ArticlePloS one2017
Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- An intelligent job scheduling and real-time resource optimization for edge-cloud continuum in next generation networks.Scientific reports · 2025Article
- A fact based analysis of decision trees for improving reliability in cloud computing.PloS one · 2024Article
- A Cloud Computing-Based Modified Symbiotic Organisms Search Algorithm (AI) for Optimal Task Scheduling.Sensors (Basel, Switzerland) · 2022Article
- Recent advancement in VM task allocation system for cloud computing: review from 2015 to2021.Artificial intelligence review · 2022Article
- Cluster equilibrium scheduling method based on backpressure flow control in railway power supply systems.PloS one · 2020Article
- A deadline constrained scheduling algorithm for cloud computing system based on the driver of dynamic essential path.PloS one · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.