DocumentCode :
2980059
Title :
A Distributed Fine-Grained Flow Control System for Scalable Aircraft Spares Management and Optimization in Clouds
Author :
Aye, T.T. ; Ta Nguyen Binh Duong ; Xiaorong Li ; Li, E.W.K.
Author_Institution :
Inst. of High Performance Comput., A*STAR, Singapore, Singapore
fYear :
2012
fDate :
17-19 Dec. 2012
Firstpage :
782
Lastpage :
787
Abstract :
In this paper, we presented the design, implementation, and evaluation of a distributed system to manage the parallelized analytics for Aircraft Spare parts Management and Optimizations (SMO), which is a well-known problem in logistics industry. Our proposed solution is able to solve the resource-intensive SMO problem using distributed computing infrastructures (e.g., private or public clouds) in a scalable manner. We designed and fine-tuned a parallel meta-heuristics based on a fine-grained flow control workflow model which enables flow controls of running parallel meta-heuristics in multiple processors and achieved significant performance gains. Together with priority based scheduling, the proposed system effectively dispatches submitted SMO jobs over the set of distributed resources to accommodate different classes of users. Extensive experimental studies were conducted to analyze the performance of parallelized SMO job executions in term of execution time, computation and data transmission time, waiting time, memory usage, etc. Insightful lessons have been drawn from the obtained results, and potential areas for further improvements have also been identified.
Keywords :
aircraft maintenance; cloud computing; job shop scheduling; logistics; parallel processing; resource allocation; SMO job dispatching; aircraft SMO; cloud computing; computation time; data transmission time; distributed computing infrastructures; distributed fine-grained flow control system; distributed resources; distributed system design; distributed system evaluation; distributed system implementation; execution time; fine-grained flow control workflow model; logistics industry; memory usage; multiple processors; parallel meta-heuristics; parallelized SMO job executions; performance analysis; priority-based scheduling; private clouds; public clouds; resource-intensive SMO problem; scalable aircraft spare parts management and optimizations; waiting time; Computational modeling; Memory management; Optimization; Processor scheduling; Program processors; Resource management; Torque; Cloud computing; distributed systems; job scheduling; parallel meta-heuristics; workflow control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Systems (ICPADS), 2012 IEEE 18th International Conference on
Conference_Location :
Singapore
ISSN :
1521-9097
Print_ISBN :
978-1-4673-4565-1
Electronic_ISBN :
1521-9097
Type :
conf
DOI :
10.1109/ICPADS.2012.127
Filename :
6413605
Link To Document :
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