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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01 Mar 2017
TL;DR: A new traffic-aware version of FM-WiFIX+.
Abstract: The growth of the IP cameras market, due to their low price and high availability, is making Wireless Video Sensor Networks (WVSNs) attractive. In a mesh, multi-hop video surveillance scenario Wi-Fi is the enabling technology for WVSNs, due to its flexibility and low cost. However, WVSNs still suffer from bad performance, throughput unfairness, and energy inefficiency. Previously, we proposed FM-WiFIX+, a holistic solution to address the problem. FM-WiFIX+ uses FM radio to signal when a video sensor should turn its IEEE 802.11 interface OFF, thus saving energy. Herein, we present a new traffic-aware version of FM-WiFIX+. The results obtained through numerical, simulation, and experimental evaluation demonstrate that the new version can achieve savings in energy consumption up to 84 %, while maintaining the levels of performance and throughput fairness.
1 citations
Cites background from "E-MiLi: energy-minimizing idle list..."
...Moreover, only the idle power of the Wi-Fi interface is considered since Wi-Fi idle listening and receive are the dominant modes of energy consumption [6]....
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...New MAC solutions have been proposed to reduce the power consumption in wireless networks [6] and WVSNs [13]....
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...11 station in a busy network and 60% in a relatively idle network [6]....
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TL;DR: A real-time data compressing algorithm is proposed, where the compressibility of data can dynamically be adjusted, on the basis of application demand, and the clock frequency can be adjusted intelligently and the energy conservation can be accomplished.
Abstract: Wireless sensing is an effective method for the acquisition of the mechanical failure signal. Many researchers have been studying in this field for decades. Due to the difficulty of the sensor installing and replacement caused by the special environment condition of mechanical equipment, the energy-efficiency of the wireless transceiver is necessary to guarantee the long lifetime. In this paper, we present a novel energy-efficiency wireless sensing method for mechanical failure signal. Actually, we are only concerned with the feature of signals in the failure visible phase, in the application such as the mechanical failure diagnosis or alert. Therefore, according to the signal feature, a real-time data compressing algorithm is proposed, where the compressibility of data can dynamically be adjusted, on the basis of application demand. Then the clock frequency can be adjusted intelligently and the energy conservation can be accomplished, through the handshake between the sampling node of the front end and the received node, based on the compressing situation. In the conversion of clock frequency, an improved dif-frequency preamble sense way is adopted to achieve the seamless change between different frequencies. Finally, the method is analyzed and the feasibility is evaluated.
1 citations
30 Jul 2019
TL;DR: A wireless sensor network (WSN) consists of sensor nodes and base stations which are connected via wireless medium and reliable data transportation i.e. ensuring data delivery with minimum loss becomes the key issue in WSNs.
Abstract: A wireless sensor network (WSN) consists of sensor nodes and base stations which are connected via wireless medium. A key functionality of WSNs consists in collecting information from sensor nodes & transporting the information of interest to the base stations required by the applications. Wireless connectivity, size and low cost of sensors in WSNs are its advantages which enable it to be deployed in hostile or inaccessible environments at a very low cost. However, WSNs suffer from high data loss due to error prone wireless transmission medium, transmission problems in hostile environments and node failures due to limited energy of sensor nodes. Hence reliable data transportation i.e. ensuring data delivery with minimum loss becomes the key issue in WSNs.
1 citations
27 Jun 2022
TL;DR: It is shown that this hardware modification in many cases can be avoided by TransFi, a new software technique that enables custom wireless PHY functionality on commodity WiFi transmitters via fine-grained emulation.
Abstract: New wireless physical-layer designs are the key to improving wireless network performance. Adopting these new designs, however, requires modifications on wireless hardware and is difficult on commodity devices. In this paper, we show that this hardware modification in many cases can be avoided by TransFi, a new software technique that enables custom wireless PHY functionality on commodity WiFi transmitters via fine-grained emulation. Our basic insight is that many custom wireless signals can be emulated by manipulating the MAC payloads of WiFi MIMO streams and mixing the transmitted signals from these streams on the air. To perform such emulation, TransFi considers the target signal as a mixture of QAM constellation points on the complex plane, and reversely computes the MAC payload of each MIMO stream from one selected QAM constellation point. We implemented TransFi on commodity WiFi devices to emulate three custom wireless PHYs with diverse characteristics. Experiment results show that TransFi's accuracy of emulation is >90% when transmitting emulated data payloads at 11.4 Mbps (46x faster than existing methods), and the decoding error at this data rate is <1% (10x lower than existing methods).
01 Dec 2019
TL;DR: This paper compares the various protocols already proposed for mitigating latency and energy consumption in WLAN networks and provides synthesis of wake-up radio (WUR) based carrier sensing approaches with analysis and discussions of merits and limitations of each technique.
Abstract: Power consumption is a key consideration in every WLAN MAC protocol design for wireless devices and extending battery life requires more efficient power management scheme considering that Carrier sensing by WLAN modules consumes enormous amount of power. Researchers over the years have proposed and implemented various schemes using a low-power Wake-up Radio for carrier sense which has proven to be effective. In this paper, a comprehensive literature review of the research progress in WuR-based energy saving is presented. This paper compares the various protocols already proposed for mitigating latency and energy consumption in WLAN networks and provides synthesis of wake-up radio (WUR) based carrier sensing approaches with analysis and discussions of merits and limitations of each technique. The operation principles of duty-cycle and wake-up radio bases MAC protocols were looked into in relation to how they affect energy efficiency and latency reduction.
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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