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International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2012)

作者： Wang, Guan Yu, Haicun TangShan Vocat & Tech Coll Modern Educ Technol Ctr Tangshan Peoples R China

ISBN: (纸本)9783037856529

Task schedule algorithms directly related to the speed and quality of schedule. min-min algorithm always completes the shortest total completion time task first, and has the characteristic of simple and shortest completion time. This paper research scheduling algorithm based on min-min algorithm. The result shows that the proposed algorithm is efficient in the cloud computing environment.

关键词： Cloud Computing Task scheduling min-min algorithm algorithm simulating

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Enhanced Load Balanced min-min algorithm for Static Meta Task Scheduling in Cloud Computing 3

Enhanced Load Balanced Min-Min algorithm for Static Meta Tas...

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3rd International Conference on Recent Trends in Computing (ICRTC)

作者： Patel, Gaurang Mehta, Rutvik Bhoi, Upendra Parul Inst Engn & Technol Comp Sci & Engn Dept Vadodara Gujarat India Parul Inst Engn & Technol Informat Technl Dept Vadodara Gujarat India

For today's most demanding service of cloud computing, there are many tasks required to be executed by the available resources to achieve best performance, reduce response time and utilize resources. There is a need of designing a new task scheduling algorithm that outperform appropriate allocation map of task. to achieve these challenges. As Load Balanced min-min algorithm selects the task with minimum completion time and assigns it to appropriate resource, it sometimes does not produce better makespan and does not utilize resources effectively. This paper represents study of variety of task scheduling algorithms and modification of Load balanced min-min (ELBMM) algorithm for Static Meta-Task Scheduling. The modified algorithm is built based on comprehensive study of the impact of Load balanced min-min algorithm for Static Meta-Task Scheduling in grid computing Enhanced Load balanced min-min algorithm (ELBMM) is based on min-min strategy and tasks rescheduling to use the unutilized resources effectively. It selects the task with maximum completion time and assigns it to appropriate resource to produce better makespan and utilize resource effectively. (C) 2015 Published by Elsevier B.V.

关键词： Cloud Computing Meta Task Scheduling ELBMM min-min algorithm

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Enhanced Load Balanced min-min algorithm for Static Meta Task Scheduling in Cloud Computing

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Procedia Computer Science 2015年 57卷 545-553页

作者： Gaurang Patel Rutvik Mehta Upendra Bhoi Computer Science & Engineering Department Parul Institute of Engineering &TechnologyVadodara Guajarat India. Assistant Professor Information TechnlogyDepartment Parul Institute of Engineering &TechnologyVadodara Guajarat India. Assistant Professor Computer Science & Engineering Department Parul Institute of TechnologyVadodara Guajarat India.

For today's most demanding service of cloud computing, there are many tasks required to be executed by the available resources to achieve best performance, reduce response time and utilize resources. There is a need of designing a new task scheduling algorithm that outperform appropriate allocation map of task. to achieve these challenges. As Load Balanced min-min algorithm selects the task with minimum completion time and assigns it to appropriate resource, it sometimes does not produce better makespan and does not utilize resources effectively. This paper represents study of variety of task scheduling algorithms and modification of Load balanced min-min (ELBMM) algorithm for Static Meta-Task Scheduling. The modified algorithm is built based on comprehensive study of the impact of Load balanced min-min algorithm for Static Meta-Task Scheduling in grid computing. Enhanced Load balanced min-min algorithm (ELBMM) is based on min-min strategy and tasks rescheduling to use the unutilized resources effectively. It selects the task with maximum completion time and assigns it to appropriate resource to produce better makespan and utilize resource effectively.

关键词： Cloud Computing Meta Task Scheduling ELBMM min-min algorithm .

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User-Priority Guided min-min Scheduling algorithm For Load Balancing in Cloud Computing

User-Priority Guided Min-Min Scheduling Algorithm For Load B...

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National Conference on Parallel Computing Technologies (PARCOMPTECH)

作者： Chen, Huankai Wang, Frank Na Helian Akanmu, Gbola Univ Kent Future Comp Grp Canterbury Kent England Univ Hertfordshire Hatfield Herts England

ISBN: (纸本)9781479915897

Cloud computing is emerging as a new paradigm of large-scale distributed computing. In order to utilize the power of cloud computing completely, we need an efficient task scheduling algorithm. The traditional min-min algorithm is a simple, efficient algorithm that produces a better schedule that minimizes the total completion time of tasks than other algorithms in the literature [7]. However the biggest drawback of it is load imbalanced, which is one of the central issues for cloud providers. In this paper, an improved load balanced algorithm is introduced on the ground of min-min algorithm in order to reduce the makespan and increase the resource utilization (LBIMM). At the same time, Cloud providers offer computer resources to users on a pay-per-use base. In order to accommodate the demands of different users, they may offer different levels of quality for services. Then the cost per resource unit depends on the services selected by the user. In return, the user receives guarantees regarding the provided resources. To observe the promised guarantees, user-priority was considered in our proposed PA-LBIMM so that user's demand could be satisfied more completely. At last, the introduced algorithm is simulated using Matlab toolbox. The simulation results show that the improved algorithm can lead to significant performance gain and achieve over 20% improvement on both VIP user satisfaction and resource utilization ratio.

关键词： Cloud Computing User-priority Aware Load Balance Makespan min-min algorithm Cloud Task Scheduling

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Remote Dance Action Correction Based on EM and min-min algorithms

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MOBILE NETWORKS & APPLICATIONS 2024年 1-13页

作者： Li, Hongmei Reddy, M. Sravan Kumar Harbin Univ Sch Mus & Dance Harbin 150086 Peoples R China RGM Coll Engn & Technol Dept Comp Sci & Engn Nandyal 518501 India

In the process of community learning for remote dance teaching, to ensure that students online master the correct dance actions and skills, and to improve the quality of teaching and students' learning outcomes, this paper proposes an action correction method in remote dance teaching based on the EM and the min-min algorithms. This method takes the remote dance video as the foundation, first using principal component analysis (PCA) to segment the action sequence of the remote dance action, then inputting the segmented remote dance action into the HENet network model, and using the EM algorithm to estimate the parameters of the network. With the optimal parameters, the HENet network model is iteratively trained to extract the key joint features within the dance action. Then, a hierarchical posture extraction for dance action based on the relationship of the joint set is applied to extract the dance posture, Using the student's posture aligning the standard action, the dance action guidance vector is calculated, and the min-min algorithm is used to allocate and schedule multiple guidance vectors, thereby achieving dance action corrections. Experimental results show that the segmentation accuracy remains above 88%, and the action accuracy is improved by about 20%, reaches accuracy between 88 and 98% and real-time (8-12 ms/frame). The extraction error of key joints is effectively reduced to between 1 and 2%. All these experiments verify the significant effect of the proposed method in improving the quality and learning effectiveness of remote dance.

关键词： EM algorithm min-min algorithm Remote dance teaching Action correction HENet network model Parameter estimation

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min-min GRID SCHEDULING algorithm BASED ON SEGMENT METHOD

MIN-MIN GRID SCHEDULING ALGORITHM BASED ON SEGMENT METHOD

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2007中国宁波国际计算机科学与技术学术大会

作者： Hu Jinzhu Chen Zhiwei Du Zhiqiang Shu Jiangbo Department of Computer Science Central China Normal University

ISBN: (纸本)9780972147903

Based on the present task scheduling algorithms in grid computation,the most classical min-min algorithm is analyzed deeply in this *** flaw of load unbalance in the min-min algorithm is pointed *** solve the flaw,an improved algorithm using segment method is *** the same time,the Sect-min algorithm is also ***,the simulation using Matlab toolbox is done,which has confirmed the rationality and validity of the improved algorithm.

关键词： Grid Scheduling algorithm min-min algorithm Segment method

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An Improved min-min Grid Tasks Scheduling algorithm Based on QoS Constraints

An Improved MIN-MIN Grid Tasks Scheduling Algorithm Based on...

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2010 International Conference on Optics, Photonics and Energy Engineering (OPEE 2010)

作者： Juefu Liu1 East China Jiao Tong University Nanchang,Jiangxi,ChinaGang Li1,* East China Jiao Tong University Nanchang,Jiangxi,China

Building upon the existing researches on grid scheduling algorithm,a priority model which improves the min-min algorithm based on Qos constraints is introduced and high-priority tasks can be implemented first on condition that high QoS tasks get high QoS resources,so that the shortage of tasks with special requirements on resources can be made up and customers' need could be satisfied more compeletely.

关键词： min-min algorithm QoS Priority

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Optimization of Tasks in Cloud Computing Based on MAX-min, min-min and Priority 4

Optimization of Tasks in Cloud Computing Based on MAX-MIN, M...

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4th International Conference on Web Research (ICWR)

作者： Derakhshan, Majid Bateni, Zohreh Univ Sci & Culture Comp Engn Tehran Iran

ISBN: (纸本)9781538653647

Considering the growing use of cloud computing and the need for optimal use of resources in the cloud, and attention to users that pay for services they use based on their pay-as-you-go basis, There should be a quicker way for users to decrease the user's waiting time and task's waiting time. The main purpose of this paper is to provide an optimal algorithm using the advantages of the two traditional min-min and Max-min algorithms. The other point that follow in this algorithm (TOMMP) is the priority of the tasks. There are a lot of scheduling algorithms in the world today, but the priority given to the tasks has been neglected and overlooked in most algorithms. In this algorithm, priority is firstly selected for tasks based on a prioritization algorithm, and then using the median number to decide which one of the min-min or Max-min algorithms is to be used. It should be noted that according to the TOMMP algorithms, its waiting time is lower than comparisons of the compared algorithms and is shown to be better than the comparable algorithms.

关键词： TOMMP algorithm optimal scheduling algorithm scheduling algorithm cloud scheduling algorithm min-min algorithm Max-min algorithm cloud computing

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The Container Scheduling Method Based on the min-min in Edge Computing 19

The Container Scheduling Method Based on the Min-Min in Edge...

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4th International Conference on Big Data and Computing (ICBDC)

作者： Chen, Feifei Zhou, Xiaofeng Shi, Chao Hohai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China China Merchants Holdings Int Informat Technol Ltd Syst Integrat Dept Shenzhen Guangdong Peoples R China

ISBN: (纸本)9781450362788

With the rapid development of the Internet of Things (IoT), the number of edge devices grows exponentially. Recently, Edge computing and edge cloud data center have been proposed to solve some problem, such as delay, Quality of Service (QoS), energy consumption. Similar to the cloud data center, the edge data center will generate a lot of energy consumption. There is a large amount of literature researched the problem of cloud data center, but less focus on energy problem of the forefront file, edge data center. In order to reduce energy consumption in the edge data center, we designed a target function for physical machine's energy consumption in heterogeneous edge data center and proposed a container scheduling method based on the min-min. According to the target function, each container is placed on the physical machine with the least increase in energy consumption. Meanwhile, we specially hypothesis the happening by considering their resource utilization balance when the estimated minimum energy consumption is the same. The simulation results show that the proposed container scheduling method reduced the energy consumption generated by the physical machine hosting container up to 56.7% compared with the FirstFit.

关键词： Edge computing energy consumption container scheduling container as a service min-min algorithm

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Grouped tasks scheduling algorithm based on QoS in cloud computing network

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EGYPTIAN INFORMATICS JOURNAL 2017年第1期18卷 11-19页

作者： Ali, Hend Gamal El Din Hassan Saroit, Imane Aly Kotb, Amira Mohamed Cairo Univ Fac Comp & Informat Dept Informat Technol Giza Egypt

This paper proposes the grouped tasks scheduling (GTS) algorithm that is used to schedule tasks in cloud computing network by applying quality of service to satisfy user's needs. The proposed algorithm distributes tasks into five categories;each category has tasks with similar attributes (user type, task type, task size, and task latency). After adding tasks into right category, it starts scheduling these tasks into available services. Scheduling is done in two steps: first step is deciding which category will be scheduled first. This depends on the attributes of the tasks that belong to each category so the category that has tasks with high value of attributes will be scheduled first. Second step is deciding which task inside the chosen category will be scheduled first. This depends on the execution time of task so the task that has minimum execution time will be scheduled first. (C) 2016 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University. This is an open access article under the CC BY-NC-ND license.

关键词： Cloud computing min-min algorithm QoS Task scheduling algorithm

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