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Cited by 88Cloud Computing and Resource ManagementDistributed and Parallel Computing SystemsMetaheuristic Optimization Algorithms Research

The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

Load Balancing Based Task Scheduling with ACO in Cloud Computing

Gupta, Ashish, Garg, Ritu·2017·2017 International Conference on Computer and Applications (ICCA)
DOI 10.1109/comapp.2017.8079781
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Abstract

Scheduling in Cloud computing infrastructure contain several challenging issues like computation time, budget, load balancing etc. Out of them, load balancing is one the major challenges for Cloud platform. Load balancing basically balances the load to achieve higher throughput and better resource utilization. Since scheduling task is NP-complete problem, so heuristic and meta heuristic approaches are preferred options to solve the same. In this paper, we chose a meta-heuristic approach of Ant colony optimization algorithm to solve the task scheduling problem in cloud environment focussing mainly on two objectives, i.e., minimizing the makespan/ computation time and better load balancing. Comparative analysis shows that proposed load balancing ant colony optimization algorithm (LB-ACO) provides better results than NSGA-II algorithm by providing better load balancing and less makespan. Simulations have been carried out using CloudSim Toolkit.

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Research works printed but not linked: 2

  1. jamaludin, 2007, A Background Study on Ant Colony Optimization Metaheuristic and its Application Principles in Resolving Three Combinatorial Optimization Problem
  2. 10.1109/CIMA.2005.1662313 · DOI

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Metadata

Authors
Gupta, A., & Garg, R.
Affiliations
National Institute of Technology Kurukshetra (IN)
ORCID
Venue
2017 International Conference on Computer and Applications (ICCA)
Publisher
IEEE
Published
2017-09
Pages
174-179
DOI
10.1109/comapp.2017.8079781
OpenAlex
W2766515570
Cited by
88
References
21
Citations by year
2026: 2 · 2025: 6 · 2024: 12 · 2023: 14 · 2022: 17 · 2021: 10 · 2020: 8 · 2019: 10 · 2018: 9
FWCI
5.67
Type
conference paper
Language
en
Open access
closed
Locations
International Conference on Computer and Applications (ICCA) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
  • Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
Keywords
task scheduling, load balancing, ant colony optimization, cloud computing, makespan minimization, resource utilization, metaheuristic optimization, NSGA-II comparison, CloudSim

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CoChat. (2026). Citation check: Load Balancing Based Task Scheduling with ACO in Cloud Computing. https://app.cochat.ai/papers/10.1109/comapp.2017.8079781
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Gupta, A., & Garg, R. (2017). Load Balancing Based Task Scheduling with ACO in Cloud Computing. 2017 International Conference on Computer and Applications (ICCA). https://doi.org/10.1109/comapp.2017.8079781

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.