A Qos Guided Task Scheduling Model in Cloud Computing Environment

Han, Haoxue; Deyui, Qi; Zheng, Weiye; Feng, Bin

doi:10.1109/eidwt.2013.17

Cited by 22 publications

(9 citation statements)

References 8 publications

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“…They have worked on cost and makespan and concluded that their proposed algorithm is effective in terms of both specified objectives. • Sufferage Min Han et al [43] have presented this algorithm in which they have divided the QoS objectives in two different stages that are "High QoS level" and "Low QoS level". To bolster this algorithm, at first step, sufferage number is computed for every task before the execution of scheduling and sorting is done according to maximum sufferage value.…”

Section: Heuristic Algorithmsmentioning

confidence: 99%

Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

et al. 2018

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Workflow scheduling concerns the mapping of complex tasks to cloud resources by taking into account various Quality of Service requirements. In virtue of continuous proliferation in the exploration of cloud computing, it has become stringent to find the proper scheduling scheme for the execution of workflow under user specifications. Moreover, till date, there exists no systematic review of the existing numerous techniques for this NP-complete problem in the cloud. Taking this into account, the present study seeks to address this gap and spotlights the comprehensive taxonomy of various scheduling schemes as well as extensively compares them by illuminating their objectives, features, merits, and demerits. This paper also highlights the future research challenges with an aim to foster more research in the realm of workflow scheduling as an optimization task.

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Section: Heuristic Algorithmsmentioning

confidence: 99%

Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

et al. 2018

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“…Thus, based on the QoS requirements of user tasks, the features information of virtual machine VM i can be abstracted into some feature information granules , representing CPU, GPU, memory and bandwidth information granule, and so forth. Similarly, for user tasks and resource availability, we create different classification and fuzzy equivalence classes [21]. As shown in Figure 3, when the system has multiple user tasks arriving, firstly the tasks are sorted in accordance with the tasks submission sequence and then the first come first serve (FCFS) queue is adopted.…”

Section: Dynamic Resource Scheduling Based On Fuzzy Control Theorymentioning

confidence: 99%

A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

Zhijia

Zhu

et al. 2015

Journal of Control Science and Engineering

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The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic resource scheduling method based on fuzzy control theory. Firstly, the resource requirements prediction model is established. Then the relationships between resource availability and the resource requirements are concluded. Afterwards fuzzy control theory is adopted to realize a friendly match between user needs and resources availability. Results show that this approach improves the resources scheduling efficiency and the quality of service (QoS) of cloud computing.

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“…A QoS guided task scheduling model, composed of scheduling strategies and QoS guided scheduling Sufferage-min heuristic algorithm was presented by Han et al, [21]. Experiment revealed that make span value was successfully shortened.…”

Section: Related Workmentioning

confidence: 99%

Trust Based Resource Selection in Cloud Computing Using Hybrid Algorithm

Kumar¹,

Aramudhan²

2015

IJISA

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Abstract-Cloud computing is experiencing rapid advancement in academia and industry. This technology offers distributed, virtualized and elastic resources as utilities for end users and can support full recognition of "computing as a utility" in the future. Scheduling distributes resources among parties which simultaneously and asynchronously seek it. Scheduling algorithms are meant for scheduling and they reduce resource starvation ensuring fairness among those using resources. Most Task-scheduling cloud computing procedures consider task resource requirements for CPU and memory, and not bandwidth. This study suggests optimizing scheduling with BAT-Harmony search hybrid algorithm.

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A Qos Guided Task Scheduling Model in Cloud Computing Environment

Cited by 22 publications

References 8 publications

Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

Trust Based Resource Selection in Cloud Computing Using Hybrid Algorithm

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