VIDalizer: An energy efficient video streamer

Digital video playback on mobile devices is fast becoming widespread and popular. Since mobile devices are typically resource constrained in terms of network bandwidth, battery power and available screen resolution, it is often necessary to formulate special encoding techniques in order to optimize power consumption during video streaming and playback. The existing H.264 standard is popular for video encoding on mobile devices, since it results in a low-bitrate video with visual clarity that is adequate for video playback on mobile devices. However, due to the complexity of the H.264 representation, the video decoding procedure is typically computationally intensive. In this paper, we propose a novel lossy video representation termed as Ligne-Claire (LC) video. LC videos are obtained via graphics overlay of outlines or silhouettes of objects in the video over an approximated texture video. Since the playback of LC video is typically meant for mobile devices, the visual quality of video is adequate for most mobile applications wherein the semantic content of the video can be characterized by object shapes and approximate texture information. Experimental results presented in the paper demonstrate that the proposed lossy LC video encoding scheme results in power savings of 50% or more during video playback compared to standard H.264-encoded videos, of similar video file size. In order to evaluate the visual quality of the LC video, we compare the performance of LC videos with H.264-encoded videos in the context of some typical computer vision tasks. Our results indicate that the performance of the computer vision algorithms on these videos is similar. This fact, coupled with subjective evaluation, and the resulting significant power savings, indicates that the proposed LC representation can be used effectively to encode video for power-constrained mobile devices.

Voice control has emerged as a popular method for interacting with smart-devices such as smartphones, smartwatches etc. Popular voice control applications like Siri and Now are already used by a large number of smartphone and tablet users. A major challenge in designing a voice control application is that it requires continuous monitoring of user?s voice input through the microphone. Such applications utilize hotwords such as Okay Google or Hi Galaxy allowing them to distinguish user?s voice command and her other conversations. A voice control application has to continuously listen for hotwords which significantly increases the energy consumption of the smart-devices. To address this energy efficiency problem of voice control, we present AccelWord in this paper. AccelWord is based on the empirical evidence that accelerometer sensors found in today?s mobile devices are sensitive to user?s voice. We also demonstrate that the effect of user?s voice on accelerometer data is rich enough so that it can be used to detect the hotwords spoken by the user. To achieve the goal of low energy cost but high detection accuracy, we combat multiple challenges, e.g. how to extract unique signatures of user?s speaking hotwords only from accelerometer data and how to reduce the interference caused by user?s mobility. We finally implement AccelWord as a standalone application running on Android devices. Comprehensive tests show AccelWord has hotword detection accuracy of 85% in static scenarios and 80% in mobile scenarios. Compared to the microphone based hotword detection applications such as Now and Samsung S Voice, AccelWord is 2 times more energy efficient while achieving the accuracy of 98% and 92% in static and mobile scenarios respectively.

The market share of mobile devices like smartphones and tablets is growing rapidly. These devices are increasingly used to access the services offered on the Internet. Time spent online has started to shift considerably from desktop and laptop computers to mobile connected post-pc devices. In certain areas, mobile usage has already exceeded the access and traffic generated by desktop computers. This development also affects the usage behavior and ex-pectations of job seekers when accessing job ads and other job-related information online. In this context the paper at hand presents a study analyzing the behavior and user expectations of job seekers using mobile devices in Germany. The study shows that the majority of smartphone and tablet users have already accessed job ads and used job search applications ("apps") through these devices. Moreover, many of those respondents who have already accessed job ads with a post-pc device also expect to be able to apply for a job via smartphone and tablet.

We propose a methodology to design user-aware streaming strategies for energy efficient smartphone video playback applications (e.g. YouTube). Our goal is to manage the streaming process to minimize the sleep and wake penalty of cellular module and at the same time avoid the energy waste from excessive downloading. The problem is modeled as a stochastic inventory system, where the real length of video playback requested by the smartphone user is considered as demand that follows a stochastic process. Through user behavior analysis, a Gaussian Mixture Model (GMM) is constructed to predict the user demand in video playback, and then an energy efficient video downloading strategy will be determined progressively during the playback process. Experimental results show that compared to a static downloading strategy that is optimized by exhaustive trail, our method can reduce the wasted energy by 10 percent in average.

The Impact of Mobile Channel Adoption on Customer Omni-Channel Banking Behavior

One of the most important factors in digital games is the immersion of the players to enhance their experience in the virtual world created by games. This immersion can be achieved in different ways, such as graphics effects, realistic physics, artificial intelligence and even from user inputs. The Nintendo Wii controller, Sony Playstation Move controller and Microsoft Xbox Kinect, to name a few, present new forms of user interaction using the player's movements, which has led to new forms of gameplay, as well as great forms of feedback. In addition, mobile devices are providing new features, like accelerometers, touch screens, cameras and GPS, which allow new forms of interaction in games played on these devices. In response to this evolution, this paper presents a multi-platform architecture that supports a desktop game being controlled by mobile devices, using their built-in features such as vibration feedback, sound feedback, image feedback and unique inputs like location, voice recognition, camera and gestures in order to enhance player immersion during game play. Additionally, the architecture supports different types of user data input, such as gesture and motion, that can be utilized according to user preferences and desires. Moreover, with this architecture, the mobile screen device can be used to give players feedback, like visual effects, scores and statistics. These available schemes have proven to be very useful and attractive for players, giving them choices that best fit their preferences and abilities. This architecture can also be used in collaborative games, where each player uses his device to interact with games running both on mobile devices and desktop computers. In order to demonstrate our architecture's effectiveness, we have developed a desktop game and done a case study with a pilot group of users, where some usability factors were evaluated. Finally, using a mobile device for game data input and player feedback provides people who are resistant to complex game controllers the opportunity to enjoy playing games using the same device they are accustomed to using daily, thereby minimizing the time needed to learn what is usually necessary to start enjoying a game. This can, in many situations, lower the barrier encountered by experienced smartphone users who are novice game players, as demonstrated in our pilot usability tests, which found high fun factors in such players.

Most mobile devices embed a CMOS image sensor (CIS) for capturing images. In addition, a variety of sensors such as proximity, ambient light, and fingerprint sensors are integrated for device control. The integration of multiple sensors in a device requires significant power consumption, area, and cost. In contrast to multiple sensors, an always-on CIS enables advanced smart sensing, including gesture sensing, face recognition, eye tracking, and so on. Smart sensing using a CIS offers a variety of user interfaces and experiences such as touch-less control, authentication, gaming, and object recognition for the Internet of Things (IOT). A major drawback of a CIS in mobile devices is that it consumes power greater than 50mW [1], and this is not feasible for always-on sensing that is required to function with the limited energy available from the device's battery. Moreover, power reduction in a CIS causes image degradation owing to reduced SNR, which is not acceptable for capturing high-quality images. Many low-power CISs have been reported [2-3]. However, they are inadequate for use as high-resolution sensors because of the requirement of additional in-pixel circuits for device operation at low supply voltages.

Mobile devices are becoming very popular due to their portability and small size, but they are still not comparable to that of PC.Computational and network intensive applications cannot run efficiently on mobile devices due to their limited batteries and energy deficient systems.Recent works to improve mobile device efficiency include mobile cloud computing, mobile edge computing, and device to device communication.Shifting the computations on the cloud will reduce the burden of mobile device but at the same time, this implementation presents many challenges.In this paper, an algorithm is proposed which can deal with the resource acquisition from different sources by using a context aware system.

Mobile devices may often use WLAN hot-spots to communicate directly with one another in a peer-to-peer fashion without having to authenticate (and pay) for Internet access. This ad-hoc-style communication may impede the performance of regular Internet users' hot-spot experience. We present how LEDBAT (Low Extra Delay Background Transport) and its modified version, fLEDBAT, can be used as transport protocol between mobile devices in an infrastructure mode WLAN to reduce the impact on regular traffic. Although promising, the use of (f)LEDBAT may not solve all the problems arising from high-volume ad-hoc data traffic. Active queue management at the access point would do this but this would require controlling it. To overcome this, we complement LEDBAT by bundle admission control mechanisms based on the queueing delay and/or the number of active bundle transfers as alternative approaches. Both combined make device-to-device traffic yield to regular traffic, which we validate through extensive ns-2 simulations.

The development frameworks and the power efficiency in mobile devices have been studied separately. This paper deals with both topics together to determine how the selection of a development framework can impact on energy consumption of a mobile application. The focus is on applications with high processing load, audio and video playback. The results were analyzed and conclusions were reached.

Mobile technologies enable individuals to organize and manage their daily li ves through the mobile applications that are use d during the day. A ugmented reality is one of those applications that can be used on mobile devices. Expectations for the use of new technologies in educational environments increase in parallel with the technolog ical advancements. Thanks to advances in computer, internet and mobile technologies, numerous new applications have emerged that facilitate communication and interaction in educational environments. In particular, t he applications of the augmented reality technologies emerging with the advancing technology in the field of education are becoming widespread and easy -to-use. Augmented reality is a technology that enriches the learning process, created by real-time integration of the virtual elements and the real world elements. In geography teaching, different knowledge and skills are expected to be acquired by the learner , therefore augmented reality application s appeal ing to the different senses of learners can be utilized. AR technology can be used in various fields , especially in education. In addition to increasing productivity, mobile augmented reality applications would be used for multiple purposes in the field of education with the interactive facilities they offer to user such as 2D and 3D visual support and video playback.

Utilizing peoples' mobile devices for gathering sensor data has attracted a lot of attention within the last few years. As a result, a great variety of systems for sensing environmental phenomena like temperature or noise have been proposed. However, most of these systems do not take into account that mobile devices have only limited energy resources. For instance, an often assumed prerequisite is that mobile devices are always aware of their position. Given the fact that a position fix is a very energy consuming operation, continuous positioning would quickly drain a device's battery. Since the owners of the mobile devices will not tolerate a significant reduction of the devices' battery lifetime, such an approach is not suitable. To address this issue we present PSense, a flexible system for efficiently gathering sensor data with mobile devices. By avoiding unnecessary position fixes, PSense reduces the energy consumption of mobile devices by up to 70% compared to existing mobile sensing approaches. This is achieved by introducing an adaptive positioning mechanism and by utilizing energy efficient short-range communication to exchange position related information.

Recently, we are surrounded by a collection of heterogeneous computing devices such as desktop computers, laptops, smart phones, smart televisions, and tablet PCs. Each device is operated with its own host operating system, has its own internal architecture, and performs its independent tasks with its own applications and data. A common property amongst these devices, namely that of internet-connectivity, allows them to configure personal virtual cloud system by interconnecting each other through an intermediate switching device. The personal cloud service should provide a seamlessly unified computing environment across multiple devices with synchronized data and application programs. As such, it allows users to freely switch their workspace from one device to another while continuing the interaction with the available applications. In order to support video applications, the cloud system should provide seamless video synchronization among the multiple devices. However, we note that the current cloud services do not provide efficient data flow among devices. In this paper, we propose and develop a new reliable transport protocol to support video synchronization for the personal virtual cloud system. In order to cope with battery limitation of many mobile devices in personal virtual cloud system, the proposed protocol is designed to provide energy efficient video communications. Our simulation results show that the proposed protocol can reduce end users power consumption up to 25 % compared to the legacy TCP with given packet loss probabilities and the average length of error bursts.

Mobile device is an important interactive platform. Due to the limitation of computation, memory, display area and energy, how to realize the efficient and real-time interaction of 3D models based on mobile devices is an important research topic. Considering features of mobile devices, this paper adopts remote rendering mode and point models, and then, proposes a transmission and rendering approach that could interact in real time. First, improved simplification algorithm based on MLS and display resolution of mobile devices is proposed. Then, a hierarchy selection of point models and a QoS transmission control strategy are given based on interest area of operator, interest degree of object in the virtual environment and rendering error. They can save the energy consumption. Finally, the rendering and interaction of point models are completed on mobile devices. The experiments show that our method is efficient.

Since malwares in mobile devices are expected to follow the same evolution of malwares in PC environment, it seems useful to apply malware defense techniques in PC environment to mobile devices. However, the malware defense techniques have limitations in terms of energy efficiency and maintenance, so that it will be inefficient to use the techniques on mobile devices, especially if the number of mobile malwares increases explosively. In this paper, we propose an energy-efficient run-time detection scheme which detects malware-infected executables and dynamic libraries on mobile devices. The proposed scheme works under collaboration between mobile devices and a binary- inspection server. To reduce energy consumption for security operation and achieve lightweight and easy maintenance, malware detection is delegated to the server. In experiments with a mobile device under embedded Linux, we show that our scheme guarantees the use of less energy of mobile devices and keeps security of all the mobile devices up-to-date easily and provides the mobile devices with strong protection that puts the advantages of the malware defense techniques in PC environment together.