Usability testing on intelligent mobile web pre-fetching of cloud storage scheme

Mobile device and Cloud Storage (CS) represent the trends of technology usage of the last few years. However, the difficulty in managing the data when there are too many simultaneous uses of cloud storage services at the same time that can cause latency or delayed time. This paper evaluates mobile cloud storage services using usability testing, which is intended to access by multiple of Cloud Storage Services (CSS) with the proposed Intelligent Mobile Web Pre-fetching of Cloud Storage Scheme (MOBICS). The results show most of the respondents with 95.65% agreeing that MOBICS system was very practical and has enhanced the speed in accessing and storing data by Mobile Cloud Storage (MCS). Besides, MOBICS reduces time of interaction up to 19.28% for the local pre-fetching and 18.80% for the intelligent pre-fetching

Rendering real-time dashboards using a GraphQL-based UI Architecture

With the increase in the complexity of the systems being built and demand in the quality of service by the customers, developing and providing highly efficient real-time systems is one of the biggest challenges today for software enterprises. BluemixTM ─ IBM’s cloud offering implemented on Cloud Foundry, an open source “Platform as a Service” (PaaS), is an example of such a system. Currently, there are approx. 26 infrastructural services running in the background from where the data is fetched and is rendered on different dashboards of the system. However, the system suffers from performance issues. This thesis explores the performance improvements of the real-time dashboards by introducing our proposed GraphQL-based UI architecture which allows caching and asynchronous loading. The test results of this architecture’s implementation on the Bluemix Usage Dashboard show that the Real data renders 245% faster and the Switching Account 153% faster than the existing system

Development of a real-time full-field range imaging system

This article describes the development of a full-field range imaging system employing a high frequency amplitude modulated light source and image sensor. Depth images are produced at video frame rates in which each pixel in the image represents distance from the sensor to objects in the scene. The various hardware subsystems are described as are the details about the firmware and software implementation for processing the images in real-time. The system is flexible in that precision can be traded off for decreased acquisition time. Results are reported to illustrate this versatility for both high-speed (reduced precision) and high-precision operating modes