Zhengtao Liu^{1, *}, Yi Ying¹, Yaqin Peng¹, Jinyue Xia²

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 861-871, 2020, DOI:10.32604/cmc.2020.07142 - 01 May 2020

Abstract Multi-tenant collaboration brings the challenge to access control in cloud computing environment. Based on the multi-tenant role-based access control (MTRBAC) model, a Temporal MT-RBAC (TMT-RBAC) model for collaborative cloud services is proposed. It adds the time constraint between trusted tenants, including usable role time constraint based on both calendar and interval time. Analysis shows that the new model strengthens the presentation ability of MT-RBAC model, achieves the finergrained access control, reduces the management costs and enhances the security of multitenant collaboration in cloud computing environment. More >

Tao Li¹, Xiang Li^{1, *}, Yongjun Ren², Jinyue Xia³

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 621-631, 2020, DOI:10.32604/cmc.2020.06463 - 01 May 2020

Abstract In view of the low accuracy of traditional ground nephogram recognition model, the authors put forward a k-means algorithm-acquired neural network ensemble method, which takes BP neural network ensemble model as the basis, uses k-means algorithm to choose the individual neural networks with partial diversities for integration, and builds the cloud form classification model. Through simulation experiments on ground nephogram samples, the results show that the algorithm proposed in the article can effectively improve the Classification accuracy of ground nephogram recognition in comparison with applying single BP neural network and traditional BP AdaBoost ensemble algorithm on More >

Jiaohua Qin¹, Yusi Cao¹, Xuyu Xiang^{1, *}, Yun Tan¹, Lingyun Xiang², Jianjun Zhang³

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 389-399, 2020, DOI:10.32604/cmc.2020.07819 - 30 March 2020

Abstract With the massive growth of images data and the rise of cloud computing that can provide cheap storage space and convenient access, more and more users store data in cloud server. However, how to quickly query the expected data with privacy-preserving is still a challenging in the encryption image data retrieval. Towards this goal, this paper proposes a ciphertext image retrieval method based on SimHash in cloud computing. Firstly, we extract local feature of images, and then cluster the features by K-means. Based on it, the visual word codebook is introduced to represent feature information More >

Yihe Liu¹, Aaqif Afzaal Abbasi², Atefeh Aghaei³, Almas Abbasi⁴, Amir Mosavi^{5, 6, 7}, Shahaboddin Shamshirband^{8, 9, *}, Mohammed A. A. Al-qaness¹⁰

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 31-39, 2020, DOI:10.32604/cmc.2020.07708 - 30 March 2020

Abstract Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace. Similarly, the field of health informatics is also considered as an extremely important field. This work observes the collaboration between these two fields to solve the traditional problem of extracting Electrocardiogram signals from trace reports and then performing analysis. The developed system has two front ends, the first dedicated for the user to perform the photographing of the trace report. Once the photographing is complete, mobile computing is used to extract the signal. Once the signal is extracted, More >

Weijin Jiang^{1, 2, 3}, Yang Wang^1,*, Yirong Jiang^4,*, Yuhui Xu¹, Jiahui Chen¹, Lina Tan¹, Guo Liang⁵

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 123-136, 2020, DOI:10.32604/cmc.2020.05933

Abstract In mobile cloud computing, trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud. Aiming at the security and trust management of mobile agent system in mobile cloud computing environment, the Human Trust Mechanism (HTM) is used to study the subjective trust formation, trust propagation and trust evolution law, and the subjective trust dynamic management algorithm (MASTM) is proposed. Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust 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… 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 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 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 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… More >