An efficient list scheduling algorithm with task duplication for scientific big data workflow in heterogeneous computing environments

2020 ◽  
Author(s):  
Wakar Ahmad ◽  
Bashir Alam
Keyword(s):  
Big Data ◽  
Heterogeneous Computing ◽  
Scheduling Algorithm ◽  
List Scheduling ◽  
Task Duplication ◽  
Computing Environments

scholarly journals HSIP: A Novel Task Scheduling Algorithm for Heterogeneous Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Guan Wang ◽  
Yuxin Wang ◽  
Hui Liu ◽  
He Guo
Keyword(s):  
Task Scheduling ◽  
High Performance ◽  
Heterogeneous Computing ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Selection Policy ◽  
Task Scheduling Algorithm ◽  
Task Duplication ◽  
Task Priority ◽  
Low Efficiency

High-performance heterogeneous computing systems are achieved by the use of efficient application scheduling algorithms. However, most of the current algorithms have low efficiency in scheduling. Aiming at solving this problem, we propose a novel task scheduling algorithm for heterogeneous computing named HSIP (heterogeneous scheduling algorithm with improved task priority) whose functionality relies on three pillars: (1) an improved task priority strategy based on standard deviation with improved magnitude as computation weight and communication cost weight to make scheduling priority more reasonable; (2) an entry task duplication selection policy to make the makespan shorter; and (3) an improved idle time slots (ITS) insertion-based optimizing policy to make the task scheduling more efficient. We evaluate our proposed algorithm on randomly generated DAGs, using some real application DAGs by comparison with some classical scheduling algorithms. According to the experimental results, our proposed algorithm appears to perform better than other algorithms in terms of schedule length ratio, efficiency, and frequency of best results.

Task Optimization Scheduling Algorithm in Embedded System Based on Internet of Things

2014 ◽  
Vol 513-517 ◽  
pp. 2398-2402
Author(s):  
Dian Hong Wu
Keyword(s):  
Internet Of Things ◽  
Embedded System ◽  
Task Scheduling ◽  
Heterogeneous Computing ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Task Duplication ◽  
System Task ◽  
Network Server ◽  
Heterogeneous Computing System

Embedded system has been widely used in the network, server, etc., and it has a good application prospect with the development of Internet of things. In the embedded heterogeneous computing system, task scheduling is the key to deciding the system performance. For multi-task scheduling, the current scheduling algorithm is mostly based on task duplication, without a full consideration of the correlation between the predecessor task and its subsequent tasks. Based on modeling the multi-frame task scheduling problem in the heterogeneous embedded system, this paper analyzes the availability of tasks through the design of genetic algorithm, so as to verify the algorithm's feasibility, which is of important guiding significance for the multi-task scheduling in the embedded heterogeneous computing system.

scholarly journals List Scheduling Algorithm Based on Virtual Scheduling Length Table in Heterogeneous Computing System

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Naqin Zhou ◽  
Xiaowen Liao ◽  
Fufang Li ◽  
Yuanyong Feng ◽  
Liangchen Liu
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Heterogeneous Computing ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Efficient Implementation ◽  
Edge Computing ◽  
List Scheduling ◽  
Start Time ◽  
Current Task

Edge computing needs the close cooperation of cloud computing to better meet various needs. Therefore, ensuring the efficient implementation of applications in cloud computing is not only related to the development of cloud computing itself but also affects the promotion of edge computing. However, resource management and task scheduling strategy are important factors affecting the efficient implementation of applications. Therefore, aiming at the task scheduling problem in cloud computing environment, this paper proposes a new list scheduling algorithm, namely, based on a virtual scheduling length (BVSL) table algorithm. The algorithm first constructs the predicted remaining length table based on the prescheduling results, then constructs a virtual scheduling length table based on the predicted remaining length table, the current task execution cost, and the actual start time of the task, and calculates the task priority based on the virtual scheduling length table to make the overall path the longest task is scheduled first, thus effectively shorten the scheduling length. Finally, the processor is selected for the task based on the predicted remaining length table. The selected processor may not be the earliest for the current task, but it can shorten the finish time of the task in the next phase and reduce the scheduling length. To verify the effectiveness of the scheduling method, experiments were carried out from two aspects: randomly generated graphs and real-world application graphs. Experimental results show that the BVSL algorithm outperforms the latest Improved Predict Priority Task Scheduling (IPPTS) and RE-18 scheduling methods in terms of makespan, scheduling length ratio, speedup, and the number of occurrences of better quality of schedules while maintaining the same time complexity.

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