Dynamic and Adaptive Fault Tolerant Scheduling With QoS Consideration in Computational Grid

Haider, Sajjad; Nazir, Babar

doi:10.1109/access.2017.2690458

Cited by 14 publications

(5 citation statements)

References 18 publications

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“…A fault-tolerant scheduling technique with QoS constraints was proposed by S. Haider et al [25]. A job scheduling system for Hadoop was developed by Mbarka Soualhia et al [27].…”

Section: ░ 2 Literature Reviewmentioning

confidence: 99%

Designing and Implementation of Failure-Aware Based Approach for Task Scheduling in Grid Computing

Singh

Kumar

2022

IJEER

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Grid computing makes large-scale computations easier to handle. In heterogeneous systems like grid computing, failure is inevitable. Because of the volume and diversity of the resources, scheduling algorithm is among the most difficult challenges to overcome in grid computing. To reduce the make-span of the job to be executed a thorough understanding of scheduling in grid is important. Say there are two computing nodes that aren't being used right now. The scheduler may choose the node that has higher computing strength (for example, higher CPU speed, higher free memory), even though this node may also have high potential of failure. High potential of failure refers to the possibility of the failure occurring at execution time, resulting in the decrease of system performance. Therefore, awareness of failure is also very important in scheduling. This work proposes and implements a failure-aware scheduling method to schedule the tasks which uses both performance factors and failure factors of resources while making scheduling decision. The proposed algorithm is analyzed over various performance matrices and it shows considerably improved performance over existing algorithm

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“…A fault-tolerant scheduling technique with QoS constraints was proposed by S. Haider et al [25]. A job scheduling system for Hadoop was developed by Mbarka Soualhia et al [27].…”

Section: ░ 2 Literature Reviewmentioning

confidence: 99%

Designing and Implementation of Failure-Aware Based Approach for Task Scheduling in Grid Computing

Singh

Kumar

2022

IJEER

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“…Some researchers proposed fault tolerance-based proactive and reactive scheduling in the cloud through which the resource scheduler selects the resources based on their location, availability, and reliability. It mainly focuses on the mean type between availability and allocating such resources for the task execution purpose and improving the QoS [18,19]. The workflow application's execution in the cloud becomes more and more attractive because ondemand computing resources can be workflow applications enabled.…”

Section: Related Workmentioning

confidence: 99%

Threshold based VM Placement Technique for Load Balanced Resource Provisioning using Priority Scheme in Cloud Computing

Sohani¹,

Jain²

2021

IJCNC

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The unbalancing load issue is a multi-variation, multi-imperative issue that corrupts the execution and productivity of processing assets. Workload adjusting methods give solutions of load unbalancing circumstances for two bothersome aspects over-burdening and under-stacking. Cloud computing utilizes planning and workload balancing for a virtualized environment, resource partaking in cloud foundation. These two factors must be handled in an improved way in cloud computing to accomplish ideal resource sharing. Henceforth, there requires productive resource, asset reservation for guaranteeing load advancement in the cloud. This work aims to present an incorporated resource, asset reservation, and workload adjusting calculation for effective cloud provisioning. The strategy develops a Priority-based Resource Scheduling Model to acquire the resource, asset reservation with threshold-based load balancing for improving the proficiency in cloud framework. Extending utilization of Virtual Machines through the suitable and sensible outstanding task at hand modifying is then practiced by intensely picking a job from submitting jobs using Priority-based Resource Scheduling Model to acquire resource asset reservation. Experimental evaluations represent, the proposed scheme gives better results by reducing execution time, with minimum resource cost and improved resource utilization in dynamic resource provisioning conditions.

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“…ns better = arg min ns max 1≤ns≤m np T np (13) where P np is the processor that the tasks are allocated to. Eq.…”

Section: Local Searchmentioning

confidence: 99%

Off-Line Time Aware Scheduling of Bag-of-Tasks on Heterogeneous Distributed System

Xuan

Wei

et al. 2019

IEEE Access

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The resource allocation for bag-of-tasks in the heterogeneous distributed system is to distribute the tasks to proper processors such that the makespan is minimized. It is a well-known NP-hard problem, and is even more complex and challenging when the processors have off-line time. To tackle this challenging problem, first, we set up a mathematical model for this problem which minimizes the makespan of the bag-oftasks with the off-line time segment of the processors. Second, to solve the model efficiently, we propose two new algorithms: a new scheduling algorithm referred to as sorting-allocation-pulling scheduling algorithm which first allocate the tasks to available time segment on proper processors and then pulls them to the formerly available time segment for the sake of minimizing the makespan, and an effective genetic algorithm with a novel local search operator and a well-designed modify operator. Finally, the numerical simulation experiments are conducted, and the two proposed algorithms are compared. The experimental results indicate the effectiveness of the proposed model and algorithms. INDEX TERMS Distributed computing, task scheduling, bag-of-tasks, generic algorithm.

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Dynamic and Adaptive Fault Tolerant Scheduling With QoS Consideration in Computational Grid

Cited by 14 publications

References 18 publications

Designing and Implementation of Failure-Aware Based Approach for Task Scheduling in Grid Computing

Designing and Implementation of Failure-Aware Based Approach for Task Scheduling in Grid Computing

Threshold based VM Placement Technique for Load Balanced Resource Provisioning using Priority Scheme in Cloud Computing

Off-Line Time Aware Scheduling of Bag-of-Tasks on Heterogeneous Distributed System

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