Chaotic social spider algorithm for load balance aware task scheduling in cloud computing

Xavier, V. M. Arul; Annadurai, S.

doi:10.1007/s10586-018-1823-x

Cited by 50 publications

(29 citation statements)

References 24 publications

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“…Arul Xavier and Annadurai have presented a new task scheduling mechanism based on a meta‐heuristic algorithm to minimize makespan and cost and improve resource utilization in the cloud. CloudSim simulation results proved the ability of this mechanism.…”

Section: Analysis Of Task Scheduling Approachesmentioning

confidence: 99%

Task scheduling mechanisms in cloud computing: A systematic review

Motlagh

Movaghar

Rahmani

2019

Int J Communication

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Summary Today, cloud computing has developed as one of the important emergent technologies in communication and Internet. It offers on demand, pay per use access to infrastructure, platforms, and applications. Due to the increase in its popularity, the huge number of requests need to be handled in an efficient manner. Task scheduling as one of the challenges in the cloud computing supports the requests for assigning a particular resource so as to perform effectively. In the resource management, task scheduling is performed where there is the dependency between tasks. Many approaches and case studies have been developed for the scheduling of these tasks. Up to now, a systematic literature review (SLR) has not been presented to discover and evaluate the task scheduling approaches in the cloud computing environment. To overcome, this paper presents an SLR‐based analysis on the task scheduling approaches that classify into (a) single cloud environments that evaluate cost‐aware, energy‐aware, multi‐objective, and QoS‐aware approaches in task scheduling; (b) multicloud environment that evaluates cost‐aware, multi‐objective, and QoS‐aware task scheduling; and (c) mobile cloud environment that is energy‐aware and QoS‐aware task scheduling. The analytical discussions are provided to show the advantages and limitations of the existing approaches.

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Section: Analysis Of Task Scheduling Approachesmentioning

confidence: 99%

Task scheduling mechanisms in cloud computing: A systematic review

Motlagh

Movaghar

Rahmani

2019

Int J Communication

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“…In the research of task scheduling algorithms aimed at load balancing, Arul Xavier and others proposed a cloud computing load balancing task aware scheduling algorithm for the task scheduling problems in various heterogeneous virtual machines [12]. In [13], by analyzing and comparing some cluster load balancing algorithms, a task load balancing scheduling algorithm based on ant colony optimization (WLB-ACO) was proposed.…”

Section: Related Workmentioning

confidence: 99%

Ant Colony Optimization Task Scheduling Algorithm for SWIM Based on Load Balancing

2019

Future Internet

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This paper focuses on the load imbalance problem in System Wide Information Management (SWIM) task scheduling. In order to meet the quality requirements of users for task completion, we studied large-scale network information system task scheduling methods. Combined with the traditional ant colony optimization (ACO) algorithm, using the hardware performance quality index and load standard deviation function of SWIM resource nodes to update the pheromone, a SWIM ant colony task scheduling algorithm based on load balancing (ACTS-LB) is presented in this paper. The experimental simulation results show that the ACTS-LB algorithm performance is better than the traditional min-min algorithm, ACO algorithm and particle swarm optimization (PSO) algorithm. It not only reduces the task execution time and improves the utilization of system resources, but also can maintain SWIM in a more load balanced state.

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“…The overall makespan during the scheduling is minimized by using a weight-based random selection method. The best virtual machine is finding out by using global intelligent searching [9]. S. Chenthara et al, proposed an ensure privacy and security of electronic health records (EHRs) in the cloud.…”

Section: Literature Surveymentioning

confidence: 99%

Workflow scheduling and reliability improvement by hybrid intelligence optimization approach with task ranking

Khurana¹,

Singh²

2018

ICST Transactions on Scalable Information Systems

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Workflow scheduling is one of the most challenging tasks in cloud computing. It uses different workflows and quality of service requirements based on the deadline and cost of the tasks. The main goal of workflow scheduling algorithm is to optimize the time and cost by using virtual machine migration. This algorithm computes the subset problem and decision problem in NP time. It works on the decision-making process to reduce the time and cost of computation on the server side. This paper proposes hybrid optimization to optimize the virtual machine locally and globally. The PEFT algorithm is used for initialization and worked as a heuristic algorithm. This algorithm reduces the error of random initialization of optimization. The proposed algorithm based upon Flower pollination with Grey Wolf Optimization using hybrid approach shows significant end effective results than flower pollination with genetic algorithm. The proposed approach also considered the reliability parameter on different workflows.

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Chaotic social spider algorithm for load balance aware task scheduling in cloud computing

Cited by 50 publications

References 24 publications

Task scheduling mechanisms in cloud computing: A systematic review

Task scheduling mechanisms in cloud computing: A systematic review

Ant Colony Optimization Task Scheduling Algorithm for SWIM Based on Load Balancing

Workflow scheduling and reliability improvement by hybrid intelligence optimization approach with task ranking

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