Investigation into Mobile Learning Framework in Cloud Computing Platform

Abstract—Cloud computing infrastructure is increasingly used for distributed applications. Mobile learning applications deployed in the cloud are a new research direction. The applications require specific development approaches for effective and reliable communication. This paper proposes an interdisciplinary approach for design and development of mobile applications in the cloud. The approach includes front service toolkit and backend service toolkit. The front service toolkit packages data and sends it to a backend deployed in a cloud computing platform. The backend service toolkit manages rules and workflow, and then transmits required results to the front service toolkit. To further show feasibility of the approach, the paper introduces a case study and shows its performance

Optimization of Radio and Computational Resources for Energy Efficiency in Latency-Constrained Application Offloading

Providing femto-access points (FAPs) with computational capabilities will allow (either total or partial) offloading of highly demanding applications from smart-phones to the so called femto-cloud. Such offloading promises to be beneficial in terms of battery saving at the mobile terminal (MT) and/or latency reduction in the execution of applications, whenever the energy and/or time required for the communication process are compensated by the energy and/or time savings that result from the remote computation at the FAPs. For this problem, we provide in this paper a framework for the joint optimization of the radio and computational resource usage exploiting the tradeoff between energy consumption and latency, and assuming that multiple antennas are available at the MT and the serving FAP. As a result of the optimization, the optimal communication strategy (e.g., transmission power, rate, precoder) is obtained, as well as the optimal distribution of the computational load between the handset and the serving FAP. The paper also establishes the conditions under which total or no offloading are optimal, determines which is the minimum affordable latency in the execution of the application, and analyzes as a particular case the minimization of the total consumed energy without latency constraints.Comment: Accepted to be published at IEEE Transactions on Vehicular Technology (acceptance: November 2014

Hardware/software partitioning of streaming applications for multi-processor system-on-chip

Hardware/software (HW/SW) co-design has emerged as a crucial and integral part in the development of various embedded applications. Moreover, the increases in the number of embedded multimedia and medical applications make streaming throughput an important attribute of Multi-Processor System-on-Chip (MPSoC). As an important development step, HW/SW partitioning affects the system performance. This paper formulates the optimization of HW/SW partitioning aiming at maximizing streaming throughput with predefined area constraint, targeted for multi-processor system with hardware accelerator sharing capability. Software-oriented and hardware-oriented greedy heuristics for HW/SW partitioning are proposed, as well as a branch-and-bound algorithm with best-first search that utilizes greedy results as initial best solution. Several random graphs and two multimedia applications (JPEG encoder and MP3 decoder) are used for performance benchmarking against brute force ground truth. Results show that the proposed greedy algorithms produce fast solutions which achieve 87.7% and 84.2% near-optimal solution respectively compared to ground truth result. With the aid of greedy result as initial solution, the proposed branch-and-bound algorithm is able to produce ground truth solution up to 2.4741e+8 times faster in HW/SW partitioning time compared to exhaustive brute force method

A Framework for Measuring the Usability Issues and Criteria of Mobile Learning Applications

With the continuing growth of mobile devices outpacing that of desktops and laptops, mobile devices have become the new personal computer. These devices have become increasingly sophisticated and extremely powerful in the last few years. Substantial work has been done to measure mobile applications’ level of quality; many researchers have attempted to figure out why certain applications fail and others succeed. In this thesis, a conceptual framework for measuring the quality aspects and criteria of m-learning is produced. Furthermore, a software prototype application for smartphones to assess usability issues of m-learning applications has been designed and implemented. This prototype application is developed using Java language and the Android Software development Kit, such that the recommended guidelines of the proposed framework are maintained. A questionnaire survey was conducted at Western University with approximately 96 undergraduate software engineering students. Five identical smartphones are used to evaluate the developed prototype in terms of ease of use, user satisfaction, attractiveness and learnability

Augmented Reality and Context Awareness for Mobile Learning Systems

Learning is one of the most interactive processes that humans practice. The level of interaction between the instructor and his or her audience has the greatest effect on the output of the learning process. Recent years have witnessed the introduction of e-learning (electronic learning), which was then followed by m-learning (mobile learning). While researchers have studied e-learning and m-learning to devise a framework that can be followed to provide the best possible output of the learning process, m-learning is still being studied in the shadow of e-learning. Such an approach might be valid to a limited extent, since both aims to provide educational material over electronic channels. However, m-learning has more space for user interaction because of the nature of the devices and their capabilities. The objective of this work is to devise a framework that utilises augmented reality and context awareness in m-learning systems to increase their level of interaction and, hence, their usability. The proposed framework was implemented and deployed over an iPhone device. The implementation focused on a specific course. Its material represented the use of augmented reality and the flow of the material utilised context awareness. Furthermore, a software prototype application for smart phones, to assess usability issues of m-learning applications, was designed and implemented. This prototype application was developed using the Java language and the Android software development kit, so that the recommended guidelines of the proposed framework were maintained. A questionnaire survey was conducted at the University, with approximately twenty-four undergraduate computer science students. Twenty-four identical smart phones were used to evaluate the developed prototype, in terms of ease of use, ease of navigating the application content, user satisfaction, attractiveness and learnability. Several validation tests were conducted on the proposed augmented reality m-learning verses m-learning. Generally, the respondents rated m-learning with augmented reality as superior to m-learning alone