Swarm intelligence-based task scheduling algorithm for load balancing in cloud system

Komalavalli, D.; T., Padma

doi:10.1504/ijenm.2021.112669

Cited by 4 publications

(2 citation statements)

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“…Dynamic balancing can dynamically adjust the number of tasks of each node during operation according to the node load, and can also dynamically adjust according to the response time and load conditions of each node [15][16]. Through load balancing, cluster resources can be maximized, so in practical applications, load The balancing implementation adopts dynamic load balancing [7][8].…”

Section: Load Balancer and Load Balancing Algorithmmentioning

confidence: 99%

Development Process of Distributed System Based on Load Balancing Fault Tolerant Scheduling Algorithm

2022

DPS

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With the rapid development of the Internet and the advancement of information technology, the server storage model is difficult to cope with the storage and management of data by companies or departments, and the file system becomes more and more complex. The purpose of this paper is to study the distributed system development process of fault-tolerant scheduling algorithm based on load balancing. This paper takes the distributed file system as the research object, points out the load skew problem in the process of load balancing, and analyzes the reason according to the file system architecture and design concept. Based on the concepts of static load balancing and dynamic load balancing, an optimal load balancing algorithm of FastDFS is proposed. The algorithm can not only ensure the load sharing ability of the system, improve the stability of the system, but also prevent the load imbalance in the process of linear expansion of the system, and overcome the original load balancing problem. Experiments show that the distributed system constructed in this paper has better resource scheduling performance, and the real-time load is also optimized to some extent.

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Section: Load Balancer and Load Balancing Algorithmmentioning

confidence: 99%

Development Process of Distributed System Based on Load Balancing Fault Tolerant Scheduling Algorithm

2022

DPS

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“…With the evolution of technologies and mainly of computational techniques, more precise and diverse proposals have been developed that have facilitated the generation of analysis with a greater degree of precision. Adopting different names in function of its creator and its way of functioning: Genetic Algorithms (Zhang et al, 2021), Ant colony optimization algorithm (Zha & Zeng, 2013;Zheng et al, 2019), Particle jam (Jian-sha et al, 2009;Komalavalli & Padma, 2021), among others. These new proposals have resulted in the original or traditional procedures being relatively obsolete.…”

Section: Introductionmentioning

confidence: 99%

Optimization of heterogeneous capacities considering the profit margin per product

Pérez-Campdesuñer

Sánchez-Rodríguez

García-Vidal

et al. 2023

IJRBS

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This paper aims to present a proposal to improve this methodology for the analysis of heterogeneous capacities based on the profit margin per product. Which was structured in three moments: development of the proposal, deployment in a business context, and validation of the results through the application of a linear programming method. This proposal considers the five initial steps of the existing tools as a starting point, taking as a reference the normal time available for each homogeneous group and introducing modifications in the steps. The application of the methodology in the conditions of SMEs demonstrated its ability to generate results superior to those of traditional methods and similar to those obtained by specific linear programming techniques.

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An Optimal Server Selection Model for Dynamic Task Allocation in Cloud

Komalavalli,

Padma

2023

Algorithms for Intelligent Systems

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Swarm intelligence-based task scheduling algorithm for load balancing in cloud system

Cited by 4 publications

References 0 publications

Development Process of Distributed System Based on Load Balancing Fault Tolerant Scheduling Algorithm

Development Process of Distributed System Based on Load Balancing Fault Tolerant Scheduling Algorithm

Optimization of heterogeneous capacities considering the profit margin per product

An Optimal Server Selection Model for Dynamic Task Allocation in Cloud

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