scholarly journals Min-Time TS: task resource mapping algorithm in cloud computing

2021 ◽  
Vol 1055 (1) ◽  
pp. 012096
Author(s):  
G K Kamalam ◽  
T Kalaiyarasi ◽  
S V Monaa ◽  
B Gurudharshini
Keyword(s):  
Cloud Computing ◽  
Mapping Algorithm ◽  
Resource Mapping

Elastic Optical Network Service-Oriented Architecture (SOA) Used for Cloud Computing and Its Resource Mapping Optimization Scheme

2020 ◽  
Vol 15 (4) ◽  
pp. 442-449
Author(s):  
Xun Xia ◽  
Ling Chen
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Service Oriented Architecture ◽  
Optical Network ◽  
Spectrum Utilization ◽  
Mapping Algorithm ◽  
Resource Mapping ◽  
Elastic Optical Network ◽  
Service Oriented

In this study, starting from the elastic optical network, the layered and function isolated service-oriented architecture (SOA) is introduced, so as to propose an elastic optical network SOA for cloud computing, and further study the resource mapping of optical network. Linear mapping model, random routing mapping algorithm, load balancing mapping algorithm and link separation mapping algorithm are introduced respectively, and the resource utilization effect of different mapping algorithms for the proposed optical network is compared. During the experiment, firstly, the elastic optical network is tested. It is found that the node utilization and spectrum utilization of the underlying optical fiber level network are significantly improved. Within the average service time of 0.312 s∼0.416 s, the corresponding node utilization and spectrum utilization are 90% and 80% respectively. In the resource mapping experiment, load balancing algorithm and link separation algorithm can effectively improve the mapping success rate of services. Among them, the link separation mapping algorithm can improve the spectrum resource utilization of optical network by 15.6%. The elastic optical network SOA proposed in this study is helpful to improve the use of network resources.

A High-Speed Railway Data Placement Strategy Based on Cloud Computing

2011 ◽  
Vol 135-136 ◽  
pp. 43-49
Author(s):  
Han Ning Wang ◽  
Wei Xiang Xu ◽  
Chao Long Jia
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Data Access ◽  
Interval Mapping ◽  
Data Placement ◽  
Programming Algorithm ◽  
High Speed Railway ◽  
Mapping Algorithm ◽  
Data Intensive ◽  
Study Results

The application of high-speed railway data, which is an important component of China's transportation science data sharing, has embodied the typical characteristics of data-intensive computing. A reasonable and effective data placement strategy is needed to deploy and execute data-intensive applications in the cloud computing environment. Study results of current data placement approaches have been analyzed and compared in this paper. Combining the semi-definite programming algorithm with the dynamic interval mapping algorithm, a hierarchical structure data placement strategy is proposed. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices. And the dynamic interval mapping algorithm could guarantee better self-adaptability of the data storage system. It has been proved both by theoretical analysis and experiment demonstration that a hierarchical data placement strategy could guarantee the self-adaptability, data reliability and high-speed data access for large-scale networks.

Resource Mapping Algorithm Between the Layers Based on Reconfigurable Network

2013 ◽  
Vol 12 (7) ◽  
pp. 1268-1278
Author(s):  
Bin Zhuge ◽  
Li Deng ◽  
Huanhuan Song ◽  
Guowei Dai ◽  
Weiming Wang ◽  
...  
Keyword(s):  
Mapping Algorithm ◽  
Resource Mapping

scholarly journals Virtual Simulation Management of Data Traffic Optimization of Big Data Cloud Platform considering Multipoint Mapping Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Haibo Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Flow ◽  
Virtual Simulation ◽  
Data Traffic ◽  
Cloud Platform ◽  
Mapping Algorithm ◽  
Computing Center ◽  
Traffic Optimization ◽  
Multipoint Mapping

With the continuous development of Internet, cloud computing, and other technologies, build a cloud platform based on Cloud Computing Center, but how to effectively carry out operation and maintenance and face users to ensure the continuity and effectiveness of the platform is extremely important. In view of these needs and limitations, this paper introduces the multipoint mapping algorithm, combs the statistical methods of platform cloud traffic, carries out platform data traffic by classification, constructs the data traffic optimization management model, analyzes the relevant data samples, carries out statistical calculation for data diversion tasks, analyzes and processes the priority indicators, and forms the final results through continuous iteration, realizing the management of data flow optimization virtual simulation of big data cloud platform. Simulation results show that the multipoint mapping algorithm is effective and can effectively support the data flow of big data cloud platform and optimize virtual simulation management.

scholarly journals Research on Feedback-Sensitive Resource Mapping Algorithm Based On Simulated Annealing in SDN

2019 ◽  
Vol 154 ◽  
pp. 96-101
Author(s):  
Wei Guang Guo ◽  
Jun Luo ◽  
Song Han ◽  
Zu Yao Zhang ◽  
Ye Ge
Keyword(s):  
Simulated Annealing ◽  
Mapping Algorithm ◽  
Resource Mapping
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