Load Balancing of Nodes in Cloud Using Ant Colony Optimization
By K. Nishant, Pratik Sharma, V. Krishna, C. Gupta, Kuwar Pratap Singh, Nitin, Ravi Rastogi. 2012 UKSim 14th International Conference on Computer Modelling and Simulation, 2012
323 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems
View Paper: https://www.semanticscholar.org/paper/8a64a37f426f030266d22eaac0b9ca18bde798e1
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In Artificial Intelligence
- Zhi-hui Zhan
- Henry Shu-Hung Chung
- Jun Zhang
- Yun Li
- Yue-jiao Gong
- Jameela Al-Jaroodi
- Nader Mohamed
- Sarbjeet Singh
In Computational Theory and Mathematics
In Information Systems
- Jameela Al-Jaroodi
- Henry Shu-Hung Chung
- Nader Mohamed
- Zhi-hui Zhan
- Jun Zhang
- Inderveer Chana
- Xiao Fang Liu
- Sarbjeet Singh
Citations in the corpus
- Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches (2015, methodology): “This is finer for crossover and mutation, but it needs to be Nishant et al. [2012] also scheduled the cloud resource for an optimized load balance of different nodes, using an ACO-based algorithm.”
- A Survey on Resource Scheduling in Cloud Computing: Issues and Challenges (2016, background): “[57] proposed ACO based resource scheduling technique for load distribution of workloads to improve cost efficiency and resource utilization.”
- A review of metaheuristic scheduling techniques in cloud computing (2015, methodology): “Kumar et al. [24] modified ant colony optimization algorithm for balancing load in cloud.”
- A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms (2012, methodology): “The proposed algorithm by Kumar [9] is an improvement version of the algorithm presented in [10].”