Proceedings Article10.1109/CCWC51732.2021.9376146
Towards Optimizing Task Scheduling Process in Cloud Environment
Yong Shi,Kun Suo,Jameson Hodge,Divya Pramasani Mohandoss,Steven Kemp +4 more
- 27 Jan 2021
- pp 81-87
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TL;DR: In this paper, the authors proposed a novel cloud task scheduling algorithm that augments the performance of the classical Sufferage algorithm, which is called BSufferage, to reduce completion times, increase throughput, and improve load balancing.
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Abstract: The cloud computing paradigm offers many advantages over traditional self-hosting computing solutions by abstracting computations from infrastructure. An essential task for any cloud provider is task scheduling, wherein tasks are assigned to computing resources within the cloud system by a broker. Numerous cloud task scheduling algorithms exist including Min-Min, Max-Min, and Sufferage-though each is defined by performance trade-offs. BSufferage is proposed as a novel cloud task scheduling algorithm that augments the performance of the classical Sufferage algorithm. Modeling the algorithm using the open source CloudSim package and comparing it to its precursor yields performance results for BSufferage-demonstrating decreased completion times, increased throughput, and improved load balancing of resources.
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Citations
Optimization of Max-Min and Min-Min Task Scheduling Algorithms Using G.A in Cloud Computing
31 May 2022
TL;DR: In this article , a hybrid task scheduling consisting of three algorithms, Min-Min, Max-Min and Genetic algorithm, is proposed to reduce makespan and optimize the load balances between resources.
10
Quantum Inspired Task Optimization for IoT Edge Fog Computing Environment
TL;DR: In this article , a Quantum Computing-inspired optimization technique for efficient task allocation in an edge computing environment for real-time IoT applications is proposed, where the QNN-Neural Network Model is employed for predicting optimal computing nodes for delivering realtime services and simulations are performed by employing 6, 10, 14, and 20 edge nodes at different times to schedule more than 600 heterogeneous tasks.
Optimization of Max-Min and Min-Min Task Scheduling Algorithms Using G.A in Cloud Computing
Ismael Salih Aref,Juliet Kadum,Amaal Kadum +2 more
- 31 May 2022
TL;DR: A hybrid task scheduling consisting of three algorithms Min-Min scheduling, Max- Min scheduling, and genetic algorithm is proposed to reduce Makespan and optimize the load balances between resources.
7
Prioritized scheduling technique for healthcare tasks in cloud computing
TL;DR: Prioritized Sorted Task-Based Allocation (PSTBA) as discussed by the authors is a new task scheduling and allocation technique for healthcare monitoring implemented in IoT cloud-based architecture, which selects the best virtual machine to execute the health task considering multiple factors such as; the wait time of the VM and the expected processing time (EPT) of the task as well as its criticality.
Evaluation of Task Scheduling Algorithms in Heterogeneous Computing Environments.
TL;DR: In this article, the authors established a set of methodologies to evaluate the performance of any task scheduling policy in heterogeneous computing contexts and formally state a scheduling model for hybrid edge-cloud computing ecosystems and conduct simulation-based experiments on large workloads.
4
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