Anticipation Scheduling in Grid with Stakeholders Preferences

In this work, a job-flow scheduling approach for grid virtual organizations (VOs) is proposed and studied. Users’ and resource providers’ preferences, VOs internal policies, resources geographical distribution along with local private utilization impose specific requirements for efficient scheduling according to different, usually contradictive, criteria. With increasing level of resources utilization, the set of available resources and corresponding decision space are reduced. This further complicates the problem of efficient scheduling. In order to improve overall scheduling efficiency, we propose an anticipation scheduling approach based on a cyclic scheduling scheme. It generates a near optimal but infeasible scheduling solution and includes a special replication procedure for efficient and feasible resources allocation. Anticipation scheduling is compared with the general cycle scheduling scheme and conservative backfilling using such criteria as average jobs’ start and finish times as well as users’ and VO economic criteria: total execution time and cost.

[1]  Victor V. Toporkov,et al.  Heuristic strategies for preference-based scheduling in virtual organizations of utility grids , 2015, J. Ambient Intell. Humaniz. Comput..

[2]  Jarek Nabrzyski,et al.  Multicriteria aspects of Grid resource management , 2004 .

[3]  Miranda R. Goode,et al.  The Psychological Consequences of Money , 2006, Science.

[4]  Richard Wolski,et al.  Eliciting honest value information in a batch-queue environment , 2007, 2007 8th IEEE/ACM International Conference on Grid Computing.

[5]  Helen D. Karatza,et al.  Job Scheduling in a Distributed System Using Backfilling with Inaccurate Runtime Computations , 2010, 2010 International Conference on Complex, Intelligent and Software Intensive Systems.

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

[7]  Maria Mirto,et al.  Preference–Based Matchmaking of Grid Resources with CP–Nets , 2012, Journal of Grid Computing.

[8]  Fernando Guirado,et al.  MIP Model Scheduling for Multi-Clusters , 2012, Euro-Par Workshops.

[9]  Victor V. Toporkov,et al.  Scheduling in Grid Based on VO Stakeholders Preferences and Criteria , 2016, DepCoS-RELCOMEX.

[10]  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..

[11]  Rajkumar Buyya,et al.  Fair resource sharing in hierarchical virtual organizations for global grids , 2007, 2007 8th IEEE/ACM International Conference on Grid Computing.

[12]  Valentin Cristea,et al.  Resource-aware hybrid scheduling algorithm in heterogeneous distributed computing , 2015, Future Gener. Comput. Syst..

[13]  Mark J. Clement,et al.  Core Algorithms of the Maui Scheduler , 2001, JSSPP.

[14]  Krzysztof Rzadca,et al.  Non-monetary fair scheduling: a cooperative game theory approach , 2013, SPAA.

[15]  Daniel Grosu,et al.  Divisible Load Scheduling: An Approach Using Coalitional Games , 2007, Sixth International Symposium on Parallel and Distributed Computing (ISPDC'07).

[16]  Yoshio Tanaka,et al.  An Advance Reservation-Based Co-allocation Algorithm for Distributed Computers and Network Bandwidth on QoS-Guaranteed Grids , 2010, JSSPP.

[17]  Liana L. Fong,et al.  Enabling Interoperability among Grid Meta-Schedulers , 2013, Journal of Grid Computing.

[18]  Anthony T. Chronopoulos,et al.  Cost minimization in utility computing systems , 2014, Concurr. Comput. Pract. Exp..

[19]  Adam Wierzbicki,et al.  Fair Game-Theoretic Resource Management in Dedicated Grids , 2007, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07).

[20]  Ramin Yahyapour,et al.  Economic Scheduling in Grid Computing , 2002, JSSPP.

[21]  Albert Y. Zomaya,et al.  Pareto-Optimal Cloud Bursting , 2014, IEEE Transactions on Parallel and Distributed Systems.

[22]  Victor V. Toporkov,et al.  Metascheduling and Heuristic Co-Allocation Strategies in Distributed Computing , 2015, Comput. Informatics.

[23]  Victor V. Toporkov,et al.  Slot selection algorithms in distributed computing , 2014, The Journal of Supercomputing.

[24]  Peter Merz,et al.  Agent-Based Grid Scheduling with Calana , 2005, PPAM.