JOURNAL ARTICLE

A List-based Heuristic Algorithm for Static Task Scheduling in Heterogeneous Distributed Computing Systems

Abstract

Executing complicated computations in parallel increases the speed of computing and brings user delight to the system. Decomposing the program into several small programs and running multiple parallel processors are modeled by Directed Acyclic Graph. Scheduling nodes to execute this task graph is an important problem that will speed up computations. Since task scheduling in this graph belongs to NP-hard problems, various algorithms were developed for node scheduling to contribute to quality service delivery. The present study brought a heuristic algorithm named looking ahead sequencing algorithm (LASA) to cope with static scheduling in heterogeneous distributed computing systems with the intention of minimizing the schedule length of the user application. In the algorithm proposed here, looking ahead is considered as a criterion for prioritizing tasks. Also, a property called Emphasized Processor has been added to the algorithm to emphasize the task execution on a particular processor. The effectiveness of the algorithm was shown on few workflow type applications and the results of the algorithm implementation were compared with two more heuristic and meta-heuristic algorithms.

Keywords:
Computer science Directed acyclic graph Distributed computing Dynamic priority scheduling Scheduling (production processes) Fair-share scheduling Parallel computing Workflow Fixed-priority pre-emptive scheduling Schedule Computation Two-level scheduling Rate-monotonic scheduling Symmetric multiprocessor system Algorithm Mathematical optimization

Metrics

8
Cited By
0.85
FWCI (Field Weighted Citation Impact)
20
Refs
0.74
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture
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