symposium on Computer and Information Sciences.

[3]  Xiao Qin,et al.  An Availability-Aware Task Scheduling Strategy for Heterogeneous Systems , 2008, IEEE Transactions on Computers.

[4]  Dharma P. Agrawal,et al.  Improving scheduling of tasks in a heterogeneous environment , 2004, IEEE Transactions on Parallel and Distributed Systems.

[5]  Ümit V. Çatalyürek,et al.  A task duplication based bottom-up scheduling algorithm for heterogeneous environments , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[6]  Helen D. Karatza,et al.  Scheduling real-time DAGs in heterogeneous clusters by combining imprecise computations and bin packing techniques for the exploitation of schedule holes , 2012, Future Gener. Comput. Syst..

[7]  Jing-Chiou Liou,et al.  A comparison of general approaches to multiprocessor scheduling , 1997, Proceedings 11th International Parallel Processing Symposium.

[8]  Albert Y. Zomaya,et al.  Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions , 2011, IEEE Transactions on Parallel and Distributed Systems.

[9]  Muslim Bozyigit,et al.  Scalable Energy-Aware Dynamic Task Allocation , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[10]  Ruay-Shiung Chang,et al.  An Adaptive Scoring Job Scheduling algorithm for grid computing , 2012, Inf. Sci..

[11]  Salim Hariri,et al.  Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing , 2002, IEEE Trans. Parallel Distributed Syst..

[12]  Tao Yang,et al.  DSC: Scheduling Parallel Tasks on an Unbounded Number of Processors , 1994, IEEE Trans. Parallel Distributed Syst..

[13]  Feng Zhao,et al.  Energy-optimal software partitioning in heterogeneous multiprocessor embedded systems , 2008, 2008 45th ACM/IEEE Design Automation Conference.

[14]  Sanjay Ranka,et al.  An overview and classification of thermal-aware scheduling techniques for multi-core processing systems , 2012, Sustain. Comput. Informatics Syst..

[15]  Feng Ding,et al.  An Improved Task Scheduling Algorithm for Heterogeneous Systems , 2009, 2009 International Joint Conference on Computational Sciences and Optimization.

[16]  G. S. Visweswaran,et al.  Battery aware dynamic scheduling for periodic task graphs , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[17]  Dharma P. Agrawal,et al.  Optimal Scheduling Algorithm for Distributed-Memory Machines , 1998, IEEE Trans. Parallel Distributed Syst..

[18]  Subramaniam Shamala,et al.  New method for scheduling heterogeneous multi-installment systems , 2012, Future Gener. Comput. Syst..

[19]  Vincenzo Liberatore.  Multicast scheduling for list requests , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[20]  Susanne Albers,et al.  Energy-efficient algorithms for flow time minimization , 2006, STACS.

[21]  Helen D. Karatza,et al.  Performance evaluation and energy consumption of a real-time heterogeneous grid system using DVS and DPM , 2013, Simul. Model. Pract. Theory.

[22]  Ishfaq Ahmad,et al.  On Exploiting Task Duplication in Parallel Program Scheduling , 1998, IEEE Trans. Parallel Distributed Syst..

[23]  Meikang Qiu,et al.  Battery-aware task scheduling in distributed mobile systems with lifetime constraint , 2011, 16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011).

[24]  Helen D. Karatza,et al.  Performance and energy aware cluster-level scheduling of compute-intensive jobs with unknown service times , 2011, Simul. Model. Pract. Theory.