Mohammad Ashraful Hoque

Energy Efficient Multimedia Streaming to Mobile Devices — A Survey

Energy conservation in battery powered mobile devices that perform wireless multimedia streaming has been a significant research problem since last decade. This is because these mobile devices consume a lot of power while receiving, decoding and ultimately, presenting the multimedia content. What makes things worse is the fact that battery technologies have not evolved enough to keep up with the rapid advancement of mobile devices. This survey examines solutions that have been proposed during the last few years, to improve the energy efficiency of wireless multimedia streaming in mobile hand-held devices. We categorize the research work according to different layers of the Internet protocol stack they utilize. Then, we again regroup these studies based on different traffic scheduling and multimedia content adaptation mechanisms. The traffic scheduling category contains those solutions that optimize the wireless receiving energy without changing the actual multimedia content. The second category on the other hand, specifically modifies the content, in order to reduce the energy consumed by the wireless receiver and to decode and view the content. We compare them and provide evidence of the fact that some of these tactics already exist in modern smaprtphones and provide energy savings with real measurements. In addition, we discuss some relevant literature on the complementary problem of energy-aware multimedia delivery from mobile devices and contrast with our target approaches for multimedia transmission to mobile devices.

Using crowd-sourced viewing statistics to save energy in wireless video streaming

Video streaming on smartphones is one of the most popular but also most energy hungry services today. Using mobile video services results in two contradictory sources of energy waste for smartphones: i) energy waste because of excessively aggressive prefetching of content that the user will not watch because of abandoning the session, and ii) excessive amount of tail energy, which is energy wasted by keeping the wireless interface powered on after receiving a chunk of content; this is caused by prefetching chunks that are too small. To remedy this, we propose a novel download scheduling algorithm based on crowd-sourced video viewing statistics. Our algorithm judiciously evaluates the probability of a user interrupting a video viewing in order to perform the right amount of prefetching. In this way, the algorithm balances the amount of the two above-mentioned kinds of energy waste. By simulations, we show that our scheduler cuts the energy waste to half compared to existing download strategies. We have also developed an Android prototype that implements the download scheduler together with a novel downloader that speeds up the download by exploiting the Fast Start technique. The prototype exhibits the desired properties of the scheduler, and its faster downloading mechanism yields further energy savings of up to 80% compared to the default Android YouTube app.

Streaming over 3G and LTE: how to save smartphone energy in radio access network-friendly way

Energy consumption of mobile devices is a great concern and streaming applications are among the most power hungry ones. We evaluate the energy saving potential of shaping streaming traffic into bursts before transmitting it over 3G and LTE networks to smartphones. The idea is that in between the bursts, the phone has sufficient time to switch from the high-power active state to low-power states. We investigate the impact of the network parameters, namely inactivity timers and discontinuous reception, on the achievable energy savings and on the radio access network signaling load. The results confirm that traffic shaping is an effective way to save energy, even up to 60% of energy saved when streaming music over LTE. However, we note large differences in the signaling load. LTE with discontinuous reception and long inactivity timer value achieves the energy savings with no extra signaling load, whereas non-standard Fast Dormancy in 3G can multiply the signaling traffic by a factor of ten.

On the energy efficiency of proxy-based traffic shaping for mobile audio streaming

We study how much energy can be saved by reshaping audio streaming traffic before receiving at the mobile devices. The rationale is the following: Mobile network interfaces (WLAN and 3G) are in active mode when they transmit or receive data, otherwise they are in idle/sleep mode. To save energy, minimum possible time should be spent in active mode and maximum in idle/sleep mode. It is well known that by reshaping the usually constant bit rate multimedia traffic into bursts, it is possible to spend more time in idle/sleep mode leading to impressive energy savings. We propose a proxy-based solution that shapes an audio stream into bursts before relaying the traffic to the mobile device. The novelty of our work is an evaluation of the energy savings using such a proxy with different configurations for both WLAN access with standard 802.11 Power Saving Mode and 3G access. We conclude that for WLAN access, proxy causes power savings of 30%-65% depending on the audio stream rate, location of the proxy and amount of cross traffic. In the case of 3G, the effectiveness of our proxy seems to vary depending on the phone model and operator. In some cases, the energy savings are encouraging, while in other cases the proxy turns out to be ineffective due to abnormal delay variation and TCP flow control behavior.

Modeling, Profiling, and Debugging the Energy Consumption of Mobile Devices

Software energy profilers are the tools to measure the energy consumption of mobile devices, applications running on those devices, and various hardware components. They adopt different modeling and measurement techniques. In this article, we aim to review a wide range of such energy profilers for mobile devices. First, we introduce the terminologies and describe the power modeling and measurement methodologies applied in model-based energy profiling. Next, we classify the profilers according to their implementation and deployment strategies, and compare the profiling capabilities and performance between different types. Finally, we point out their limitations and the corresponding challenges.

Dissecting mobile video services: An energy consumption perspective

Multimedia streaming applications are among the most energy hungry applications in smartphones. The energy consumption mostly depends on the delivery techniques and on the power management techniques of wireless interfaces (Wi-Fi and 3G). In order to provide insights on what kind of streaming techniques exist, how they work on different mobile platforms, and what is their impact on the energy consumption of mobile phones, we have done a large set of active measurements with several smartphones having both Wi-Fi and cellular network access. Our analysis reveals five different techniques to deliver the content to the video players. The selection of a technique depends on the device, player, quality, and service. The results from our power measurements allow us to conclude that none of the identified techniques is optimal because they take none of the following facts into account: access technology used, user behaviour, and user preferences concerning data waste. However, we point out the techniques that provide the most attractive trade-offs in particular situations. Furthermore, we make several observations on the energy consumption of different players, containers, and video qualities that should be taken into consideration when optimizing the energy consumption.

Mobile multimedia streaming techniques

Multimedia streaming to mobile devices is challenging for two reasons. First, the way content is delivered to the client must ensure that a user does not experience a long initial playback delay or a distorted playback in the middle of a streaming session. Second, multimedia streaming applications are among the most energy hungry applications in smartphones. The energy consumption mostly depends on the delivery techniques and on the power management techniques of wireless interfaces (Wi-Fi, 3G, and 4G). In order to provide insights on what kind of streaming techniques exist, how they work on different mobile platforms, their efforts in providing quality of experience, and their impact on energy consumption of mobile phones, we have done a large set of active measurements with several smartphones having both Wi-Fi and cellular network access. Our analysis reveals five different techniques to deliver the content to the video players. The selection of a technique depends on the mobile platform, device, player, quality, and service. The results from our traffic and power measurements allow us to conclude that none of the identified techniques is optimal because they take none of the following facts into account: access technology used, user behavior, and user preferences concerning data waste. We point out the techniques that provide the most attractive trade-offs in particular situations.

Mobile Multimedia Streaming Techniques: QoE and Energy Consumption Perspective

Multimedia streaming to mobile devices is challenging for two reasons. First, the way content is delivered to the client must ensure that a user does not experience a long initial playback delay or a distorted playback in the middle of a streaming session. Second, multimedia streaming applications are among the most energy hungry applications in smartphones. The energy consumption mostly depends on the delivery techniques and on the power management techniques of wireless interfaces (Wi-Fi, 3G, and 4G). In order to provide insights on what kind of streaming techniques exist, how they work on different mobile platforms, their efforts in providing quality of experience, and their impact on energy consumption of mobile phones, we have done a large set of active measurements with several smartphones having both Wi-Fi and cellular network access. Our analysis reveals five different techniques to deliver the content to the video players. The selection of a technique depends on the mobile platform, device, player, quality, and service. The results from our traffic and power measurements allow us to conclude that none of the identified techniques is optimal because they take none of the following facts into account: access technology used, user behavior, and user preferences concerning data waste. We point out the techniques that provide the most attractive trade-offs in particular situations.

Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach

This article proposes a novel energy-efficient multimedia delivery system called EStreamer. First, we study the relationship between buffer size at the client, burst-shaped TCP-based multimedia traffic, and energy consumption of wireless network interfaces in smartphones. Based on the study, we design and implement EStreamer for constant bit rate and rate-adaptive streaming. EStreamer can improve battery lifetime by 3x, 1.5x, and 2x while streaming over Wi-Fi, 3G, and 4G, respectively.

Energy consumption anatomy of live video streaming from a smartphone

Smartphones are frequently used to shoot and share videos online and emerging applications, such as Augmented Reality, will increase the usage of the camera. Unfortunately, shooting and streaming video drains a modern smartphones battery very quickly. We report results from a measurement study to dissect the smartphone energy consumption when using such an application. Our main findings are that the majority of power is drawn already when the camera is in focus mode and not yet recording. This power is drawn by the camera internal hardware and some other hardware of the smartphone related to the video processing, and none of this hardware seems to scale the power draw with the video resolution or bit rate. We also study the effectiveness of two simple optimization techniques, namely frame bundling to optimize the radio usage and more aggressive frequency and voltage scaling to reduce the computational power draw. We conclude that while the mechanisms are effective, their potential is overshadowed by the large power draw of other hardware.