Lini Cai^∗

Computer Systems Science and Engineering, Vol.35, No.3, pp. 183-189, 2020, DOI:10.32604/csse.2020.35.183

Abstract In this paper, we use modern education concept and satisfaction theory to study the construction of a system used to evaluate Japanese teaching quality based on a satisfaction model. We use a cloud computing platform to mine the rules of Japanese teaching quality satisfaction by using an improved Apriori algorithm to explore the impact of measurement indicators of teaching objectives, processes and results on overall satisfaction with Japanese teaching practices, so as to improve Japanese teaching in the future. Scientific decision-making, improvement of teaching practices, transformation and innovation of students’ learning methods provide data reference and theoretical support. More >

Vaibhav Pandey^∗, Poonam Saini^†

Computer Systems Science and Engineering, Vol.34, No.6, pp. 357-376, 2019, DOI:10.32604/csse.2019.34.357

Abstract The cloud computing paradigm facilitates a finite pool of on-demand virtualized resources on a pay-per-use basis. For large-scale heterogeneous distributed systems like a cloud, scheduling is an essential component of resource management at the application layer as well as at the virtualization layer in order to deliver the optimal Quality of Services (QoS). The cloud scheduling, in general, is an NP-hard problem due to large solution space, thus, it is difficult to find an optimal solution within a reasonable time. In application layer scheduling, the tasks are mapped to logical resources (i.e., virtual machines), aiming to optimize one or more… More >

Haiyang Zhang¹, Guolong Chen², Xianwei Li^2,3,*

Computer Systems Science and Engineering, Vol.34, No.4, pp. 249-254, 2019, DOI:10.32604/csse.2019.34.249

Abstract As a new computing paradigm, cloud computing has received much attention from research and economics fields in recent years. Cloud resources can be priced according to several pricing options in cloud markets. Usage-based and reserved pricing schemes are commonly adopted by leading cloud service providers (CSPs) such as Amazon and Google. With more and more CSPs entering cloud computing markets, the pricing of cloud resources is an important issue that they need to consider. In this paper, we study how to segment cloud resources using hybrid pricing schemes in order to obtain the maximum revenue by means of optimal pricing… More >

Abid Nisar¹, Waheed Iqbal^1,*, Fawaz Bokhari¹, Faisal Bukhari¹, Khaled Almustafa²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 353-365, 2020, DOI:10.31209/2019.100000159

Abstract The adaptive resource provisioning of cloud-hosted applications is enabled to provide a better quality of services to the users of applications. Most of the cloud-hosted applications follow the multi-tier architecture model. However, it is challenging to adaptively provision the resources of multi-tier applications. In this paper, we propose an auto-scaling method to dynamically scale resources for multi-tier web applications. The proposed method exploits the horizontal scaling at the web server tier and vertical scaling at the database tier dynamically to maintain response time guarantees. We evaluated our proposed method on Amazon Web Services using a real web application. The extensive… More >

Kiranbir Kaur^{1, *}, Sandeep Sharma¹, Karanjeet Singh Kahlon²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1625-1647, 2020, DOI:10.32604/cmc.2020.011535

Abstract Vendor lock-in can occur at any layer of the cloud stack-Infrastructure, Platform, and Software-as-a-service. This paper covers the vendor lock-in issue at Platform as a Service (PaaS) level where applications can be created, deployed, and managed without worrying about the underlying infrastructure. These applications and their persisted data on one PaaS provider are not easy to port to another provider. To overcome this issue, we propose a middleware to abstract and make the database services as cloud-agnostic. The middleware supports several SQL and NoSQL data stores that can be hosted and ported among disparate PaaS providers. It facilitates the developers… More >

Dong Huang^a,b, Yong Bai^b, Jingcheng Liu^c, Hongtao Chen^d, Jinghua Lin^d, Jingjing Wu^d

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 883-889, 2018, DOI:10.1080/10798587.2017.1327634

Abstract With limited homogeneous and heterogeneous resources in a cloud computing system, it is not feasible to successively expand network infrastructure to adequately support the rapid growth in the cloud service. In this paper, an approach for optimal transmission of hierarchical network for heterogeneous service in Cloud Scenarios was presented. Initially, the theoretical optimal transmission model of a common network was transformed into the hierarchical network with the upper and lower optimization transmission model. Furthermore, the computation simplification and engineering transformation were presented for an approximation method at the low cost of computational complexity. In the final section, the average delay… More >

Sayed Chhattan Shah

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 285-298, 2018, DOI:10.1080/10798587.2017.1280995

Abstract Grid and cloud computing systems have been extensively used to solve large and complex problems in science and engineering fields. These systems include powerful computing resources that are connected through high-speed networks. Due to the recent advances in mobile computing and networking technologies, it has become feasible to integrate various mobile devices, such as robots, aerial vehicles, sensors, and smart phones, with grid and cloud computing systems. This integration enables the design and development of the next generation of applications by sharing of resources in mobile environments and introduces several challenges due to a dynamic and unpredictable network. This paper… More >

Yang Li¹, Jianjiang Li¹, Peng Shi², Xiaoning Qin³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 615-624, 2019, DOI:10.31209/2019.100000116

Abstract The applications to process large amounts of materials scientific data at different scales, have been placed the field of materials science on the verge of a revolution. This domain faces serious challenges, including diversity of format of scientific data, and missing unified platform for sharing. A Virtual DataSpace model and the evolution model is introduced to organize heterogeneous data according to the user requirements and track the variations of data. The open cloud model is embedded in a materials scientific data sharing platform in our experiments to verify its effectiveness. The results show the model has made efforts making more… More >

Tongmao Ma^1,2, Shanchen Pang¹, Weiguang Zhang¹, Shaohua Hao¹

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115

Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >

Yu Zhang^1,2, Yan-Ge Wang¹, Yan-Ping Bai³, Yong-Zhen Li^1,4, Zhao-Yong Lv⁵, Hong-Wei Ding⁶

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 561-572, 2019, DOI:10.31209/2019.100000111

Abstract Rockburst phenomenon is a kind of phenomenon that the rock is out and ejected because the mineral was dug out, and the original force balance was destroyed in the process of mineral exploitation. From 2007, GeoLab (abbreviation of State Key Laboratory in China for GeoMechanics and Deep Underground Engineering) had made a series of important achievements in rockburst. Up to now, GeoLab’s rockburst experiment data is reached 800T, and these data may occupy about 2PB hard disk space after analyzed. At this ratio, GeoLab need to buy a new hard disk to save all these data every 46 hours rockburst… More >