A Static Multiprocessor Scheduling Algorithm for Arbitrary Directed Task Graphs in Uncertain Environments

2008 ◽  
pp. 18-29 ◽  
Author(s):  
Jun Yang ◽  
Xiaochuan Ma ◽  
Chaohuan Hou ◽  
Zheng Yao
Keyword(s):  
Scheduling Algorithm ◽  
Multiprocessor Scheduling ◽  
Uncertain Environments ◽  
Task Graphs

scholarly journals Real-Time Multiprocessor Scheduling Algorithm Based on Information Theory Principles

2017 ◽  
Vol 9 (4) ◽  
pp. 93-96 ◽  
Author(s):  
Carlos A. Rincon C. ◽  
Xingliang Zou ◽  
Albert M. K. Cheng
Keyword(s):  
Information Theory ◽  
Real Time ◽  
Scheduling Algorithm ◽  
Multiprocessor Scheduling

An unfair semi-greedy real-time multiprocessor scheduling algorithm

2016 ◽  
Vol 50 ◽  
pp. 143-165 ◽  
Author(s):  
Hitham Alhussian ◽  
Nordin Zakaria ◽  
Ahmed Patel
Keyword(s):  
Real Time ◽  
Scheduling Algorithm ◽  
Multiprocessor Scheduling

Expected Cost Based Greedy Scheduling Algorithm for Out-Tree Task Graphs

2014 ◽  
Vol 556-562 ◽  
pp. 3431-3437 ◽  
Author(s):  
Jian Jun Zhang ◽  
Tian Hong Wang ◽  
Yu Zhuo Wang
Keyword(s):  
High Performance ◽  
Heterogeneous Computing ◽  
Heuristic Algorithms ◽  
Scheduling Algorithm ◽  
Heterogeneous Environments ◽  
Task Graphs ◽  
Schedule Length ◽  
Current Task ◽  
Greedy Scheduling Algorithm ◽  
Greedy Scheduling

Effective task scheduling is crucial for achieving high performance in heterogeneous computing environments. Whiling scheduling Out-Tree task graphs, many previous heterogeneity based heuristic algorithms usually require high scheduling costs and may not deliver good quality schedules with lower costs. Aiming at the characteristics of Out-Tree task graphs and the features of heterogeneous environments and adopting the strategy based on expected costs and task duplications, this paper proposes a greedy scheduling algorithm, which, at each scheduling step, tries to guarantee not to increase the schedule length, schedules the current task onto the used processor which minimizes its execution finish time; meanwhile, takes load balances into account to economize the use of processors. The comparative experimental results show that the proposed algorithm has higher scheduling efficiency and robust performance, which could produce better schedule which has shorter schedule length and less number of used processors.

A Fuzzy CDS-based Scheduling Algorithm for More Than Two Machine Centers

2001 ◽  
Vol 5 (4) ◽  
pp. 239-245
Author(s):  
Tzung-Pei Hong ◽  
◽  
Tzu-Ting Wang ◽  
Shyue-Liang Wang ◽  
Keyword(s):  
Flow Shop ◽  
Scheduling Algorithm ◽  
Uncertain Environments ◽  
Flow Shops ◽  
Flow Shop Problem ◽  
Lpt Algorithm ◽  
Machine Centers ◽  
Operation Center ◽  
One Machine ◽  
Simple Flow

In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Flexible flow shops can thus be thought of as generalizations of simple flow shops. In Ref.14), we have demonstrated how fuzzy concepts can easily be used in the Sriskandarajak and Sethi’s algorithm for managing uncertain scheduling on two-machine centers. This paper extends application to fuzzy flexible flow-shops with more than two machine centers. A new fuzzy heuristic flexible flowshop scheduling algorithm is then designed since optimal solutions seem unnecessary for uncertain environments. We first use fuzzy LPT algorithm to allocate jobs into the groups and then use the fuzzy CDS algorithm to deal with sequencing the tasks. The proposed method thus provides a flexible way to more fit real world applications.

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