Adaptive buffer power save mechanism for mobile multimedia streaming

With the proliferation of wireless networks, the use of mobile devices to stream multimedia is growing in popularity. Although the devices are improving in that they are becoming smaller, more complex and capable of running more applications than ever before, there is one aspect of them that is lagging behind. Batteries have seen little development, even though they are one of the most important parts of the devices. Multimedia streaming puts extra pressure on batteries, causing them to discharge faster. This often means that streaming tasks can not be completed, resulting in significant user dissatisfaction. Consequently, effort is required to devise mechanisms to enable and increase in battery life while streaming multimedia. In this context, this thesis presents a novel algorithm to save power in mobile devices during the streaming of multimedia content. The proposed Adaptive-Buffer Power Save Mechanism (AB-PSM) controls how the data is sent over wireless networks, achieving significant power savings. There is little or no effect on the user and the algorithm is very simple to implement. The thesis describes tests which show the effectiveness of AB-PSM in comparison with the legacy power save mechanism present in IEEE 802.11. The thesis also presents a detailed overview of the IEEE 802.11 protocols and an in-depth literature review in the area of power saving during multimedia streaming. A novel analysis of how the battery of a mobile device is affected by multimedia streaming in its different stages is given. A total-power-save algorithm is then described as a possible extension to the Adaptive-Buffer Power Save Mechanism

Transparent resource sharing framework for Internet services on handheld devices

Abstract Handheld devices have limited processing power and a short battery lifetime. As a result, computational intensive applications can not run appropriately or cause the device to run out-of-battery too early. Additionally, Internet-based service providers targeting these mobile devices lack information to estimate the remaining battery autonomy and have no view on the availability of idle resources in the neighborhood of the handheld device. In this paper, we propose a transparent resource sharing framework that enables service providers to delegate (a part of) a client application from a handheld device to idle resources in the LAN the device is connected to. The key component is the Resource Sharing service, hosted on the LAN gateway, which can be queried by Internet-based service providers. The service includes a battery model to predict the remaining battery lifetime. We describe the concept of Resource-Sharingas-a-Service that allows users of handheld devices to subscribe to the Resource Sharing service. In a proof-of-concept, we evaluate the delay to offload a client application to an idle computer and study the impact on battery autonomy as a function of the CPU cycles that can be offloaded

Modeling and managing energy consumption of mobile devices

Thanks to the significant improvement in the processing and networking capabilities of mobile devices, mobile devices today can run applications that require complex computation and high network bandwidth. As these applications become ever more popular, a rise is seen in the energy demand that is generated by a typical usage of mobile devices, with the result that existing battery technology is not able to satisfy the growing demand. Improving the energy efficiency of mobile devices and applications has, therefore, become essential. In this thesis, we investigate the energy consumption of mobile devices and propose practical solutions for improving the energy efficiency of wireless data transmission. We propose power models of wireless data transmission over Wi-Fi and show how the power consumption is related to power-saving mechanisms, to Internet traffic characteristics, and to the network throughput. We utilize the linear dependency of transmission costs on network throughput in order to extend the linear regression power models from microprocessor level to system level. These power models provide us with an insight into developing software with energy-efficient wireless data transmission. In this thesis, we present three strategies for reducing transmission cost: applying lossless data compression to network traffic data, scheduling the transmission based on the prediction of network conditions, and power management of the wireless network interface based on the predicted traffic intervals. Our strategies consider the trade-offs between computational and transmission costs, and between energy consumption and transmission performance. In addition, we apply statistical methods for implementing prediction utilities. Finally, considering the complexity in the context collection and processing, we propose an event-driven framework that can be used for implementing, deploying and managing various energy-efficient strategies on mobile platforms

Image Processing for Machine Vision Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Energy-aware adaptive solutions for multimedia delivery to wireless devices

The functionality of smart mobile devices is improving rapidly but these devices are limited in terms of practical use because of battery-life. This situation cannot be remedied by simply installing batteries with higher capacities in the devices. There are strict limitations in the design of a smartphone, in terms of physical space, that prohibit this “quick-fix” from being possible. The solution instead lies with the creation of an intelligent, dynamic mechanism for utilizing the hardware components on a device in an energy-efficient manner, while also maintaining the Quality of Service (QoS) requirements of the applications running on the device. This thesis proposes the following Energy-aware Adaptive Solutions (EASE): 1. BaSe-AMy: the Battery and Stream-aware Adaptive Multimedia Delivery (BaSe-AMy) algorithm assesses battery-life, network characteristics, video-stream properties and device hardware information, in order to dynamically reduce the power consumption of the device while streaming video. The algorithm computes the most efficient strategy for altering the characteristics of the stream, the playback of the video, and the hardware utilization of the device, dynamically, while meeting application’s QoS requirements. 2. PowerHop: an algorithm which assesses network conditions, device power consumption, neighboring node devices and QoS requirements to decide whether to adapt the transmission power or the number of hops that a device uses for communication. PowerHop’s ability to dynamically reduce the transmission power of the device’s Wireless Network Interface Card (WNIC) provides scope for reducing the power consumption of the device. In this case shorter transmission distances with multiple hops can be utilized to maintain network range. 3. A comprehensive survey of adaptive energy optimizations in multimedia-centric wireless devices is also provided. Additional contributions: 1. A custom video comparison tool was developed to facilitate objective assessment of streamed videos. 2. A new solution for high-accuracy mobile power logging was designed and implemented

High efficiency smart voltage regulating module for green mobile computing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis a design for a smart high efficiency voltage regulating module capable of supplying the core of modern microprocessors incorporating dynamic voltage and frequency scaling (DVS) capability is accomplished using a RISC based microcontroller to facilitate all the functions required to control, protect, and supply the core with the required variable operating voltage as set by the DVS management system. Normally voltage regulating modules provide maximum power efficiency at designed peak load, and the efficiency falls off as the load moves towards lesser values. A mathematical model has been derived for the main converter and small signal analysis has been performed in order to determine system operation stability and select a control scheme that would improve converter operation response to transients and not requiring intense computational power to realize. A Simulation model was built using Matlab/Simulink and after experimenting with tuned PID controller and fuzzy logic controllers, a simple fuzzy logic control scheme was selected to control the pulse width modulated converter and several methods were devised to reduce the requirements for computational power making the whole system operation realizable using a low power RISC based microcontroller. The same microcontroller provides circuit adaptations operation in addition to providing protection to load in terms of over voltage and over current protection. A novel circuit technique and operation control scheme enables the designed module to selectively change some of the circuit elements in the main pulse width modulated buck converter so as to improve efficiency over a wider range of loads. In case of very light loads as the case when the device goes into standby, sleep or hibernation mode, a secondary converter starts operating and the main converter stops. The secondary converter adapts a different operation scheme using switched capacitor technique which provides high efficiency at low load currents. A fuzzy logic control scheme was chosen for the main converter for its lighter computational power requirement promoting implementation using ultra low power embedded controllers. Passive and active components were carefully selected to augment operational efficiency. These aspects enabled the designed voltage regulating module to operate with efficiency improvement in off peak load region in the range of 3% to 5%. At low loads as the case when the computer system goes to standby or sleep mode, the efficiency improvent is better than 13% which will have noticeable contribution in extending battery run time thus contributing to lowering the carbon footprint of human consumption

Power Consumption Analysis, Measurement, Management, and Issues:A State-of-the-Art Review of Smartphone Battery and Energy Usage

The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed