Power Consumption Measurement and Scenario Based Energy Model in Wearable Computing Applications

The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

Cloud computing contribution to manufacturing industry

Manufacturing industry has been always facing challenge to improve the production efficiency, product quality, innovation ability and struggling to adopt cost-effective manufacturing system. In recent years cloud computing is emerging as one of the major enablers for the manufacturing industry. Combining the emerged cloud computing and other advanced manufacturing technologies such as Internet of Things, service-oriented architecture (SOA), networked manufacturing (NM) and manufacturing grid (MGrid), with existing manufacturing models and enterprise information technologies, a new paradigm called cloud manufacturing is proposed by the recent literature. This study presents concepts and ideas of cloud computing and cloud manufacturing. The concept, architecture, core enabling technologies, and typical characteristics of cloud manufacturing are discussed, as well as the difference and relationship between cloud computing and cloud manufacturing. The research is based on mixed qualitative and quantitative methods, and a case study. The case is a prototype of cloud manufacturing solution, which is software platform cooperated by ATR Soft Oy and SW Company China office. This study tries to understand the practical impacts and challenges that are derived from cloud manufacturing. The main conclusion of this study is that cloud manufacturing is an approach to achieve the transformation from traditional production-oriented manufacturing to next generation service-oriented manufacturing. Many manufacturing enterprises are already using a form of cloud computing in their existing network infrastructure to increase flexibility of its supply chain, reduce resources consumption, the study finds out the shift from cloud computing to cloud manufacturing is feasible. Meanwhile, the study points out the related theory, methodology and application of cloud manufacturing system are far from maturity, it is still an open field where many new technologies need to be studied.

Cyber foraging for green computing, improving performance and prolonging battery life of mobile devices

The increasing dependency of everyday life on mobile devices also increases the number and complexity of computing tasks to be supported by these devices. However, the inherent requirement of mobility restricts them from being resources rich both in terms of energy (battery capacity) and other computing resources such as processing capacity, memory and other resources. This thesis looks into cyber foraging technique of offloading computing tasks. Various experiments on android mobile devices are carried out to evaluate offloading benefits in terms of sustainability advantage, prolonging battery life and augmenting the performance of mobile devices. This thesis considers two scenarios of cyber foraging namely opportunistic offloading and competitive offloading. These results show that the offloading scenarios are important for both green computing and resource augmentation of mobile devices. A significant advantage in battery life gain and performance enhancement is obtained. Moreover, cyber foraging is proved to be efficient in minimizing energy consumption per computing tasks. The work is based on scavenger cyber foraging system. In addition, the work can be used as a basis for studying cyber foraging and other similar approaches such as mobile cloud/edge computing for internet of things devices and improving the user experiences of applications by minimizing latencies through the use of potential nearby surrogates.