scholarly journals An efficient fault-tolerant scheduling algorithm for precedence constrained tasks in heterogeneous distributed systems

2007 ◽  
pp. 301-307 ◽  
Author(s):  
M. Nakechbandi ◽  
J.-Y. Colin ◽  
J.B. Gashumba
Keyword(s):  
Distributed Systems ◽  
Fault Tolerant ◽  
Scheduling Algorithm ◽  
Heterogeneous Distributed Systems

DAG Reliability Model and Fault-Tolerant Algorithm for Heterogeneous Distributed Systems

2014 ◽  
Vol 36 (10) ◽  
pp. 2019-2032 ◽  
Author(s):  
Guo-Qi XIE ◽  
Ren-Fa LI ◽  
Lin LIU ◽  
Fan YANG
Keyword(s):  
Distributed Systems ◽  
Fault Tolerant ◽  
Reliability Model ◽  
Heterogeneous Distributed Systems

A Novel Security-Driven Scheduling Algorithm for Precedence-Constrained Tasks in Heterogeneous Distributed Systems

2011 ◽  
Vol 60 (7) ◽  
pp. 1017-1029 ◽  
Author(s):  
Tang Xiaoyong ◽  
Kenli Li ◽  
Zeng Zeng ◽  
Bharadwaj Veeravalli
Keyword(s):  
Distributed Systems ◽  
Scheduling Algorithm ◽  
Heterogeneous Distributed Systems

Enhanced Parallel Application Scheduling Algorithm with Energy Consumption Constraint in Heterogeneous Distributed Systems

2019 ◽  
Vol 28 (11) ◽  
pp. 1950190 ◽  
Author(s):  
Jinghong Li ◽  
Guoqi Xie ◽  
Keqin Li ◽  
Zhuo Tang
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Gaussian Elimination ◽  
Scheduling Algorithm ◽  
Parallel Applications ◽  
Parallel Application ◽  
Heterogeneous Distributed Systems ◽  
Dynamic Voltage ◽  
Cluster Computer Systems ◽  
Consumption Constraints

Energy consumption has always been one of the main design problems in heterogeneous distributed systems, whether for large cluster computer systems or small handheld terminal devices. And as energy consumption explodes for complex performance, many efforts and work are focused on minimizing the schedule length of parallel applications that meet the energy consumption constraints currently. In prior studies, a pre-allocation method based on dynamic voltage and frequency scaling (DVFS) technology allocates unassigned tasks with minimal energy consumption. However, this approach does not necessarily result in minimal scheduling length. In this paper, we propose an enhanced scheduling algorithm, which allocates the same energy consumption for each task by selecting a relatively intermediate value among the unequal allocations. Based on the two real-world applications (Fast Fourier transform and Gaussian elimination) and the randomly generated parallel application, experiments show that the proposed algorithm not only achieves better scheduling length while meeting the energy consumption constraints, but also has better performance than the existing parallel algorithms.

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