Wireless adapter sleep scheduling based on video QoE: How to improve battery life when watching streaming video? M´arton Csernai, Andr´as Guly´as Budapest University of Technology and Economics Department of Telecommunications and Media Informatics 1117 Budapest, Magyar tud´osok k¨or´utja 2. Hungary Email: {csernai,gulyas}@tmit.bme.hu Abstract—Power management is a critical issue for mobile devices, where a significant portion of the total system energy can be often consumed by heavy wireless network activity. In this paper we present a framework that reduces the energy consumption of wireless mobile devices during streaming video content over Wireless LAN networks by utilizing the power saving mechanisms defined in the IEEE 802.11e standard. The framework allows video applications to directly optimize the overall energy efficiency by controlling the sleep cycles of wireless network adapters based on video QoE. The framework employs a simple QoE estimation algorithm that estimates the user level video quality, and adjusts the sleep intervals of the wireless adapter to maintain video quality while maximizing power efficiency. As an important part of our paper the building and configuration steps of a working testbed system is carefully described, which demonstrates the availability and efficiency of the U-APSD power saving technology at hand. A preliminary evaluation of the proposed framework supports that by enabling the WMM Power Saving feature 20-30% of total system energy can be saved even in case of asynchronous video traffic. Index Terms—wireless LAN, IEEE 802.11e, U-APSD, QoE, power management I. I NTRODUCTION Recently the Wireless LAN technology has spread to a growing number of mobile phones and with the advent of the tablets there are more and more battery limited wireless mobile devices connecting to the Internet. The majority of user initiated internet traffic is due to multimedia content (youtube, facebook, video chat), which imposes a great load on mobile devices with limited energy resources and the improvement of battery life is a widely researched critical issue. Many standards that define different mechanisms regarding power management of the wireless network adapter, such as IEEE 802.11e, have been around for years. However, to the best of our knowledge there are only a few complete integrated solutions that utilize the standardized technologies [1]. It is conveniently believed that U-APSD mechanism defined in 802.11e is best exploited in symmetrical traffic scenarios, such as VoIP, as the U-APSD triggering mechanism requires uplink data traffic at well defined time intervals. In most cases, even if the device supports the technology, the U-APSD feature is disabled by default and even professionals on forums advise to do so. This is due to the fact that even if the feature is enabled and configured properly, the user can experience problems with the wireless connection (i.e. in case of asynchronous traffic the lack of trigger packets sent uplink to the access point blocks the traffic flow) and there are hardly any applications supporting the technology. We aim to fill the gap by proposing a general application framework that allows mobile devices to employ the foregoing power saving mechanism. In this paper we investigate the possibilities to reduce the energy consumption of wireless mobile devices in case of streaming video content over Wireless LAN (WLAN) networks. The scope of our research extends to find the tradeoff between the quality of the video perceived by the end user and the energy efficiency of the wireless network adapter in the mobile device. As our main contribution we propose a general framework that allows video applications to directly optimize the power management in wireless network adapters by adaptively adjusting the sleep cycles of the network adapter based on the estimated measure of the video quality of user experience (QoE). The proposed framework is the combination of a simple QoE estimation algorithm and a packet sending mechanism, which can be widely implemented in various video player applications in the form of a network capable video player plugin. We found that it is an interesting challenge to be able to determine, which devices implement and support the required power saving protocols, let alone their precise configuration. As an important part of our paper the building and configuration steps of a working testbed system is carefully described, which demonstrates the availability and efficiency of the power saving technology at hand. There are numerous related proposals which optimize energy efficiency in mobile devices by using the sleep scheduling mechanisms in wireless network adapters [2], [3]. Fewer papers are concerned with energy optimization while streaming video content to wireless mobile devices. Lee et al. [4] propose a client-server architecture, that reduces the unnecessary transmission of bitstreams by using Scalable Video Coding on the server side and manages the power states of the network adapter based on the video buffer occupancy of the client. Mur et al. [5] propose an architectural change in 978-1-4577-0638-7 /11/$26.00 ©2011 IEEE the power saving protocol by designing an adaptive power saving mechanism that provides QoS to mobile devices using information available only at the MAC layer. Adams et al. [6] also propose an adaptive algorithm that defines different power saving levels for the wireless adapter, and switches between the states according to the power level of the battery of the device utilizing the Legacy Power Save protocol. Although all the proposals above achieve some boost in energy efficiency during video streaming, none of them includes a user level quality of experience feedback regarding the video content played on the mobile device and most of them requires some level of architectural change. The rest of the paper is structured as follows. Section II gives a brief overview of the power saving technologies in wireless networks looked at from our applications perspective. In Section III the proposed framework for power saving based on user level quality of experience is presented. We carefully describe in Section IV the building and configuration of our testbed system. Section V contains a preliminary evaluation of the proposed framework, which is based upon specific measurements conducted on the testbed. II. P OWER S AVING T ECHNOLOGIES IN W IRELESS N ETWORK D EVICES Power saving technologies in wireless networks describe and implement different mechanisms for devices to efficiently reduce their power consumption. There are many ways for a device to achieve energy efficiency during wireless communication, like adaptively adjusting the transmitter power of the wireless adapter [7], dynamically switching between single and multiple antenna use [8], and also by scheduling the sleep cycles of mobile devices [9]. In the case of our wireless video streaming scenario the most suitable method is the sleep scheduling based power saving technologies, since it is possible to download chunks of the video stream in advance if bandwidth allows, and while video is played from the buffer of the device, its wireless controller can be put to low energy consuming sleep mode. A. Power management in IEEE 802.11 Different power saving mechanisms have been built into the IEEE 802.11 standard [10] over time and most of them are types of sleep scheduling of the wireless network adapter. The basic principle behind all sleep scheduling mechanisms is that lots of energy is wasted listening on the wireless channel while there is nothing to receive or no data is being send. The sleep scheduler puts the wireless network adapter from time to time into low powered doze state, when there is no traffic between the access point (AP) and the mobile station. In this state the device is not able to transmit or receive packets. Also, the scheduler periodically wakes up the network adapter, so it can check if there is traffic intended for the mobile device. The AP keeps track of the power state of the stations by investigating the Power Management bits within the Frame Control field of the received frames and buffers packets destined for a mobile station while it is in doze state. The most basic power management scheme is available from the original version of the IEEE 802.11 standard, which is now often referred to as Legacy Power Save. Stations in legacy power saving mode wake up for every beacon frame that is sent by the AP, and learn about buffered packets addressed to them by examining the Traffic Indication Map (TIM) field of the beacon frame. The stations can request the buffered packets one at a time by sending PS-Poll packets to the AP as long as there are remaining buffered data indicated within the More Data bit in the frame control field. Note that this mechanism introduces a delay of downlink packets in the order of the beacon interval (its typical value is 100 ms) which is critical in most real-time applications and also the mechanism is very inefficient because the station needs to send one PS-Poll packet for every buffered packet [11]. B. U-APSD Protocol The IEEE 802.11e extension defines an enhanced power saving mechanism called Unscheduled Automatic Power Save Delivery (U-APSD) and this amendment has already been incorporated into IEEE 802.11-2007. The main idea behind the U-APSD design is that the power saving stations can indicate the instants, when they are awake, with data packets sent uplink to the AP. When the AP receives a trigger packet from a station, it responses with the packets that were buffered while the station was in doze state. A trigger packet sent by a station instantiates an unscheduled Service Period (SP). During this SP the AP sends buffered packets to the station and marks the last buffered packet with a special End Of Service Period (EOSP) bit within the QoS Control field of the QoS frame1 . The station is awake only for the duration of the SP then it goes back to doze state. The maximum length of an SP can be set by the station at association time with the Max SP Length bits. If there are more buffered data even after the SP has ended, this will be indicated by the AP in the More Data bit of the last packet of the SP. In this case the station triggers new SPs with QoS Null trigger packets until all buffered data is received. For a more detailed overview of the U-APSD protocol the reader is referred to [9]. The 802.11e standard defines four different access categories (AC) which correspond to four different transmit queues, which allow devices to prioritize their traffic over the wireless channel. The four ACs, ordered by descending priority, are defined for voice, video, best effort and background traffic. For a packet to go to a specific transmit queue, the DSCP2 field of the IP packet has to be marked with a value reflecting the respective AC. The corresponding DSCP value depends on the actual implementation of the U-APSD protocol, and may vary among devices. Also, trigger packets with different DSCP values will trigger different corresponding AC queues. 1 In a WMM WLAN session QoS MAC frames are sent instead of normal MAC frames. This type of frames contains an additional 2 byte QoS Control field [12]. 2 Differentiated Services Code Point The U-APSD power saving protocol is defined in the IEEE 802.11 standard but it is only optional for manufacturers to implement it. The market demand for Voice over IP capable WLAN mobile devices drove the Wi-Fi Alliance to issue a WiR Fi Multimedia Power Save certificate system. The WMM Power Save Certificate [13] is based on a subset of the IEEE 802.11e standard. The Alliance certificates products with WMM-PS that support the U-APSD power save protocol. It is noteworthy that the new IEEE 802.11n standard contains an enhancement to the U-APSD protocol called Unscheduled Power Save Multi-Poll (U-PSMP), which add some minor modifications to the power management protocol but doesn’t alter the U-APSD mechanism presented here. III. N ETWORK ADAPTER SLEEP SCHEDULING BASED ON VIDEO Q O E We propose a framework which is able to estimate the quality of video content in mobile devices, and adaptively cycles the sleep modes of the wireless adapter based on the video quality of experience (QoE). IEEE 802.11e and WMM Power Save technologies permit manufacturers and software developers to incorporate a power saving mechanism into the mobile devices’ energy management scheme through software and driver components specified according to standards. Our main contribution is a software framework which extends the WMM Power Save technology to streaming video applications. During video transmission a QoE estimation algorithm is run on the video content in the mobile device, and the U-APSD trigger packet sending interval is based upon the estimated QoE measure. A. QoE estimation The estimation of the user experience, which is a measure of the quality of the content directly perceived by users, gives an important guideline to enhance standard video content distribution techniques with network traffic optimization and hence energy saving features. The system is based on the so called no-reference image quality analysis. The no-reference method estimates user experience according to the displayed image properties and is very flexible and efficient since it doesn’t need any reference video signal to compare the output with. The idea of the estimation architecture is to search for specific distortions like blockiness, blurring, etc. in the output video. Typical distortions caused by network transmission errors and delays can be effectively detected by image processing methods. There are many such adequate QoE estimation algorithms, and we analyzed the method of T. Vlachos [14] and the BABU method [15]. Both of the algorithms calculate the QoE measure based on the blockiness of the decoded video image, which is the most typical distortion in packet switched networks. The Vlachos method requires slightly more computational power and produces more effective QoE estimates, while the BABU method places itself into a more energy efficient but slightly less reliable part of the trade-off space. Our analysis shows that both of them are suitable for video QoE estimation in today’s mobile device crowd. The measurements with the presented algorithms may be achieved in real time, which enables the video source to tune the UAPSD triggering parameters accordingly. B. U-APSD triggering based on video QoE Our mechanism adjusts the U-APSD power save protocol triggering interval based on the above mentioned estimated video QoE measure. The schematic view of our proposed framework can be seen in Figure 1. The mechanism gets input in the form of decoded video frames. The QoE estimation algorithm is then run on the decoded video data, and it determines the quality of the video by processing the video frame image. The different algorithms provide the QoE measures in different domains which has to be scaled accordingly to provide input for the trigger interval setting mechanism with fine enough resolution. This measure can also be scaled to the 5-grade Mean Opinion Score (MOS) system. Depending on the QoE measure the U-APSD triggering component will send out trigger packets on the WLAN channel. When the QoE estimate show bad video quality, the triggering component raises the frequency of the trigger packets. On the other hand, if the video quality is flawless, then it can lower the trigger frequency, thus enabling the wireless adapter of the mobile device to be in sleep mode for longer intervals. The trigger packets has to be a regular IP packet with DSCP field set according to the 802.11e QoS video AC. This ensures that in response to this packet the AP sends all packets to the mobile station, which were previously buffered at the AP while the network adapter of the mobile station was in sleep mode. When the transmission of the buffered packets is over, the AP marks the last packet with the More Data bit set to 0, and the network adapter goes back to sleep mode. Fig. 1: Schematic diagram of the U-APSD triggering mechanism based on estimated video QoE. We emphasize that for our framework to be fully functional the video stream has to be configured also on the server side according to the WMM Power Save standard. This means that the IP packets of the video stream only have to be flagged with the appropriate DSCP value, so that the WLAN AP directs them into the video AC queue, and buffers them as long as the mobile device is in sleep mode, and no other actions are required from the server (encoding, adaptivity etc.). The method is transparent from the server side which eases the introducion of the system independently from video content providers. Note that the right DSCP value may depend on the implementation of the AP firmware. Due to the architecture of our framework some limitations of the system arise. Besides the wireless channel, transmission error or delay in other segments of the network can also cause video quality degradation, which cannot be identified by our mechanism. In response, our mechanism tries to improve the video quality by setting higher value for the trigger packet sending frequency, which however is not going to help improving the video quality and will render the device to wake up more often, hence degrading its energy efficiency. Although providing high quality video content to end users can be considered far gone, the resolution of this issue is out of our scope and we look at it as future improvement to our framework. Setting the desired QoE level, the framework adaptively adjust the sleep scheduling intervals so that the desired QoE level is realized. Wireless channels with different throughput parameters (signal strength, saturation/congestion of the wireless channel), different energy efficiency while achieving the same QoE level. IV. T ESTBED AND CONFIGURATION STEPS We built a testbed which contains key resources of our proposed framework. It is a simplified setting compared to the framework, which is chosen so that the power saving efficiency of our framework could be finely tuned and measured. Wireless Access Point: Our testbed contains two HTC Dream mobile devices with Android 1.6 operating system, a Linksys WRT54G WLAN WiFi AP running DD-WRT v24 SP1 [16]. These devices are chosen since they are all WMM Power Save certified wireless LAN devices. The configuration in the Wireless/Advanced settings section of the AP is set so that it enables WMM support, and the device indicates this by carrying the Vendor Specific WME3 Information Element (IE) in its Beacon, Probe Response and Association Response management frames with WME Parameter Element set to 128 [12]. In Figure 2 there is a Wireshark [17] screenshot showing the WME IE within a Beacon frame and the meaning of the corresponding bits. This vendor specific tag sent by the AP lets mobile stations in the BSS to discover at association time whether or not they can use the power saving abilities defined in WMM Power Save. It contains every important information regarding the WMM Power Save mechanism broken down for the four different AC types. Such an association between an AP and station is called a WMM Association. Mobile devices: One of the mobile stations is also configured through its WLAN adapter driver configuration file [18] so that it enables the same power saving technology. In most cases, even if the device supports the technology, WMM Power Save feature is disabled by default. This can be due 3 WME is a former abbreviation for WMM, they are used interchangeably Fig. 2: Wireshark screenshot of the WME Information Element within a Beacon frame sent by the AP and the meaning of parameter bits. to the fact that if the feature is enabled but not configured correctly, the user can experience problems with the wireless connection (i.e the lack of trigger packets sent uplink can block all traffic to the mobile device). It is also noteworthy that we might have to dig deep into the device’s configuration files to enable the feature. For our framework to be functional we set the device to use U-APSD protocol for its video and voice Access Categories (AC VI and AC VO, respectively). Now, when the mobile device learns from the WLAN management frames that the AP supports WMM Power Save, it sends back the appropriate IE in its Association Request management frame, where it indicates for which ACs it enables U-APSD (see Figure 3). If the Association Request frame contained the WME IE, then the AP replies with an Association Response which carries also a WME Information Element. Fig. 3: Wireshark screenshot of the WME Information Element within an Association Request frame sent by the station and the meaning of parameter bits. We implemented an Android [19] application for the mobile device so that it can send trigger packets at a given interval. The trigger frame is a simple UDP packet with the 1 byte IP TOS field set to 160 in decimal representation. The exact value is defined in the configuration file of the wireless adapter as the DSCP code corresponding to the video AC [18]. The packet is then sent through the video AC from the station to the AP, which in turn will trigger the buffered packets belonging to the video AC queue to be flushed to the mobile station. This way the sleep time interval of the station can be quantitatively adjusted, and also the frequency of the video data transfer can be easily set, which after all effects the quality of the video. Video Server: On the server side QuickTime Streaming Server [20] is used running over Mac OS X from which RTP streaming video data is sent to the mobile devices through the AP. The video stream is configured to be easily playable by the mobile devices (25 frames per second, 200 kbps data rate, 8 key frame per second). A network proxy running iptables is also set up in the video transmission flow, which tags the Fig. 4: Testbed configuration IP TOS field of each video RTP packets to 0xb8 (184d ). This also puts the video traffic into the video AC on the WLAN AP which will buffer these packet until the mobile device is in sleep mode. Power Usage Monitoring: Our trigger packet sending application is implemented to include the mobile device’s current power consumption measure in mA in the trigger packet, which is in turn sent to a monitoring Linux server connected to one of the LAN ports of the AP, where the measurements data are logged and evaluated in real time. We checked the wireless traffic during video streaming with Wireshark to see if WMM Power Save was properly configured. According to the 802.11 level network traffic we could verify that the AP started to send the buffered data packets to the station only when the device sent a special trigger packet to the AP. In response, the AP sent all buffered packets4 to the station. Fig. 5: Power consumption in mobile devices configured with U-APSD vs. Legacy Power Save Mode. show that the device power consumption is higher in case of higher video bit rates for identical MOS values and if we enable a slightly degraded video quality the device can save some 5-7% additional energy. V. P OWER EFFICIENCY MEASUREMENTS For the evaluation of the proposed framework we conducted measurements on our testbed. The measurements aim at determining the power saving capability in the mobile devices introduced by our framework. Also by measuring the different power consumption levels which correspond to different subjective QoE measures, we can quantify the available power saving possibility that can be achieved by defining the desired QoE level in the mobile device. As a reference measurement we compare the U-APSD power saving mechanism with Legacy Power Save Mode. Figure 5 shows the power consumption of the two identical mobile devices (brightness of the displays set to the same setting, etc.), one with WMM Power Save enabled and the other configured with Legacy PS. The device with U-APSD enabled can save up to 20-30% compared to the other device. We measured how the video quality of experience grades affect the power consumption of the device. We manually adjusted the trigger interval to achieve the same subjective Mean Opinion Score value with different video bit rates. The relationship between QoE measures of the video and power consumption of the device can be seen in Figure 6. The results 4 Unfortunately the Max Service Period length could not be set in the driver configuration of the mobile station and the default setting was 2. This rendered the device to send a new trigger frame to the AP after 2 received data packets until the More Data bit of the received packet indicated that there are still buffered packets left at the AP. If the Max SP length is set so the device gets all buffered packets in reply to a single trigger packet, there can be some further optimization in the energy efficiency. Fig. 6: MOS - Mean Opinion Score vs. Power consumption for different bit rate videos. As a reference the corresponding trigger values for different bit rates and different MOS values can be seen in Table I. The varying trigger intervals imply that there is some space for the proposed framework to level out the differences in the wireless transmission channel and the varying bit rates of the streaming video by constantly optimizing the energy efficiency of the wireless network adapter. TABLE I: Trigger interval values that correspond to the MOS grades while streaming videos with different bit rates. Video bitrate 100 kbit/s 200 kbit/s 500 kbit/s 5 0-10 ms 0-5 ms 0-5 ms MOS 4 10-1000 ms 5-100 ms 5-100 ms 3 1000-3000 ms 100-1000 ms 100-1000 ms VI. C ONCLUSIONS In this paper we presented a framework that optimizes the energy efficiency of wireless mobile devices during video streaming. The proposed mechanism estimates the quality of experience of the video image and adaptively adjusts the sleep cycles of the power saving capable network adapters. The QoE estimation is done by specific algorithms and their output measure controls the triggering interval of the underlying UAPSD power saving protocol. We evaluated our framework by conducting measurements R Power Save certified WLAN on a testbed containing WMM devices. Our measurements support the claim that by utilizing the technology up to 30% of the total power consumption can be saved, and we show that this is achievable even during asynchronous wireless traffic scenarios. Our general conclusion is that significant amount of power saving can be easily achievable with the right software components by utilizing readily available power management technologies. 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