Utility functions for adaptively executing concurrent workflows

Concurrency and Computation: Practice and Experience

Volumn 23, Issue 6, 2011, Pages 646-666

  Lee, Kevin ^a   Paton, Norman W ^a   Sakellariou, Rizos ^a   Fernandes, Alvaro A A ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

adaptivity; scientific workflows; utility functions

Indexed keywords

OPTIMIZATION; WORK SIMPLIFICATION;

ADAPTIVITY; COMPUTATIONAL RESOURCES; EXECUTION ENVIRONMENTS; EXPERIMENTAL EVALUATION; EXPLORATION OF ALTERNATIVES; SCIENTIFIC WORKFLOWS; UTILITY FUNCTIONS; WORKFLOW MANAGEMENT SYSTEMS;

MAPPING;

EID: 79952958217     PISSN: 15320626     EISSN: 15320634     Source Type: Journal    
DOI: 10.1002/cpe.1673     Document Type: Article

References (50)

1. Taylor IJ, Deelman E, Gannon DB, Shields M,. Workflows for e-Science. Scientific Workflows for Grids. Springer: 2007.
2. Deelman E, Gannon D, Shields M, Taylor I,. Workflows and e-Science: An overview of workflow system features and capabilities. Future Generation Computer Systems 2009; 25 (5): 528-540.
3. Blythe J, Jain S, Deelman E, Gil Y, Vahi K, Mandal A, Kennedy K,. Task scheduling strategies for workflow-based applications in grids. CCGrid05, 2005; 759-767.
4. Wieczorek M, Prodan R, Fahringer T,. Scheduling of scientific workflows in the ASKALON grid environment. SIGMOD Record 2005; 34 (3): 56-62. (Pubitemid 43152533)
5. Deelman E, Singh G, Su M-H, Blythe J, Gil Y, Kesselman C, Mehta G, Vahi K, Berriman GB, Good J, Laity A, Jacob JC, Katz DS,. Pegasus: A framework for mapping complex scientific workflows onto distributed systems. Scientific Programming 2005; 13 (3): 219-237. (Pubitemid 43022937)
6. Heinis T, Pautasso C, Alonso G,. Design and evaluation of an autonomic workflow engine. ICAC05: Proceedings of the 2nd International Conference on Autonomic Computing. IEEE Computer Society Press: Silver Spring, MD, 2005; 27-38. (Pubitemid 43959609)
7. Duan R, Prodan R, Fahringer T,. Run-time optimisation of grid workflow applications. Proceedings of the 7th IEEE/ACM International Conference on Grid Computing. IEEE Computer Society Press: Silver Spring, MD, 2006; 33-40.
8. Yu Z, Shi W,. An adaptive rescheduling strategy for grid workflow applications. IPDPS. IEEE Press: New York, 2007; 1-8.
9. Lee K, Sakellariou R, Paton NW, Fernandes AAA,. Workflow adaptation as an autonomic computing problem. WORKS07: Proceedings of the 2nd Workshop on Workflows in Support of Large-scale Science. ACM Press: New York, 2007; 29-34. (Pubitemid 47291449)
10. Kephart JO, Chess DM,. The vision of autonomic computing. IEEE Computer 2003; 36 (1): 41-50.
11. Kephart JO, Das R,. Achieving self-management via utility functions. IEEE Internet Computing 2007; 11 (1): 40-48. (Pubitemid 46332142)
12. Huebscher MC, McCann JA,. An adaptive middleware framework for context-aware applications. Personal and Ubiquitous Computing 2006; 10 (1): 12-20. (Pubitemid 41749178)
13. Yu J, Buyya R, Tham CK,. Cost-based scheduling of scientific workflow application on utility grids. e-Science. IEEE Computer Society: Silver Spring, MD, 2005; 140-147. (Pubitemid 46116670)
14. Blum C, Roli A,. Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys 2003; 35 (3): 268-308.
15. Lee K, Paton NW, Sakellariou R, Deelman E, Fernandes AAA, Metha G,. Adaptive workflow processing and execution in Pegasus. The 3rd International Workshop on Workflow Management and Applications in Grid Environments (WaGe08). Proceedings of the 3rd International Conference on Grid and Pervasive Computing Symposia/Workshops. IEEE Computer Society Press: Silver Spring, MD, 2008; 99-106.
16. Sakellariou R, Zhao H,. A low-cost rescheduling policy for efficient mapping of workflows on grid systems. Scientific Programming 2004; 12 (4): 253-262. (Pubitemid 40173745)
17. Hellerstein JL, Diao Y, Parekh S, Tilbury DM,. Feedback Control of Computing Systems. Wiley: New York, 2004.
18. Diao Y, Hellerstein JL, Storm AJ, Surendra M, Lightstone S, Parekh S, Garcia-Arellano C,. Incorporating cost of control into the design of a load balancing controller. IEEE Real-time and Embedded Technology and Applications Symposium, Toronto, Canada, 2004; 376-387.
19. Yfoulis C, Gounaris A, Paton NW,. An efficient load balancing lqr controller in parallel database queries under random perturbations. IEEE Multi-conference on Systems and Control, Saint Petersburg, Russia, 2009.
20. Gounaris A, Yfoulis C, Sakellariou R, Dikaiakos MD,. A control theoretical approach to self-optimizing block transfer in web service grids. ACM Transactions on Autonomous and Adaptive Systems 2008; 3 (2): 1-30.
21. Menascé DA, Dubey V,. Utility-based QoS brokering in service oriented architectures. ICWS07: IEEE International Conference on Web Services, Salt Lake City, Utah, U.S.A., 2007; 422-430.
22. Walsh WE, Tesauro G, Kephart JO, Das R,. Utility functions in autonomic systems. ICAC04: Proceedings of the 1st International Conference on Autonomic Computing. IEEE Press: New York, 2004; 70-77.
23. Kephart JO, Chan H, Das R, Levine DW, Tesauro G, Rawson F, Lefurgy C,. Coordinating multiple autonomic managers to achieve specified power-performance tradeoffs. ICAC07: Proceedings of the 4th International Conference on Autonomic Computing, Jacksonville, FL, U.S.A., 2007; 24.
24. Kumar V, Cooper BF, Schwan K,. Distributed stream management using utility-driven self-adaptive middleware. ICAC05: Proceedings of the 2nd International Conference on Autonomic Computing, Seattle, WA, U.S.A., 2005; 3-14. (Pubitemid 43959607)
25. Lee K, Paton NW, Sakellariou R, Fernandes AAA,. Utility driven adaptive workflow execution. CCGrid 2009, 2009.
26. Kwok YK, Ahmad I,. Static scheduling algorithms for allocating directed task graphs to multiprocessors. ACM Computing Surveys 1999; 31 (4): 406-471.
27. Sakellariou R, Zhao H,. A hybrid heuristic for DAG scheduling on heterogeneous systems. The 13th Heterogeneous Computing Workshop. IEEE Computer Society Press: Silver Spring, MD, 2004; 111-123.
28. Nurmi D, Mandal A, Brevik J, Koelbel C, Wolski R, Kennedy K,. Evaluation of a workflow scheduler using integrated performance modelling and batch queue wait time prediction. SC06: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. ACM: New York, NY, U.S.A., 2006; 119.
29. Canon LC, Jeannot E, Sakellariou R, Zheng W,. Comparative evaluation of the robustness of dag scheduling heuristics. Integrated Research in Grid Computing, CoreGRID Integration Workshop, Hersonissos, Crete, Greece, 2008; 63-74.
30. Mandal A, Kennedy K, Koelbel C, Marin G, Mellor-Crummey J, Liu B, Johnsson L,. Scheduling strategies for mapping application workflows onto the grid. HPDC05: Proceedings of the 14th IEEE International Symposium on High Performance Distributed Computing (HPDC-14). IEEE Computer Society: Washington, DC, U.S.A., 2005; 125-134. (Pubitemid 41543482)
31. Topcuoglu H, Hariri S, Wu MY,. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE Transactions on Parallel and Distributed Systems 2002; 13 (3): 260-274. (Pubitemid 34448780)
32. Nadeem F, Fahringer T,. Predicting the execution time of grid workflow applications through local learning. SC09: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis. ACM: New York, NY, U.S.A., 2009; 1-12.
33. Jarvis SA, He L, Spooner DP, Nudd GR,. The impact of predictive inaccuracies on execution scheduling. Performance Evaluation 2005; 60 (1-4): 127-139. Performance Modeling and Evaluation of High-performance Parallel and Distributed Systems. (Pubitemid 40304991)
34. Adve VS, Bagrodia R, Browne JC, Deelman E, Dube A, Houstis E, Rice J, Sakellariou R, Sundaram-Stukel D, Teller PJ, Vernon MK,. Poems: End-to-end performance design of large parallel adaptive computational systems. IEEE Transactions on Software Engineering 2000; 26: 1027-1048. (Pubitemid 32076243)
35. Feitelson DG, Rudolph L, Schwiegelshohn U,. Parallel job schedulingâA status report. JSSPP04: Proceedings of the 10th International Workshop on Job Scheduling Strategies for Parallel Processing. Springer: Berlin, Heidelberg, 2004; 1-16.
36. Decker J, Schneider J,. Heuristic scheduling of grid workflows supporting co-allocation and advance reservation. IEEE International Symposium on Cluster Computing and the Grid. IEEE Computer Society: Los Alamitos, CA, U.S.A., 2007; 335-342. (Pubitemid 47334571)
37. Kuo D, Mckeown M,. Advance reservation and co-allocation protocol for grid computing. E-SCIENCE05: Proceedings of the First International Conference on e-Science and Grid Computing. IEEE Computer Society: Washington, DC, U.S.A., 2005; 164-171. (Pubitemid 46116673)
38. Zhao H, Sakellariou R,. Advance reservation policies for workflows. JSSPP06: Proceedings of the 12th International Workshop on Job scheduling Strategies for Parallel Processing. Springer: Berlin, Heidelberg, 2006; 47-67.
39. Margo M, Yoshimoto K, Kovatch PA, Andrews P,. Impact of reservations on production job scheduling. JSSPP07: Proceedings of the 13th International Workshop on Job Scheduling Strategies for Parallel Processing. Springer: Berlin, Heidelberg, 2007; 116-131.
40. Qin J, Wieczorek M, Plankensteiner K, Fahringer T,. Towards a light-weight workflow engine in the Askalon Grid environment. CoreGRID Symposium. Springer: Berlin, 2007; 239-251.
41. Duan R, Prodan R, Fahringer T,. Performance and cost optimization for multiple large-scale grid workflow applications. SC, 2007; 12.
42. Wieczorek M, Hoheisel A, Prodan R,. Towards a general model of the multi-criteria workflow scheduling on the grid. Future Generation Computer Systems 2009; 25 (3): 237-256.
43. Yu J, Buyya R,. Scheduling scientific workflow applications with deadline and budget constraints using genetic algorithms. Scientific Programming 2006; 14: 217-230. (Pubitemid 46474559)
44. Sakellariou R, Zhao H, Tsiakkouri E, Dikaiakos MD,. Scheduling workflows with budget constraints. Integrated Research in Grid Computing. Springer: Berlin, 2007; 189-202.
45. Bennani MN, Menascé DA,. Resource allocation for autonomic data centers using analytic performance models. ICAC05: Proceedings of the Second International Conference on Autonomic Computing. IEEE Computer Society Press: Silver Spring, MD, 2005; 229-240. (Pubitemid 43959626)
46. Frey J, Tannenbaum T, Livny M, Foster I, Tuecke S,. Condor-G: A computation management agent for multi-institutional grids. HPDC01: Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing (HPDC-10), 2001; 55-63.
47. Arasu A, Babcock B, Babu S, Datar M, Ito K, Nishizawa I, Rosenstein J, Widom J,. STREAM: The Stanford stream data manager. SIGMOD Conference, Madison, WI, U.S.A., 2003; 665.
48. Arasu A, Babu S, Widom J,. The CQL continuous query language: Semantic foundations and query execution. VLDB Journal 2006; 15 (2): 121-142. (Pubitemid 43938935)
49. Abramson MA, Audet C, Dennis JE,. Nonlinear programing with mesh adaptive direct searches. SIAG/Optimization Views-and-News 2006; 17 (1): 2-11.
50. Audet C, Dennis JJE,. Mesh adaptive direct search algorithms for constrained optimization. SIAM Journal on Optimization 2006; 17 (1): 188-217.