检索结果-内蒙古大学图书馆

A self-protecting agents based model for high-performance mobile-cloud computing

COMPUTERS & SECURITY 2018年 77卷 380-396页

作者： Angin, Pelin Bhargava, Bharat Ranchal, Rohit Middle East Tech Univ Dept Comp Engn Ankara Turkey Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA IBM Watson Hlth Cloud Cambridge MA USA

mobile-cloud computing (MCC) allows devices with resource and battery limitations to achieve computation-intensive tasks in real-time. While this new paradigm of computing seems beneficial for real-time mobile computing, existing MCC models mainly rely on keeping full clones of program code at remote sites and unstandardized/uninteroperable environments, hampering wider adoption. Moreover, the security risks arising from offloading data and code to an untrusted platform and the computational overhead introduced by complex security mechanisms stand as deterrents for adoption of MCC at large. In this paper, we present a context-dependent computation-offloading model for MCC, which is based on application segments packed into autonomous agents. This approach only requires isolated execution containers in the cloud to provide a runtime environment for the agents, and minimal involvement of the mobile platform during the computation process. The agents in the proposed model are able to protect themselves from tampering using integrity-checkpointing and an authenticated encryption-based communication mechanism. Experiments with two mobile applications demonstrate the effectiveness of the approach for high-performance, secure MCC. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： mobile-cloud computing Tamper resistance Autonomous agents Performance Security

来源：评论

学校读者我要写书评

暂无评论

Enhanced dynamic credential generation scheme for protection of user identity in mobile-cloud computing

引用

JOURNAL OF SUPERcomputing 2013年第3期66卷 1687-1706页

作者： Khan, Abdul Nasir Kiah, M. L. Mat Madani, Sajjad A. Khan, Atta ur Rehman Ali, Mazhar Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur Malaysia COMSATS Inst Informat Technol Dept Comp Sci Abbottabad Pakistan N Dakota State Univ Dept Elect & Comp Engn Fargo ND 58105 USA

To improve the resource limitation of mobile devices, mobile users may utilize cloud-computational and storage services. Although the utilization of the cloud services improves the processing and storage capacity of mobile devices, the migration of confidential information on untrusted cloud raises security and privacy issues. Considering the security of mobile-cloud-computing subscribers' information, a mechanism to authenticate legitimate mobile users in the cloud environment is sought. Usually, the mobile users are authenticated in the cloud environment through digital credential methods, such as password. Once the users' credential information theft occurs, the adversary can use the hacked information for impersonating the mobile user later on. The alarming situation is that the mobile user is unaware about adversary's malicious activities. In this paper, a light-weight security scheme is proposed for mobile user in cloud environment to protect the mobile user's identity with dynamic credentials. The proposed scheme offloads the frequently occurring dynamic credential generation operations on a trusted entity to keep minimum processing burden on the mobile device. To enhance the security and reliability of the scheme, the credential information is updated frequently on the basis of mobile-cloud packets exchange. Furthermore, the proposed scheme is compared with the existing scheme on the basis of performance metrics i.e. turnaround time and energy consumption. The experimental results for the proposed scheme showed significant improvement in turnaround time and energy consumption as compared to the existing scheme.

关键词： cloud computing mobile-cloud computing Security Privacy

来源：评论

学校读者我要写书评

暂无评论

JavaScript Offloading for Web Applications in mobile-cloud computing 3

JavaScript Offloading for Web Applications in Mobile-Cloud C...

引用

IEEE 3rd International Conference on mobile Services MS

作者： Yu, Meihua Huang, Gang Wang, Xudong Zhang, Ying Chen, Xiangqun Peking Univ Sch Elect Engn & Comp Sci Minist Educ Key Lab High Confidence Software Technol Beijing Peoples R China

ISBN: (纸本)9781467372848

Current mobile Web applications (a.k.a, mobile Web apps) become quite computation-intensive by involving complex JavaScript, e.g., data analytic applications and AI games, etc. In the context of mobile-cloud computing, computation offloading is a promising solution to improve performance and user experiences for mobile devices, and a lot of research efforts have been made for native apps. However, very few attentions have been paid on mobile Web apps. Compared to native apps, the dynamic feature of Web apps poses some challenging issues for computation offloading. To address these issues, this paper presents a systematic approach for augmenting JavaScript-based mobile Web apps. Our approach proposes a programming abstraction to extract "offloadable" computation-intensive portions for facilitating Web developers to define when an offloading can occur. We implement a browser-based offloading runtime service and deploy it as a front-end proxy on cloud, to automatically partition the Web apps afore the mobile devices. We demonstrate the efficiency of our approach with some typical computation-intensive Web apps across various high-end and low-end hardware specifications under Wi-Fi and cellular networks.

关键词： mobile Web apps JavaScript Offloading mobile-cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Self-Cloning Agents Based Model for High-Performance mobile-cloud computing 8

A Self-Cloning Agents Based Model for High-Performance Mobil...

引用

IEEE 8th International Conference on cloud computing

作者： Angin, Pelin Bhargava, Bharat Jin, Zhongjun Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA Univ Michigan Dept Comp Sci & Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9781467372879

The rise of the mobile-cloud computing paradigm in recent years has enabled mobile devices with processing power and battery life limitations to achieve complex tasks in real-time. While mobile-cloud computing is promising to overcome the limitations of mobile devices for real-time computing, the lack of frameworks compatible with standard technologies and techniques for dynamic performance estimation and program component relocation makes it harder to adopt mobile-cloud computing at large. Most of the available frameworks rely on strong assumptions such as the availability of a full clone of the application code and negligible execution time in the cloud. In this paper, we present a dynamic computation offloading model for mobile-cloud computing, based on autonomous agents. Our approach does not impose any requirements on the cloud platform other than providing isolated execution containers, and it alleviates the management burden of offloaded code by the mobile platform using stateful, autonomous application partitions. We also investigate the effects of different cloud runtime environment conditions on the performance of mobile-cloud computing, and present a simple and low-overhead dynamic makespan estimation model integrated into autonomous agents to enhance them with self-performance evaluation in addition to self-cloning capabilities. The proposed performance profiling model is used in conjunction with a cloud resource optimization scheme to ensure optimal performance. Experiments with two mobile applications demonstrate the effectiveness of the proposed approach for high-performance mobile-cloud computing.

关键词： mobile-cloud computing autonomous agents context performance

来源：评论

学校读者我要写书评

暂无评论

DNNTune: Automatic Benchmarking DNN Models for mobile-cloud computing

引用

ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION 2019年第4期16卷 49-49页

作者： Xia, Chunwei Zhao, Jiacheng Cui, Huimin Feng, Xiaobing Xue, Jingling Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture 6 Kexueyuan South Rd Zhongguancun Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Comp Sci & Technol 19 A Yuquan Rd Beijing 100049 Peoples R China Univ New South Wales Sch Comp Sci & Engn Gate 14 Barker St Sydney NSW 2052 Australia

Deep Neural Networks (DNNs) are now increasingly adopted in a variety of Artificial Intelligence (AI) applications. Meantime, more and more DNNs are moving from cloud to the mobile devices, as emerging AI chips are integrated into mobiles. Therefore, the DNN models can be deployed in the cloud, on the mobile devices, or even mobile-cloud coordinate processing, making it a big challenge to select an optimal deployment strategy under specific objectives. This article proposes a DNN tuning framework, i.e., DNNTune, that can provide layer-wise behavior analysis across a number of platforms. Using DNNTune, this article further selects 13 representative DNN models, including CNN, LSTM, and MLP, and three mobile devices ranging from low-end to high-end, and two AI accelerator chips to characterize the DNN models on these devices to further assist users finding opportunities for mobile-cloud coordinate computing. Our experimental results demonstrate that DNNTune can find a coordinated deployment achieving up to 1.66x speedup and 15% energy saving comparing with mobile-only and cloud-only deployment.

关键词： DNN mobile-cloud computing heterogeneous computing

来源：评论

学校读者我要写书评

暂无评论

An Open and Portable Platform for Learning Data Security in mobile cloud computing 16

An Open and Portable Platform for Learning Data Security in ...

引用

17th Annual Conference on Information Technology Education (SIGITE) and 5th Annual Conference on Research in Information Technology (RIIT)

作者： Li, Lei Qian, Kai Hasan, Ragid Chen, Qian Wu, Dalei Shi, Yong Kennesaw State Univ 1100 South Marietta Pkwy Marietta GA 30060 USA Univ Alabama Birmingham 300 Univ Blvd Birmingham AL 35294 USA Savannah State Univ 3219 Coll St Savannah GA 31404 USA Univ Tennessee 615 McCallie Ave Chattanooga TN 37403 USA Kennesaw State Univ 1100 South Marietta Pkwy Mairetta GA 30060 USA

ISBN: (纸本)9781450344524

mobile cloud computing (MCC) has become an emerging technology given the explosive growth of mobile devices and advances in cloud computing in recent years. Data security and privacy are the main issues preventing individuals and organizations from adopting MCC despite the benefits it promises. Security professionals need to be trained on the new data security threats introduced by MCC. Building on open source software, this paper presents a portable architecture for teaching data security threat analysis and defense in the mobile cloud computing environment.

关键词： data security portable open source software. mobile-cloud computing

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Remote-I/O Support for a DSM-Based Computation Offloading Scheme

引用

Journal of Computer Science & Technology 2017年第5期32卷 957-973页

作者： Yuhun Jun Jaemin Lee Euiseong Seo College of Software Sungkyunkwan University Suwon 16419 Korea

Computation offloading enables mobile devices to execute rich applications by using the abundant computing resources of powerful server systems. The distributed shared memory based (DSM-based) computation offloading approach is expected to be especially popular in the near future because it can dynamically migrate running threads to computing nodes and does not require any modifications of existing applications to do so. The current DSM-based computation offloading scheme, however, has focused on efficiently offloading computationally intensive applications and has not considered the significant performance degradation caused by processing the I/O requests issued by offloaded threads. Because most mobile applications are interactive and thus yield frequent I/O requests, efficient handling of I/O operations is critically important. In this paper, we quantitatively analyze the performance degradation caused by I/O processing in DSM-based computation offloading schemes using representative commodity applications. To remedy the performance degradation, we apply a remote I/O scheme based on remote device support to computation offloading. The proposed approach improves the execution time by up to 43.6% and saves up to 17.7% of energy consumption in comparison with the existing offloading schemes. Selective compression of the remote I/O scheme reduces the network traffic by up to 53.5%.

关键词： computation offloading mobile-cloud computing distributed shared memory (DSM) mobile computing

来源：评论

学校读者我要写书评

暂无评论

MyMOOCSpace: A cloud-based mobile system to support effective collaboration in higher education online courses

引用

COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2017年第6期25卷 910-926页

作者： Ramirez-Donoso, Luis Rojas-Riethmuller, Juan S. Perez-Sanagustin, Mar Neyem, Andres Alario-Hoyos, Carlos Pontificia Univ Catolica Chile DCC Avda Vicuna Mackenna 4860 Santiago 7820436 Chile Univ Bernardo OHiggins Santiago Chile Univ Carlos III Madrid Leganes Spain

In recent years, institutions of higher education have been using Massive Open Online Courses (MOOCs) as an alternative to enhance and innovate traditional classroom practices. One of the approaches to this type of innovation consists of using the platforms where MOOCs are hosted for the development of courses that are aligned to their on-campus curricular contents. They are known as Small Private Online Courses (SPOCs), which allow online access to knowledge for groups of students with a well-defined profile. The platforms where MOOCs (and SPOCs) are hosted have been designed to support large volumes of data and visits. However, these platforms present important limitations regarding the implementation of collaborative learning activities. To address this problem, this article presents MyMOOCSpace, a cloud-based mobile system aimed at supporting effective collaboration in MOOCs, by combining key aspects of collaboration from the research area of Computer Supported Collaborative Learning (CSCL) with game-based dynamics. MyMOOCSpace has been tested in three quasi-experiments that were run in four Latin-American universities with a total of 68 participants. The objective was to assess its usability and its effect in enhancing collaboration among students in a SPOC. The results obtained on usability show that MyMOOCSpace is easy to use, and that participants felt pleased with while using it. Finally, it was observed that MyMOOCSpace managed to enhance interaction and collaboration among students.

关键词： CSCL-collaboration gamification m-learning mobile-cloud computing MOOC-SPOC

来源：评论

学校读者我要写书评

暂无评论

Towards Emotionally Aware AI Smart Classroom: Current Issues and Directions for Engineering and Education

引用

IEEE ACCESS 2018年 6卷 5308-5331页

作者： Kim, Yelin Soyata, Tolga Behnagh, Rezafeyzi SUNY Albany Dept Elect & Comp Engn Albany NY 12222 USA SUNY Albany Dept Educ Theory & Practice Albany NY 12222 USA

Future smart classrooms that we envision will significantly enhance learning experience and seamless communication among students and teachers using real-time sensing and machine intelligence. Existing developments in engineering have brought the state-of-the-art to an inflection point, where they can be utilized as components of a smart classroom. In this paper, we propose a smart classroom system that consists of these components. Our proposed system is capable of making real-time suggestions to an in-class presenter to improve the quality and memorability of their presentation by allowing the presenter to make real-time adjustments/corrections to their non-verbal behavior, such as hand gestures, facial expressions, and body language. We base our suggested system components on existing research in affect sensing, deep learning-based emotion recognition, and real-time mobile-cloud computing. We provide a comprehensive study of these technologies and determine the computational requirements of a system that incorporates these technologies. Based on these requirements, we provide a feasibility study of the system. Although the state-of-the-art research in most of the components we propose in our system are advanced enough to realize the system, the main challenge lies in: 1) the integration of these technologies into a holistic system design;2) their algorithmic adaptation to allow real-time execution;and 3) quantification of valid educational variables for use in algorithms. In this paper, we discuss current issues and provide future directions in engineering and education disciplines to deploy the proposed system.

关键词： Educational technology emotion recognition smart classroom deep learning real-time computing mobile-cloud computing meta-cognition

来源：评论

学校读者我要写书评

暂无评论

mobile-cloud assisted framework for selective encryption of medical images with steganography for resource-constrained devices

引用

MULTIMEDIA TOOLS AND APPLICATIONS 2017年第3期76卷 3519-3536页

作者： Sajjad, Muhammad Muhammad, Khan Baik, Sung Wook Rho, Seungmin Jan, Zahoor Yeo, Sang-Soo Mehmood, Irfan Islamia Coll Peshawar Digital Image Proc Lab Dept Comp Sci Peshawar Pakistan Sejong Univ Intelligent Media Lab Dept Digital Contents Coll Elect & Informat Engn Seoul South Korea Sungkyul Univ Dept Media Software Anyang South Korea Mokwon Univ Div Convergence Comp & Media Daejeon South Korea Sejong Univ Dept Comp Sci & Engn Seoul South Korea

In this paper, the problem of outsourcing the selective encryption of a medical image to cloud by resource-constrained devices such as smart phone is addressed, without revealing the cover image to cloud using steganography. In the proposed framework, the region of interest of the medical image is first detected using a visual saliency model. The detected important data is then embedded in a host image, producing a stego image which is outsourced to cloud for encryption. The cloud which has powerful resources, encrypts the image and sent back the encrypted marked image to the client. The client can then extract the selectively encrypted region of interest and can combine it with the region of non-interest to form a selectively encrypted image, which can be sent to medical specialists and healthcare centers. Experimental results and analysis validate the effectiveness of the proposed framework in terms of security, image quality, and computational complexity and verify its applicability in remote patient monitoring centers.

关键词： Medical image processing Image steganography Visual saliency models Selective image encryption mobile-cloud computing Information security Resource-constrained devices

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：