scholarly journals Efficient Task Scheduling for Quality of Service in Cloud Computing Network

2020 ◽  
Vol 8 (5) ◽  
pp. 3193-3196
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Response Time ◽  
Task Scheduling ◽  
Waiting Time ◽  
Threshold Values ◽  
Specific Time ◽  
Required Quality ◽  
Cloud Resources

Task scheduling in cloud is the process of allocating a resource to a task at specific time. The allocation of limited cloud resources to large number of tasks to satisfy the required quality of service is the key challenge in cloud. Allocation of a resource with less capability to a task increases the response time, makespan of the task and waiting time of the entire tasks in the waiting queue. This problem will result to an unsatisfied Quality of Service. In this paper we proposed an efficient task scheduling that uses three threshold values to specify the resource to be allocated to a task at a given time. This method ensures that a capable resource is allocated to task such that the response time and makespan of the all task are minimized. The proposed method was simulated using CloudSim and the result shows a better response time and makespan than the well known Min-Min and Max-Min Method.

scholarly journals Service Level Agreement Violation Preventive Task Scheduling for Quality of Service Delivery in Cloud Computing Environment

2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Delivery ◽  
Task Scheduling ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment

scholarly journals An Attribute-Oriented Task Scheduling Strategy for Improvement of Quality of Service in Cloud Computing

2021 ◽  
Author(s):  
Jianying Miao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Simulation Environment ◽  
Attribute Matching ◽  
Resource Allocation Strategy ◽  
And Task

This thesis describes an innovative task scheduling and resource allocation strategy by using thresholds with attributes and amount (TAA) in order to improve the quality of service of cloud computing. In the strategy, attribute-oriented thresholds are set to decide on the acceptance of cloudlets (tasks), and the provisioning of accepted cloudlets on suitable resources represented by virtual machines (VMs,). Experiments are performed in a simulation environment created by Cloudsim that is modified for the experiments. Experimental results indicate that TAA can significantly improve attribute matching between cloudlets and VMs, with average execution time reduced by 30 to 50% compared to a typical non-filtering policy. Moreover, the tradeoff between acceptance rate and task delay, as well as between prioritized and non-prioritized cloudlets, may be adjusted as desired. The filtering type and range and the positioning of thresholds may also be adjusted so as to adapt to the dynamically changing cloud environment.

scholarly journals Green Metascheduler Architecture to Provide QoS in Cloud Computing

2015 ◽  
Author(s):  
Osvaldo Adilson De Carvalho Junior ◽  
Sarita Mazzini Bruschi ◽  
Regina Helena Carlucci Santana ◽  
Marcos José Santana
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Response Time ◽  
Large Scale ◽  
Quality Of Services ◽  
Average Response ◽  
Average Response Time ◽  
Private Cloud

The aim of this paper is to propose and evaluate GreenMACC (Green Metascheduler Architecture to Provide QoS in Cloud Computing), an extension of the MACC architecture (Metascheduler Architecture to provide QoS in Cloud Computing) which uses greenIT techniques to provide Quality of Service. The paper provides an evaluation of the performance of the policies in the four stages of scheduling focused on energy consumption and average response time. The results presented confirm the consistency of the proposal as it controls energy consumption and the quality of services requested by different users of a large-scale private cloud.

An Improved Task Scheduling Algorithm Based on Multi-QoS in Cloud Computing

2014 ◽  
Vol 538 ◽  
pp. 512-515
Author(s):  
Feng Song Li ◽  
Yuan Sheng Lou
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Priority Scheduling ◽  
Task Scheduling Algorithm ◽  
Priority Function

For the issues of quality of service (QoS) in the cloud computing raised by users, this paper proposes a strategy for QoS classification and builds tasks' priority function modeling and through priority scheduling tasks, assigning tasks to the reasonable resources, and finally to complete the task efficiently, improve the utilization of resources.

scholarly journals An Approach towards Development of a Migration enabled Improved Datacenter Broker Policy

2019 ◽  
Vol 4 (3) ◽  
pp. 112-124
Author(s):  
Sourav Banerjee ◽  
Debashis Das ◽  
Ayan Kundu ◽  
Saptarshi Pal ◽  
Utpal Biswas
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Waiting Time ◽  
Load Capacity ◽  
Cloud Service ◽  
Turnaround Time ◽  
Cloud Service Provider ◽  
Allocation Policy ◽  
Critical Issues

Cloud computing has left its remarkable note on the computing world over the last few years. Through its effectiveness, litheness, scalability & availability cloud computing has changed the nature of computer system deployment. The Quality of Service (QoS)of a cloud service provider (CSP) is an important element of research interest which includes different critical issues such as proper load, minimization of waiting time, turnaround time, makespan and suppressing the wastage of bandwidth of the system. The Datacenter Broker (DCB) policy help assigning a cloudlet to a VM. In the present study, we proposed an algorithm, i.e., Migration enabled Cloudlet Allocation Policy (MCAP) for allocation of cloudlets to the VMs in a Datacenter by taking into account the load capacity of VMs and length of the cloudlets. The experimental results obtained using CloudSim toolkit under extensive loads that establish performance supremacy of MCAP algorithm over the existing algorithms.

scholarly journals DELAY DIMINISHED EFFICIENT TASK SCHEDULING AND ALLOCATION FOR HETEROGENEOUS CLOUD ENVIRONMENT

2019 ◽  
Vol 01 (01) ◽  
pp. 51-62 ◽  
Author(s):  
Bhalaji N
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Cloud Environment ◽  
Wide Range ◽  
Heterogeneous Cloud ◽  
The Way

Cloud computing being a promising paradigm has become very prominent among a wide range of applications due to their timely service rendering capability. Attracted to the type of servicing and the way of servicing lots and lots of users, adapt to the cloud computing. This makes the time servicing of the cloud computing a tedious job. So in order to effectively handle the tasks the scheduling approach is entailed in the cloud computing. The paper proposes an efficient task scheduling for the heterogeneous cloud to render service at a minimized delay utilizing the genetic algorithm. The proposed method is validated through the, cloud simulator to understand the efficiency of the same in terms of delay and the quality of service.

Quality of Service Aware Reliable Task Scheduling in Vehicular Cloud Computing

2015 ◽  
Vol 21 (3) ◽  
pp. 482-493 ◽  
Author(s):  
Tamal Adhikary ◽  
Amit Kumar Das ◽  
Md. Abdur Razzaque ◽  
Ahmad Almogren ◽  
Majed Alrubaian ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Vehicular Cloud Computing ◽  
Vehicular Cloud

scholarly journals An Attribute-Oriented Task Scheduling Strategy for Improvement of Quality of Service in Cloud Computing

2021 ◽  
Author(s):  
Jianying Miao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Task Scheduling ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Simulation Environment ◽  
Attribute Matching ◽  
Resource Allocation Strategy ◽  
And Task

This thesis describes an innovative task scheduling and resource allocation strategy by using thresholds with attributes and amount (TAA) in order to improve the quality of service of cloud computing. In the strategy, attribute-oriented thresholds are set to decide on the acceptance of cloudlets (tasks), and the provisioning of accepted cloudlets on suitable resources represented by virtual machines (VMs,). Experiments are performed in a simulation environment created by Cloudsim that is modified for the experiments. Experimental results indicate that TAA can significantly improve attribute matching between cloudlets and VMs, with average execution time reduced by 30 to 50% compared to a typical non-filtering policy. Moreover, the tradeoff between acceptance rate and task delay, as well as between prioritized and non-prioritized cloudlets, may be adjusted as desired. The filtering type and range and the positioning of thresholds may also be adjusted so as to adapt to the dynamically changing cloud environment.

Adaptive replication strategy based on popular content in cloud computing

2021 ◽  
Vol 17 (3) ◽  
pp. 273-295
Author(s):  
Imad Eddine Miloudi ◽  
Belabbas Yagoubi ◽  
Fatima Zohra Bellounar ◽  
Taieb Chachou
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Ideal Solution ◽  
On Demand ◽  
Query Response Time ◽  
Replication Strategy ◽  
New Challenges ◽  
Required Quality ◽  
Adaptive Replication

The cloud is an infrastructure that provides decentralized on-demand services. It allows consumers to pay only for the services they use. The consumer is the important entity in the cloud. The violation of the SLA contract between the consumer and the provider often leads to consequences because the service provider has to pay penalties. Data replication is emerging as an ideal solution to meet the new challenges of the cloud. This paper proposes a new replication strategy based on the popularity of data. This strategy adaptively selects the files to be replicated to improve the overall availability of data in the system, minimize query response time, and achieve the required quality of service. In addition, it dynamically determines the number of replicas to add and the best locations to store them. Experimental results show the effectiveness of the proposed strategy.

scholarly journals Quality of Service based Task Scheduling Algorithms in Cloud Computing

2017 ◽  
Vol 7 (2) ◽  
pp. 1088 ◽  
Author(s):  
Sirisha Potluri ◽  
Katta Subba Rao
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Load Balancing ◽  
Task Scheduling ◽  
Scheduling Algorithms ◽  
Task Time ◽  
The Cost

<p>In cloud computing resources are considered as services hence utilization of the resources in an efficient way is done by using task scheduling and load balancing. Quality of service is an important factor to measure the trustiness of the cloud. Using quality of service in task scheduling will address the problems of security in cloud computing. This paper studied quality of service based task scheduling algorithms and the parameters used for scheduling. By comparing the results the efficiency of the algorithm is measured and limitations are given. We can improve the efficiency of the quality of service based task scheduling algorithms by considering these factors arriving time of the task, time taken by the task to execute on the resource and the cost in use for  the communication.</p>

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