E-MiLi: energy-minimizing idle listening in wireless networks
19 Sep 2011-pp 205-216
TL;DR: E-MiLi employs an opportunistic downclocking mechanism to optimize the efficiency of switching clock rate, based on a simple interface to existing MAC-layer scheduling protocols, and can detect packets with close to 100 percent accuracy on the USRP software radio platform.
Abstract: WiFi interface is known to be a primary energy consumer in mobile devices, and idle listening (IL) is the dominant source of energy consumption in WiFi. Most existing protocols, such as the 802.11 power-saving mode (PSM), attempt to reduce the time spent in IL by sleep scheduling. However, through an extensive analysis of real-world traffic, we found more than 60% of energy is consumed in IL, even with PSM enabled. To remedy this problem, we propose E-MiLi (Energy-Minimizing idle Listening) that reduces the power consumption in IL, given that the time spent in IL has already been optimized by sleep scheduling. Observing that radio power consumption decreases proportionally to its clock-rate, E-MiLi adaptively downclocks the radio during IL, and reverts to full clock-rate when an incoming packet is detected or a packet has to be transmitted. E-MiLi incorporates sampling rate invariant detection, ensuring accurate packet detection and address filtering even when the receiver's sampling clock-rate is much lower than the signal bandwidth. Further, it employs an opportunistic downclocking mechanism to optimize the efficiency of switching clock-rate, based on a simple interface to existing MAC-layer scheduling protocols. We have implemented E-MiLi on the USRP software radio platform. Our experimental evaluation shows that E-MiLi can detect packets with close to 100% accuracy even with downclocking by a factor of 16. When integrated with 802.11, E-MiLi can reduce energy consumption by around 44% for 92% of users in real-world wireless networks.
Citations
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Proceedings Article•
13 May 2013TL;DR: In this article, the authors proposed a Lifetime Adjustable design for WiFi networks, where the devices are powered by battery, electric power, and/or renewable energy, and a device turns off its radio to save energy when the channel is sensed to be busy, and sleeps for a random time period before sensing the channel again.
Abstract: WiFi usage significantly reduces the battery lifetime of handheld devices such as smartphones and tablets, due to its high energy consumption. In this paper, we propose “Life-Add”: a Lifetime Adjustable design for WiFi networks, where the devices are powered by battery, electric power, and/or renewable energy. In Life-Add, a device turns off its radio to save energy when the channel is sensed to be busy, and sleeps for a random time period before sensing the channel again. Life-Add carefully controls the devices' average sleep periods to improve their throughput while satisfying their operation time requirement. It is proven that Life-Add achieves near-optimal proportional-fair utility performance for single access point (AP) scenarios. Moreover, Life-Add alleviates the near-far effect and hidden terminal problem in general multiple AP scenarios. Our ns-3 simulations show that Life-Add simultaneously improves the lifetime, throughput, and fairness performance of WiFi networks, and coexists harmoniously with IEEE 802.11.
7 citations
TL;DR: This study shows that DFS can greatly improve the energy efficiency of WiFi networks even under low SNR conditions and can be well integrated with other commonly used power-saving mechanisms to improve energy efficiency further.
Abstract: Dynamic frequency scaling (DFS) is a state-of-the-art power-saving technique. Various DFS-based WiFi schemes have been proposed for power saving. These schemes demonstrated the power-saving feasibility of DFS via hardware implementation or simulation. This paper is the first that proposes a general theoretical framework to evaluate the performance of these schemes, where we use Queuing theory to analyze the system throughput and use Semi-Markov theory to quantify the power consumption. In addition, we adopt the energy efficiency (i.e., the throughput per energy cost) to compare the gains of these schemes. This efficiency measure can be used to make a trade-off between system throughput and power consumption and therefore help us choose appropriate parameter settings. Extensive simulations verify that our theoretical model is very accurate and our theoretical results well match with universal software radio peripheral (USRP) experiment results. Our study shows that DFS can greatly improve the energy efficiency of WiFi networks even under low SNR conditions; for example, when SNR = 9.7 dB (i.e., the basic requirement for decoding packets in WiFi), the improvement is around 25 percent for 802.11b at rate 11 Mb/s and 16 percent for 802.11 ac at rate 1300 Mb/s. Our study also shows that DFS can be well integrated with other commonly used power-saving mechanisms to improve energy efficiency further.
7 citations
Cites background or methods or result from "E-MiLi: energy-minimizing idle list..."
...schemes including E-MiLi [1], SloMo [4], and their variants....
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...Particularly, our theoretical results of E-MiLi well match with hardware experimental results in E-MiLi [1]....
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...DYNAMIC frequency scaling [1], [2], [3], [4], [5], [6] is a stateof-the-art power-saving technique....
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...And other parameters related to E-MiLi are set by [1] and shown in Table 3....
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...proposed E-MiLi that reduces the power consumption in WiFi’s idle listening by downclocking its radio, but will revert to the full clockrate in transmission and reception [1]....
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24 Mar 2015
TL;DR: Two energy-efficient cooperation schemes for CRSNs that use randomized channel sensing, implicit cooperation, and simplified aggregation to reduce the energy consumed in channel sensing are presented.
Abstract: Cognitive radio sensor networks (CRSNs) exploit the cognitive radio concept to allow wireless sensor networks to dynamically access the available channels. However, existing channel sensing techniques developed for cognitive radios are not applicable to the energy-constrained sensor nodes. In this paper, we present two energy-efficient cooperation schemes for CRSNs. The proposed schemes use randomized channel sensing, implicit cooperation, and simplified aggregation to reduce the energy consumed in channel sensing. The proposed implicit OR and implicit AND save up to 55% of the energy, reduce the decision taking time by 30.6%–95%, and achieve similar miss-detection performance compared to their explicit counterparts.
7 citations
TL;DR: A long-range directional wake-up radio (LDWuR) for wireless mobile networks that adopts both static and dynamic antennas, where the static ones are directional, while the dynamic ones are omnidirectional for beamforming.
Abstract: This paper describes a long-range directional wake-up radio (LDWuR) for wireless mobile networks. In contrast to most wake-up radios (WuR) to date, which are short range, ours is applicable to long-range deployments. Existing studies achieve long distance by using modulation and coding schemes or by directional antennas, though the latter require exploring the direction of the transmitter. To address this issue, our LDWuR adopts both static and dynamic antennas, where the static ones are directional, while the dynamic ones are omnidirectional for beamforming. We present our LDWuR prototype and design principle. Simulation results show that our LDWuR and event-driven MAC protocol suppress the idle-listening of Wi-Fi stations in a wireless network, thereby enhancing the Wi-Fi power savings. Keywords: directional antenna; wake-up radio; beamforming; wireless mobile networks
7 citations
TL;DR: This paper argues that current Wi-Fi PHY design does not take full advantage of the inherent asymmetry between AP and IoT, and proposes an asymmetric design where IoT devices transmit uplink packets using the lowest power while pushing all the decoding burdens to the AP side.
Abstract: The conventional high-speed Wi-Fi has recently become a contender for low-power Internet-of-Things (IoT) communications. OFDM continues its adoption in the new IoT Wi-Fi standard due to its spectrum efficiency that can support the demand of massive IoT connectivity. While the IoT Wi-Fi standard offers many new features to improve power and spectrum efficiency, the basic physical layer (PHY) structure of transceiver design still conforms to its conventional design rationale where access points (AP) and clients employ the same OFDM PHY. In this paper, we argue that current Wi-Fi PHY design does not take full advantage of the inherent asymmetry between AP and IoT. To fill the gap, we propose an asymmetric design where IoT devices transmit uplink packets using the lowest power while pushing all the decoding burdens to the AP side. Such a design utilizes the sufficient power and computational resources at AP to trade for the transmission (TX) power of IoT devices. The core technique enabling this asymmetric design is that the AP takes full power of its high clock rate to boost the decoding ability. We provide an implementation of our design and show that it can reduce up to 88% of the IoT’s TX power when the AP sets $8\times $ clock rate.
7 citations
Cites background from "E-MiLi: energy-minimizing idle list..."
...It has been reported that idle listening consumes 90% energy for most nodes [8]....
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...Downclocking receivers’ radios is proposed to reduce the power consumption while receiving packets [6], [7] or idle listening [8], [9]....
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...E-Mili [8] pioneers this kind of mechanisms to downclock receiver’s clock rate during idle listening, and switches to full clock rate for packet reception....
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References
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Journal Article•
TL;DR: S-MAC as discussed by the authors is a medium access control protocol designed for wireless sensor networks, which uses three novel techniques to reduce energy consumption and support self-configuration, including virtual clusters to auto-sync on sleep schedules.
Abstract: This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses three novel techniques to reduce energy consumption and support self-configuration. To reduce energy consumption in listening to an idle channel, nodes periodically sleep. Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules. Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes. Unlike PAMAS, it only uses in-channel signaling. Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network. We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley. The experiment results show that, on a source node, an 802.11-like MAC consumes 2–6 times more energy than S-MAC for traffic load with messages sent every 1–10s.
5,354 citations
07 Nov 2002
TL;DR: S-MAC uses three novel techniques to reduce energy consumption and support self-configuration, and applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network.
Abstract: This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks Wireless sensor networks use battery-operated computing and sensing devices A network of these devices will collaborate for a common application such as environmental monitoring We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 80211 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important S-MAC uses three novel techniques to reduce energy consumption and support self-configuration To reduce energy consumption in listening to an idle channel, nodes periodically sleep Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes Unlike PAMAS, it only uses in-channel signaling Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data move through the network We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley The experiment results show that, on a source node, an 80211-like MAC consumes 2-6 times more energy than S-MAC for traffic load with messages sent every 1-10 s
5,117 citations
"E-MiLi: energy-minimizing idle list..." refers methods in this paper
...In sensor networks, a popular MAC-layer energy saving mechanism is LPL, which is used by S-MAC [32], B-MAC [33] and many derivatives....
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03 Nov 2004
TL;DR: B-MAC's flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC, and the need for flexible protocols to effectively realize energy efficient sensor network applications is illustrated.
Abstract: We propose B-MAC, a carrier sense media access protocol for wireless sensor networks that provides a flexible interface to obtain ultra low power operation, effective collision avoidance, and high channel utilization. To achieve low power operation, B-MAC employs an adaptive preamble sampling scheme to reduce duty cycle and minimize idle listening. B-MAC supports on-the-fly reconfiguration and provides bidirectional interfaces for system services to optimize performance, whether it be for throughput, latency, or power conservation. We build an analytical model of a class of sensor network applications. We use the model to show the effect of changing B-MAC's parameters and predict the behavior of sensor network applications. By comparing B-MAC to conventional 802.11-inspired protocols, specifically SMAC, we develop an experimental characterization of B-MAC over a wide range of network conditions. We show that B-MAC's flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC. By deploying a real world monitoring application with multihop networking, we validate our protocol design and model. Our results illustrate the need for flexible protocols to effectively realize energy efficient sensor network applications.
3,631 citations
"E-MiLi: energy-minimizing idle list..." refers methods in this paper
...In sensor networks, a popular MAC-layer energy saving mechanism is LPL, which is used by S-MAC [32], B-MAC [33] and many derivatives....
[...]
23 Sep 2002
TL;DR: This paper introduces a technique to increase the battery lifetime of a PDA-based phone by reducing its idle power, the power a device consumes in a "standby" state and shows that it can provide a significant lifetime improvement over other technologies.
Abstract: The demand for an all-in-one phone with integrated personal information management and data access capabilities is beginning to accelerate. While personal digital assistants (PDAs) with built-in cellular, WiFi, and Voice-Over-IP technologies have the ability to serve these needs in a single package, the rate at which energy is consumed by PDA-based phones is very high. Thus, these devices can quickly drain their own batteries and become useless to their owner.In this paper, we introduce a technique to increase the battery lifetime of a PDA-based phone by reducing its idle power, the power a device consumes in a "standby" state. To reduce the idle power, we essentially shut down the device and its wireless network card when the device is not being used---the device is powered only when an incoming call is received. Using this technique, we can increase the battery lifetime by up to 115%.In this paper, we describe the design of our "wake-on-wireless" energy-saving strategy and the prototype device we implemented. To evaluate our technique, we compare it with alternative approaches. Our results show that our technique can provide a significant lifetime improvement over other technologies.
863 citations
"E-MiLi: energy-minimizing idle list..." refers background in this paper
...The wake-on-wireless scheme [26] augments a secondary low-power radio for packet detection, and triggers the primary receiver only when a new packet arrives....
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