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

The crowd as a cameraman : on-stage display of crowdsourced mobile video at large-scale events

Recording videos with smartphones at large-scale events such as concerts and festivals is very common nowadays. These videos register the atmosphere of the event as it is experienced by the crowd and offer a perspective that is hard to capture by the professional cameras installed throughout the venue. In this article, we present a framework to collect videos from smartphones in the public and blend these into a mosaic that can be readily mixed with professional camera footage and shown on displays during the event. The video upload is prioritized by matching requests of the event director with video metadata, while taking into account the available wireless network capacity. The proposed framework's main novelty is its scalability, supporting the real-time transmission, processing and display of videos recorded by hundreds of simultaneous users in ultra-dense Wi-Fi environments, as well as its proven integration in commercial production environments. The framework has been extensively validated in a controlled lab setting with up to 1 000 clients as well as in a field trial where 1 183 videos were collected from 135 participants recruited from an audience of 8 050 people. 90 % of those videos were uploaded within 6.8 minutes

Quality assessment technique for ubiquitous software and middleware

The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future

Mobile application platform heterogeneity: Android vs Windows phone vs iOS vs Firefox OS

Modern smartphones have a rich spectrum of increasingly sophisticated features, opening opportunities for software-led innovation. Of the large number of platforms to develop new software on, in this paper we look closely at three platforms identified as market leaders for the smartphone market by Gartner Group in 2013 and one platform, Firefox OS, representing a new paradigm for operating systems based on web technologies. We compare the platforms in several different categories, such as software architecture, application development, platform capabilities and constraints, and, finally, developer support. Using the implementation of a mobile version of the tic-tac-toe game on all the four platforms, we seek to investigate strengths, weaknesses and challenges of mobile application development on these platforms. Big differences are highlighted when inspecting community environments, hardware abilities and platform maturity. These inevitably impact upon developer choices when deciding on mobile platform development strategies

IRC Mobile library Services

The evolution of mobile technology allowed the introduction of m-learning. Many institutions have been implementing Digital Library Systems and more specifically m-library (Mobile Library). This report shows how libraries worldwide have been developing websites designed especially for mobile phones and PDA solutions, to enhance the accessibility range of their websites. It describes the Digital Library Systems available in the market, similarities among them and describes the proposed system to be implemented by UTP. Readers will be able to identify the major problems with regards to the IRC PRECISE System and the areas in which following worldwide practices or UTP’s needs the system can provide a more reliable link between IRC and students. This report aims to clarify and emphasize the importance of the development of this project and how relevant it is to the UTP Students Community and also to the IRC Management. The background specifies the scope of work for this project, the purpose and significance. The literature review presents studies that have been conducted in this area, and similar projects developed around the globe. Furthermore in this document, the methodology used to conduct research and the respective results and discussion are exposed; the timeline for the project completion, the tools identified for the project development will also be described in the methodology section. The final part describes the prototype including the functional specifications and lastly the conclusion which includes the relevancy of the objectives and recommendations

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time