scholarly journals Bio-backfill: A Scheduling Policy Enhancing the Performance of Bioinformatics Workflows in Shared Clusters

2018 ◽  
Author(s):  
Ferran Badosa ◽  
Antonio Espinosa ◽  
Gonzalo Vera ◽  
Ana Ripoll
Keyword(s):  
Scheduling Policy ◽  
Bioinformatics Workflows

A scheduling policy to save 10% of communication time in parallel fast Fourier transform

2021 ◽  
Author(s):  
Samar A. Aseeri ◽  
Anando Gopal Chatterjee ◽  
Mahendra K. Verma ◽  
David E. Keyes
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Scheduling Policy ◽  
Communication Time

scholarly journals Aircraft Maintenance Check Scheduling Using Reinforcement Learning

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 113
Author(s):  
Pedro Andrade ◽  
Catarina Silva ◽  
Bernardete Ribeiro ◽  
Bruno F. Santos
Keyword(s):  
Reinforcement Learning ◽  
Time Horizon ◽  
Learning Algorithm ◽  
Initial Conditions ◽  
Q Learning ◽  
Scheduling Policy ◽  
Real Scenario ◽  
Maintenance Plan ◽  
Small Disturbances

This paper presents a Reinforcement Learning (RL) approach to optimize the long-term scheduling of maintenance for an aircraft fleet. The problem considers fleet status, maintenance capacity, and other maintenance constraints to schedule hangar checks for a specified time horizon. The checks are scheduled within an interval, and the goal is to, schedule them as close as possible to their due date. In doing so, the number of checks is reduced, and the fleet availability increases. A Deep Q-learning algorithm is used to optimize the scheduling policy. The model is validated in a real scenario using maintenance data from 45 aircraft. The maintenance plan that is generated with our approach is compared with a previous study, which presented a Dynamic Programming (DP) based approach and airline estimations for the same period. The results show a reduction in the number of checks scheduled, which indicates the potential of RL in solving this problem. The adaptability of RL is also tested by introducing small disturbances in the initial conditions. After training the model with these simulated scenarios, the results show the robustness of the RL approach and its ability to generate efficient maintenance plans in only a few seconds.

A scheduling policy for preserving cache locality in a multiprogrammed system

2000 ◽  
Vol 46 (13) ◽  
pp. 1191-1204
Author(s):  
Inbum Jung ◽  
Jongwoong Hyun ◽  
Joonwon Lee
Keyword(s):  
Scheduling Policy

Exigency-based real-time scheduling policy to provide absolute QoS for web services

2007 ◽  
Author(s):  
Lucas S. Casagrande ◽  
Rodrigo F. de Mello ◽  
Ricardo Bertagna ◽  
Jose A. Andrade Filho ◽  
Francisco J. Monaco
Keyword(s):  
Web Services ◽  
Real Time ◽  
Real Time Scheduling ◽  
Scheduling Policy ◽  
Time Scheduling

Fuzzy Logic Based Algorithm for Disk Scheduling Policy

2009 ◽  
Author(s):  
Mohamad Sofian Abu Talip ◽  
Aisha Hassan Abdalla ◽  
Ahmed Asif ◽  
Abdurazzag Ali Aburas
Keyword(s):  
Fuzzy Logic ◽  
Disk Scheduling ◽  
Scheduling Policy
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