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

Energy Efficiency Analysis And Optimization For Mobile Platforms

The introduction of mobile devices changed the landscape of computing. Gradually, these devices are replacing traditional personal computer (PCs) to become the devices of choice for entertainment, connectivity, and productivity. There are currently at least 45.5 million people in the United States who own a mobile device, and that number is expected to increase to 1.5 billion by 2015. Users of mobile devices expect and mandate that their mobile devices have maximized performance while consuming minimal possible power. However, due to the battery size constraints, the amount of energy stored in these devices is limited and is only growing by 5% annually. As a result, we focused in this dissertation on energy efficiency analysis and optimization for mobile platforms. We specifically developed SoftPowerMon, a tool that can power profile Android platforms in order to expose the power consumption behavior of the CPU. We also performed an extensive set of case studies in order to determine energy inefficiencies of mobile applications. Through our case studies, we were able to propose optimization techniques in order to increase the energy efficiency of mobile devices and proposed guidelines for energy-efficient application development. In addition, we developed BatteryExtender, an adaptive user-guided tool for power management of mobile devices. The tool enables users to extend battery life on demand for a specific duration until a particular task is completed. Moreover, we examined the power consumption of System-on-Chips (SoCs) and observed the impact on the energy efficiency in the event of offloading tasks from the CPU to the specialized custom engines. Based on our case studies, we were able to demonstrate that current software-based power profiling techniques for SoCs can have an error rate close to 12%, which needs to be addressed in order to be able to optimize the energy consumption of the SoC. Finally, we summarize our contributions and outline possible direction for future research in this field

ADAPTIVE POWER MANAGEMENT FOR COMPUTERS AND MOBILE DEVICES

Power consumption has become a major concern in the design of computing systems today. High power consumption increases cooling cost, degrades the system reliability and also reduces the battery life in portable devices. Modern computing/communication devices support multiple power modes which enable power and performance tradeoff. Dynamic power management (DPM), dynamic voltage and frequency scaling (DVFS), and dynamic task migration for workload consolidation are system level power reduction techniques widely used during runtime. In the first part of the dissertation, we concentrate on the dynamic power management of the personal computer and server platform where the DPM, DVFS and task migrations techniques are proved to be highly effective. A hierarchical energy management framework is assumed, where task migration is applied at the upper level to improve server utilization and energy efficiency, and DPM/DVFS is applied at the lower level to manage the power mode of individual processor. This work focuses on estimating the performance impact of workload consolidation and searching for optimal DPM/DVFS that adapts to the changing workload. Machine learning based modeling and reinforcement learning based policy optimization techniques are investigated. Mobile computing has been weaved into everyday lives to a great extend in recent years. Compared to traditional personal computer and server environment, the mobile computing environment is obviously more context-rich and the usage of mobile computing device is clearly imprinted with user\u27s personal signature. The ability to learn such signature enables immense potential in workload prediction and energy or battery life management. In the second part of the dissertation, we present two mobile device power management techniques which take advantage of the context-rich characteristics of mobile platform and make adaptive energy management decisions based on different user behavior. We firstly investigate the user battery usage behavior modeling and apply the model directly for battery energy management. The first technique aims at maximizing the quality of service (QoS) while keeping the risk of battery depletion below a given threshold. The second technique is an user-aware streaming strategies for energy efficient smartphone video playback applications (e.g. YouTube) that minimizes the sleep and wake penalty of cellular module and at the same time avoid the energy waste from excessive downloading. Runtime power and thermal management has attracted substantial interests in multi-core distributed embedded systems. Fast performance evaluation is an essential step in the research of distributed power and thermal management. In last part of the dissertation, we present an FPGA based emulator of multi-core distributed embedded system designed to support the research in runtime power/thermal management. Hardware and software supports are provided to carry out basic power/thermal management actions including inter-core or inter-FPGA communications, runtime temperature monitoring and dynamic frequency scaling

FlexStream: SDN-Based Framework for Programmable and Flexible Adaptive Video Streaming

With the tremendous increase in video traffic fueled by smartphones, tablets, 4G LTE networks, and other mobile devices and technologies, providing satisfactory services to end users in terms of playback quality and a fair share of network resources become challenging. As a result, an HTTP video streaming protocol was invented and widely adopted by most video providers today with the goal of maximizing the user’s quality of experience. However, despite the intensive efforts of major video providers such as YouTube and Netflix to improve their players, several studies as well as our measurements indicate that the players still suffer from several performance issues including instability and sub-optimality in the video bitrate, stalls in the playback, unfairness in sharing the available bandwidth, and inefficiency with regard to network utilization, considerably degrading the user’s QoE. These issues are frequently experienced when several players start competing over a common bottleneck. Interestingly, the root cause of these issues is the intermittent traffic pattern of the HTTP adaptive protocol that causes the players to over-estimate the available bandwidth and stream unsustainable video bitrates. In addition, the wireless network standards today do not allow the network to have a fine-grain control over individual devices which is necessary for providing resource usage coordination and global policy enforcement. We show that enabling such a network-side control would drive each device to fairly and efficiently utilize the network resources based on its current context, which would result in maximizing the overall viewing experience in the network and optimizing the bandwidth utilization. In this dissertation, we propose FlexStream, a flexible and programmable Software-Defined Network (SDN) based framework that solves all the adaptive streaming problems mentioned above. We develop FlexStream on top of the SDN-based framework that extends SDN functionality to mobile end devices, allowing for a fine-grained control and management of bandwidth based on real time context-awareness and specified policy. We demonstrate that FlexStream can be used to manage video delivery for a set of end devices over WiFi and cellular links and can effectively alleviate common problems such as player instability, playback stalls, large startup delay, and inappropriate bandwidth allocation. FlexStream offloads several tasks such as monitoring and policy enforcement to end-devices, while a network element (i.e., Global Controller), which has a global view of a network condition, is primarily employed to manage the resource allocation. This also alleviates the need for intrusive, large and costly traffic management solutions within the network, or modifications to servers that are not feasible in practice. We define an optimization method within the global controller for resource allocation to maximize video QoE considering context information, such as screen size and user priority. All features of FlexStream are implemented and validated on real mobile devices over real Wi-Fi and cellular networks. To the best of our knowledge, FlexStream is the first implementation of SDN-based control in a live cellular network that does not require any internal network support for SDN functionality

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

Optimizing the delivery of multimedia over mobile networks

Mención Internacional en el título de doctorThe consumption of multimedia content is moving from a residential environment to mobile phones. Mobile data traffic, driven mostly by video demand, is increasing rapidly and wireless spectrum is becoming a more and more scarce resource. This makes it highly important to operate mobile networks efficiently. To tackle this, recent developments in anticipatory networking schemes make it possible to to predict the future capacity of mobile devices and optimize the allocation of the limited wireless resources. Further, optimizing Quality of Experience—smooth, quick, and high quality playback—is more difficult in the mobile setting, due to the highly dynamic nature of wireless links. A key requirement for achieving, both anticipatory networking schemes and QoE optimization, is estimating the available bandwidth of mobile devices. Ideally, this should be done quickly and with low overhead. In summary, we propose a series of improvements to the delivery of multimedia over mobile networks. We do so, be identifying inefficiencies in the interconnection of mobile operators with the servers hosting content, propose an algorithm to opportunistically create frequent capacity estimations suitable for use in resource optimization solutions and finally propose another algorithm able to estimate the bandwidth class of a device based on minimal traffic in order to identify the ideal streaming quality its connection may support before commencing playback. The main body of this thesis proposes two lightweight algorithms designed to provide bandwidth estimations under the high constraints of the mobile environment, such as and most notably the usually very limited traffic quota. To do so, we begin with providing a thorough overview of the communication path between a content server and a mobile device. We continue with analysing how accurate smartphone measurements can be and also go in depth identifying the various artifacts adding noise to the fidelity of on device measurements. Then, we first propose a novel lightweight measurement technique that can be used as a basis for advanced resource optimization algorithms to be run on mobile phones. Our main idea leverages an original packet dispersion based technique to estimate per user capacity. This allows passive measurements by just sampling the existing mobile traffic. Our technique is able to efficiently filter outliers introduced by mobile network schedulers and phone hardware. In order to asses and verify our measurement technique, we apply it to a diverse dataset generated by both extensive simulations and a week-long measurement campaign spanning two cities in two countries, different radio technologies, and covering all times of the day. The results demonstrate that our technique is effective even if it is provided only with a small fraction of the exchanged packets of a flow. The only requirement for the input data is that it should consist of a few consecutive packets that are gathered periodically. This makes the measurement algorithm a good candidate for inclusion in OS libraries to allow for advanced resource optimization and application-level traffic scheduling, based on current and predicted future user capacity. We proceed with another algorithm that takes advantage of the traffic generated by short-lived TCP connections, which form the majority of the mobile connections, to passively estimate the currently available bandwidth class. Our algorithm is able to extract useful information even if the TCP connection never exits the slow start phase. To the best of our knowledge, no other solution can operate with such constrained input. Our estimation method is able to achieve good precision despite artifacts introduced by the slow start behavior of TCP, mobile scheduler and phone hardware. We evaluate our solution against traces collected in 4 European countries. Furthermore, the small footprint of our algorithm allows its deployment on resource limited devices. Finally, in an attempt to face the rapid traffic increase, mobile application developers outsource their cloud infrastructure deployment and content delivery to cloud computing services and content delivery networks. Studying how these services, which we collectively denote Cloud Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding some of the performance limitations of today’s mobile apps. To that end, we perform the first empirical study of the complex dynamics between applications, MNOs and CSPs. First, we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign to identify the most prevalent CSPs supporting today’s mobile Internet. Then, we investigate how well these services interconnect with major European MNOs at a topological level, and measure their performance over European MNO networks through a month-long measurement campaign on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs are used by 85% of apps, and observe significant differences in their performance across different MNOs due to the nature of their services, peering relationships with MNOs, and deployment strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming, and presence of middleboxes, but not influenced by the choice of DNS resolver. We also observe that the choice of operator’s Point of Presence (PoP) may inflate by at least 20% the delay towards popular websites.This work has been supported by IMDEA Networks Institute.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Ahmed Elmokashfi.- Secretario: Rubén Cuevas Rumín.- Vocal: Paolo Din

Network-aware video streaming for future media Internet

272 p

Bagadus App: Notational data capture and instant video analysis using mobile devices

Enormous amounts of money and other resources are poured into professional soccer today. Teams will do anything to get a competitive advantage, including investing heavily in new technology for player development and analysis. In this thesis, we investigate and implement an instant analytical system that captures sports notational data and combines it with high-quality virtual view video from the Bagadus system, removing the manual labor of traditional video analysis. We present a multi-platform mobile application and a playback system, which together act as a state-of-the-art analytical tool providing soccer experts with the means of capturing annotations and immediately play back zoomable and pannable video on stadium big screens, computers and mobile devices. By controlling remote playback and drawing on video through the app, sports professionals can provide instant, video-backed analysis of interesting situations on the pitch to players, analysts or even spectators. We investigate how to best design, implement and combine these components into a Instant Replay Analytical Subsystem for the Bagadus project to create anautomated way of viewing and controlling video based on annotations. We describe how the system is optimized in terms of performance, to achieve real-time video control and drawing; scalability, by minimizing network data and memory usage; and usability, through a user-tested interface optimized for accuracy and speed for notational data capture, as well as user customization based on roles and easy filtering of annotations. The system has been tested and adapted through real life scenarios at Alfheim Stadium for Tromsø Idrettslag (TIL) and at Ullevaal Stadion for the Norway national football team

Bagadus App: Notational data capture and instant video analysis using mobile devices

Enormous amounts of money and other resources are poured into professional soccer today. Teams will do anything to get a competitive advantage, including investing heavily in new technology for player development and analysis. In this thesis, we investigate and implement an instant analytical system that captures sports notational data and combines it with high-quality virtual view video from the Bagadus system, removing the manual labor of traditional video analysis. We present a multi-platform mobile application and a playback system, which together act as a state-of-the-art analytical tool providing soccer experts with the means of capturing annotations and immediately play back zoomable and pannable video on stadium big screens, computers and mobile devices. By controlling remote playback and drawing on video through the app, sports professionals can provide instant, video-backed analysis of interesting situations on the pitch to players, analysts or even spectators. We investigate how to best design, implement and combine these components into a Instant Replay Analytical Subsystem for the Bagadus project to create an automated way of viewing and controlling video based on annotations. We describe how the system is optimized in terms of performance, to achieve real-time video control and drawing; scalability, by minimizing network data and memory usage; and usability, through a user tested interface optimized for accuracy and speed for notational data capture, as well as user customization based on roles and easy filtering of annotations. The system has been tested and adapted through real life scenarios at Alfheim Stadium for Tromsø Idrettslag (TIL) and at Ullevaal Stadion for the Norway national football team