Cloud-based or On-device: An Empirical Study of Mobile Deep Inference

Modern mobile applications are benefiting significantly from the advancement in deep learning, e.g., implementing real-time image recognition and conversational system. Given a trained deep learning model, applications usually need to perform a series of matrix operations based on the input data, in order to infer possible output values. Because of computational complexity and size constraints, these trained models are often hosted in the cloud. To utilize these cloud-based models, mobile apps will have to send input data over the network. While cloud-based deep learning can provide reasonable response time for mobile apps, it restricts the use case scenarios, e.g. mobile apps need to have network access. With mobile specific deep learning optimizations, it is now possible to employ on-device inference. However, because mobile hardware, such as GPU and memory size, can be very limited when compared to its desktop counterpart, it is important to understand the feasibility of this new on-device deep learning inference architecture. In this paper, we empirically evaluate the inference performance of three Convolutional Neural Networks (CNNs) using a benchmark Android application we developed. Our measurement and analysis suggest that on-device inference can cost up to two orders of magnitude greater response time and energy when compared to cloud-based inference, and that loading model and computing probability are two performance bottlenecks for on-device deep inferences.Comment: Accepted at The IEEE International Conference on Cloud Engineering (IC2E) conference 201

Designing and Developing a Mobile-Cloud E-Learning Application

The mobile-cloud E-Learning application is an application software which can be downloaded into a mobile phone or a smart phone. This application software functions with the presence of a network, which is the Internet. The objectives of this project are to study on how the contents of the current existing E-Learning can be adapted to the mobile phones/smart phones which will then lead to designing and developing the contents of the mobile E-Learning application to suit the small screens of the mobile phones/smart phones using the cloud computing concept. This objective was made due to the problems identified during the research of the limitations of the current E-Learning system which are usability and accessibility problems. The scope of this study is to design and develop a mobile-cloud E-Learning application for the specifications of the BlackBerry OS 6 with the functions of viewing and posting announcements as well as downloading and uploading lecture notes by students, lecturers and management staffs respectively. The methodology used for the research are distributing online questionnaire and conducting interviews. On the other hand, the project methodology chosen is the prototyping method which requires users’ participation. Finally, up to date, the distributed online showed positive response from the responders whereby they support the mobile version of the E-Learning system

Enhancing Consumer Experience through Mobile Commerce: Challenges and Opportunities

During this information technology era, mobile commerce is succeeding very easily especially Covid-19 pandemic timings. This article is mentioned about commerce, mobile, mobile commerce, users of e-commerce, Users of Mobile Commerce, Holistic Points, Classification of Mobile Commerce, Mobile Commerce Applications, Five Stages in Systems Development Life Cycle for mobile commerce applications, Data Flow Diagrams - Some general guidelines for developing DFDs, Why documentation is important for mobile development?.Cloud Computing, Cloud Computing models, Advantages of Cloud Computing, Disadvantage of Cloud Computing, Influence of cloud computing upon E-commerce, Advantage of cloud computing in E-commerce, All about The Advantages And Disadvantages Of Online Learning, Challenges of Mobile Commerce, E-Commerce will change in the next 5 years in India, Opportunities in (or applications of) M-Commerce, Application of M-Commerce, Opportunities for M-Commerce and Conclusion

Rancang Bangun Aplikasi Mobile Learning Pada Sistem Operasi Android

Abstrak Teknologi diharapkan menjadi solusi kebutuhan masa depan. Pada saat ini hampir setiap orang memiliki telepon seluler. Teknologi telepon seluler selalu berkembang dari masa ke masa hingga sekarang dimana telepon seluler dapat terkoneksi dengan internet dan mengambil data dari server melalui sistem cloud computing. Salah satu pemanfaatan dari sistem ini adalah untuk pendidikan. Dengan demikian pendidikan dapat diusahakan dapat dinikmati semua orang dimanapun dan kapanpun. Telepon seluler yang terkoneksi dengan internet dapat berperan sebagai pendamping peserta didik untuk belajar, yang sering disebut dengan istilah mobile learning. Namun di sisi lain perangkat mobile learning memiliki keterbatasan sumber daya dan keragaman platform sehingga diperlukan rancangan yang mampu menjamin kompatibilitas. Dari percobaan-percobaan yang telah dilakukan dalam beberapa smartphone android dengan spesifikasi yang berbeda-beda, maka dapat disimpulkan bahwa aplikasi yang dibangun dapat berjalan dengan baik. Keywords: telepon seluler, cloud computing, internet, mobile learning   Abstract Technology is expected to be a future solution needs. At present, almost every people has a cellular phone. Mobile phone technology is always evolving from time to time until now where cellular phones can be connected to the Internet and retrieve data from the server over the cloud computing system. One of the utilization of this system is for education. Using this technology education can be done by people everywhere and everytime. Cellular phone that connected to the internet can be as a assistant to the learners to learn, which is called as mobile learning. However mobile learning devices is limited by resources and diversity of the platform. With the result, design to ensure compatibility is required. By experiments have been conducted in several android smartphone with different specifications, it can be concluded that mobile learning application run properly. Keywords: cellular phone, cloud computing, internet, mobile learnin

Developing service-oriented application for the educational cloud

In this paper we present an application which is used for cloud computing infrastructure management. The application is based on web services and it is integrated with an existing e-learning system. Main users of the applications are teachers and students and the application consists of two main parts which are web application and mobile application. The application is successfully implemented at the e-Business Laboratory of the Faculty of Organizational Sciences in Belgrade

Spontaneous Proximity Clouds: Making Mobile Devices to Collaborate for Resource and Data Sharing

International audienceThe base motivation of Mobile Cloud Computing was empowering mobile devices by application offloading onto powerful cloud resources. However, this goal can't entirely be reached because of the high offloading cost imposed by the long physical distance between the mobile device and the cloud. To address this issue, we propose an application offloading onto a nearby mobile cloud composed of the mobile devices in the vicinity-a Spontaneous Proximity Cloud. We introduce our proposed dynamic, ant-inspired, bi-objective offloading middleware-ACOMMA, and explain its extension to perform a close mobile application offloading. With the learning-based offloading decision-making process of ACOMMA, combined to the collaborative resource sharing, the mobile devices can cooperate for decision cache sharing. We evaluate the performance of ACOMMA in collaborative mode with real benchmarks Face Recognition and Monte-Carlo algorithms-and achieve 50% execution time gain