Modeling the Resource Requirements of Convolutional Neural Networks on Mobile Devices

Convolutional Neural Networks (CNNs) have revolutionized the research in computer vision, due to their ability to capture complex patterns, resulting in high inference accuracies. However, the increasingly complex nature of these neural networks means that they are particularly suited for server computers with powerful GPUs. We envision that deep learning applications will be eventually and widely deployed on mobile devices, e.g., smartphones, self-driving cars, and drones. Therefore, in this paper, we aim to understand the resource requirements (time, memory) of CNNs on mobile devices. First, by deploying several popular CNNs on mobile CPUs and GPUs, we measure and analyze the performance and resource usage for every layer of the CNNs. Our findings point out the potential ways of optimizing the performance on mobile devices. Second, we model the resource requirements of the different CNN computations. Finally, based on the measurement, pro ling, and modeling, we build and evaluate our modeling tool, Augur, which takes a CNN configuration (descriptor) as the input and estimates the compute time and resource usage of the CNN, to give insights about whether and how e ciently a CNN can be run on a given mobile platform. In doing so Augur tackles several challenges: (i) how to overcome pro ling and measurement overhead; (ii) how to capture the variance in different mobile platforms with different processors, memory, and cache sizes; and (iii) how to account for the variance in the number, type and size of layers of the different CNN configurations

Implementation of E-education in Africa via Space Networks

In this paper is introduced an advanced E-education provision in remote dispersed communities, such as rural, remote, mobile, agriculture, mining, construction, surveying, military, tourism and so on, based on the specific needs and requirements, implies significant broadband connectivity requirements, timely and quality-assured content delivery of service, applications and interactivity. The E-education solutions of distance learning and training for remote and rural areas, which are out of range of terrestrial and short distance wireless telecommunications facilities, cannot provide the broadband access without space-enabled communication infrastructures, such as satellite constellations and Stratospheric Platform Systems (SPS) or High Altitude Platforms (HAP). The paper also discusses the integration challenges that are presented by combining use of the space solutions for implementation Education and learning in urban, rural and mobile environments. The configuration of in-house design and development of Space Segment, installation of the scale-down Digital Video Broadcasting-Return Channel via Satellite (DVB-RCS) Hub as a Gateway, Ground Network and Interactive VSAT, known as Fixed Interactive Terminals (FIT), for E-education, distance learning and staff training initiative in Africa are described

An educational tool for enhanced mobile e-Learning for technical higher education using mobile devices for augmented reality

In all dimensions of education and all subjects, Smartphones have turned out to be broadly acknowledged technology. It plays an essential task in advanced online education systems. Because of smart devices� effortlessness and extension property, it is getting to be mandatory for portable applications. This paper analyses the research on Smart Devices (SD) to incorporate visual simulation into e-learning. The researchers created an Augmented Reality (AR) platform for e-learners to expand the coursebook with graphics and virtual multimedia applications. This paper recommends a Mobile e-Learning (MeL) application termed �MeL app. The advanced MeL app methods have been tested using Mann-Whitney �U� Test in the lecture hall using real-time learners. The proposed MeL app planned to create the learning practice easier, focusing on e-learner�s requirements by encouraging e-learners and instructor relationships to maintain communicative development-based e-learning for Technical Higher Education (THE). Software engineering learners assess this proposed framework in THE. Future work in this investigation incorporates new highlights, testing the device in extreme situations, evaluating the instructive perspectives utilizing more significant and increasingly various understudy and beginner inhabitants, and at last, extending the application space

DESAIN PORTAL KAMPUS SELULER DI LINGKUNGAN BIG DATA : MOBILE CAMPUS PORTAL DESIGN IN THE BIG DATA ENVIRONMENT

The development of smart mobile devices and big data technology and mobile applications has become an efficient tool for sharing information. This mobile learning system provides an interactive teaching platform between lecturers and students. Learners can study online classes at any time and anywhere with the help of mobile devices. This research proposes a mobile learning application to Android and Blackberry smart phones. The mobile application provides e-learning services on the client side for students and sharing service interface on the service side. The concept of big data uses volume, variety, velocity, veracity and value or abbreviated as 5V. This research explains why and how to design a mobile campus portal to meet the requirements of the education big data environment, introduce the topology, applications and structure of the mobile portal campus system and discuss the implementation of the 5V big data concept on the mobile portal campus. This study applies the concept of 5V big data in designing an effective mobile campus portal. The final results of Mobile Campus Portal research at the application level provide five types of application modules for users including teaching management, administrative management, financial management, research management and public services. In meeting the requirements of the big data environment on campus, the Mobile Campus Portal applies the five dimensions of the big data concept to the entire data processing cycle. Data integration uses volume and dimension variations. Data translation uses the speed dimension and the data security control uses the truth and authentication dimension. Data mining uses the value dimension

Designing citizen science tools for learning: lessons learnt from the iterative development of nQuire

This paper reports on a 4-year research and development case study about the design of citizen science tools for inquiry learning. It details the process of iterative pedagogy-led design and evaluation of the nQuire toolkit, a set of web-based and mobile tools scaffolding the creation of online citizen science investigations. The design involved an expert review of inquiry learning and citizen science, combined with user experience studies involving more than 200 users. These have informed a concept that we have termed ‘citizen inquiry’, which engages members of the public alongside scientists in setting up, running, managing or contributing to citizen science projects with a main aim of learning about the scientific method through doing science by interaction with others. A design-based research (DBR) methodology was adopted for the iterative design and evaluation of citizen science tools. DBR was focused on the refinement of a central concept, ‘citizen inquiry’, by exploring how it can be instantiated in educational technologies and interventions. The empirical evaluation and iteration of technologies involved three design experiments with end users, user interviews, and insights from pedagogy and user experience experts. Evidence from the iterative development of nQuire led to the production of a set of interaction design principles that aim to guide the development of online, learning-centred, citizen science projects. Eight design guidelines are proposed: users as producers of knowledge, topics before tools, mobile affordances, scaffolds to the process of scientific inquiry, learning by doing as key message, being part of a community as key message, every visit brings a reward, and value users and their time

On sharing and synchronizing groupware calendars under android platform

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Sharing a calendar of tasks and events is a cornerstone in collaborative group work. Indeed, the individual work of the members of the group as well as the group work as a whole need the calendar to guide their activity and to meet the deadlines, milestones, deliverables of a project, etc. Additionally the members of the group should be able to work both offline and online, which arises when members of the group use smartphones and can eventually run out of Internet connection from time to time, or simply want to develop some activities locally. In the former case, they should have access to the calendar locally, while in the later case they should access the calendar online, shared by all members of the group. In both cases they should be able to see eventually the same information, namely the local calendars of the members should be synchronized with the group calendar. For the case of smartphones under Android system, one solution could be using the Google calendar, however, that is not easily tailorable to collaborative group work. In this paper we present an analysis, design and implementation of group work calendar that meets several requirements such as 1) sharing among all of members of the group, 2) synchronization among local calendars of members and global group calendar, 3) conflict resolution through a voting system, 4) awareness of changes in the entries (tasks, members, events, etc.) of the calendar and 5) all these requirements under proper privacy, confidentiality and security mechanisms. Moreover, we extend the sharing of calendars among different groups, a situation which often arises in enterprises when different groups need to be aware of other projects' development, or, when some members participate in more than one project at the same time.Peer ReviewedPostprint (author's final draft

Big Data Caching for Networking: Moving from Cloud to Edge

In order to cope with the relentless data tsunami in $5G$ wireless networks, current approaches such as acquiring new spectrum, deploying more base stations (BSs) and increasing nodes in mobile packet core networks are becoming ineffective in terms of scalability, cost and flexibility. In this regard, context-aware $5$G networks with edge/cloud computing and exploitation of \emph{big data} analytics can yield significant gains to mobile operators. In this article, proactive content caching in $5$G wireless networks is investigated in which a big data-enabled architecture is proposed. In this practical architecture, vast amount of data is harnessed for content popularity estimation and strategic contents are cached at the BSs to achieve higher users' satisfaction and backhaul offloading. To validate the proposed solution, we consider a real-world case study where several hours of mobile data traffic is collected from a major telecom operator in Turkey and a big data-enabled analysis is carried out leveraging tools from machine learning. Based on the available information and storage capacity, numerical studies show that several gains are achieved both in terms of users' satisfaction and backhaul offloading. For example, in the case of $16$ BSs with $30\%$ of content ratings and $13$ Gbyte of storage size ($78\%$ of total library size), proactive caching yields $100\%$ of users' satisfaction and offloads $98\%$ of the backhaul.Comment: accepted for publication in IEEE Communications Magazine, Special Issue on Communications, Caching, and Computing for Content-Centric Mobile Network