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 Jan 2013
TL;DR: This thesis investigates the problem of maximizing the throughput or utility performance for a wireless sensor network with renewable energy, and develops a low-complexity online scheme that is asymptotically optimal as network operation period of time tends to infinite.
Abstract: Renewable energy sources, such as solar and wind power, have been widely used in various forms of networks, which include both communication networks and the smart power grid. Since the renewable energy is usually highly fluctuating, the temporal and spatial dynamics of such sources are often difficult to model and predict. This makes it extremely challenging to incorporate and operate such energy sources while maintaining adequate utilization of them. In this thesis, we study the control and optimization strategies of renewable energy in several network scenarios, including wireless sensor networks, WiFi networks, and the smart grid. We first investigate the problem of maximizing the throughput or utility performance for a wireless sensor network with renewable energy. The two solutions that we developed here are based on a finite time horizon and an infinite time horizon respectively. In the finite-horizon problem, we propose a simple heuristic distributed scheme in a rechargeable sensor network with optimal performance under some specific conditions and with provable performance guarantee. Regarding the infinite-horizon problem, after characterizing the optimal network utility with an upper bound, we develop a low-complexity online scheme that is asymptotically optimal as network operation period of time tends to infinite. It shows that by focusing on long-term system performance, we can greatly simplify computational complexity while maintaining high performance. We then study the problem of efficient channel access in WiFi networks, where
Journal Article•
TL;DR: Six WLAN network services on prime of Odin moreover are demonstrated as load-balancing, quality management, and sender Detection, automatic channel-selection, energyManagement, and guest policy group action, to demonstrate the effectiveness of the approach.
Abstract: Residential broadband gateways comprise equipment, router, and Wi-Fi access point, though one by one overwhelming only 5-10 Watts of power and important contributors to overall network energy consumption because of huge preparation numbers. Wi-Fi traces collected throughout a building with thirty access points and twenty 5,000 shopper connections, and worth via simulation the tradeoffs between energy savings, session disruptions, and fairness. Our system on artifact Wi-Fi access points, take a glance at it throughout a two-storey building emulating vi residences, and demonstrate radio energy reduction of over sixty influence little or no impact on user experience. Considering the spotlight the effectiveness of the approach we have got a bent to demonstrate six WLAN network services on prime of Odin moreover as load-balancing, quality management, and sender Detection, automatic channel-selection, energy management, and guest policy group action. Index Terms —Energy consumption, aggregation, centralized control, Green networking, WLAN, sleep modes.
01 Feb 2020
TL;DR: This paper proposes IL down-clocking schemes using deep learning model with recurrent neural network (RNN) to reduce the energy consumption in IL time, and exploits the orthogonal frequency-division multiplexing (OFDM) subcarrier addressing for the preamble design.
Abstract: Wi-Fi interface is known to consume a lot of energy in mobile devices, and Idle Listening (IL) dominates clients' energy consumption in Wi-Fi. In this paper, we propose IL down-clocking schemes using deep learning model to reduce the energy consumption in IL time. We exploit the orthogonal frequency-division multiplexing (OFDM) subcarrier addressing for the preamble design. To minimize preamble length for energy efficiency, we use a deep learning model with the recurrent neural network (RNN). Our experimental evaluation using OPNET network simulator and USRP/GNU Radio implementation shows that our scheme outperforms the state-of-the-art down-clocking scheme in both energy consumption and network throughput.
Cites background from "E-MiLi: energy-minimizing idle list..."
...To restoring process, E-MiLi adopts long length preamble design which decreases network throughput [7]....
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...In the recent paper [7], the E-MiLi proposes scheme that operates in a down-clocking state only in the IL state, thereby significantly reducing energy consumption....
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...To tackle these limitations, recent work takes a different approach – the down-clocking scheme – in which the clock rate of the device is kept to be decreased in the IL state [7]....
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27 Jun 2022
TL;DR: TransFi as discussed by the authors is a software technique that enables custom wireless PHY functionality on commodity WiFi transmitters via fine-grained emulation by manipulating the MAC payloads of WiFi MIMO streams and mixing the transmitted signals from these streams on the air.
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).
TL;DR: A novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power to offer maximum energy conservation is presented.
Abstract: With increasing adoption of multicarrier-based communications e.g. 3G and 4G, the users are significantly benefited with impressive data rate but at the cost of battery life of their mobile devices. We reviewed the existing techniques to find an open research gap in this regard. This paper presents a novel framework where an optimization is carried out with the objective function to maintain higher level of equilibrium between maximized data delivery and minimized transmit power. An analytical model considering multiple radio antennae in the mobile device is presented with constraint formulations of data quality and threshold power factor. The model outcome is evaluated with respect to amount of power being conserved as performance factor. The study was found to offer maximum energy conservation and the framework also suits well with existing communication system of mobile networks.
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....
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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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