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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TL;DR: A simulator to evaluate the power consumption of Opportunistic Downclocking (ODoc) and shows that compared with 802.11, ODoc has a potential to reduce thePower consumption by 30%.
Abstract: Downclocking is considered as one of the most classical amendments on power saving of 802.11 protocols. Opportunistic Downclocking (ODoc) is a crucial component of the downclocking technique, which determines when a node returns to a downclocked rate after finishing receiving a packet at full-clock rate. In this paper, we develop a simulator to evaluate the power consumption of ODoc. Extensive simulations show that compared with 802.11, ODoc has a potential to reduce the power consumption by 30%.
Cites methods from "E-MiLi: energy-minimizing idle list..."
...The default parameter settings are set by [2] and shown in TABLE I, and the downclocked rate is set to 1⁄4 full-clock rate....
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Journal Article•
TL;DR: It is argued that LNC may not always benefit convergecast, and LNC-aided convergecast schemes may even be inferior to none-LNC ones when the wireless link delivery ratio is high enough.
Abstract: Convergecast is probably the most common communication style in wireless sensor networks (WSNs). And linear network coding (LNC) is a promising concept to improve throughput or reliability of convergecast. Most of the existing works have mainly focused on exploiting these benefits without considering its potential adverse effect. In this paper, we argue that LNC may not always benefit convergecast. This viewpoint is discussed within four basic scenarios: LNC-aided and none-LNC convergecast schemes with and without automatic repeat request (ARQ) mechanisms. The most concerned performance metrics, including packet collection rate, energy consumption, energy consumption balance and end-to-end delay, are investigated. Theoretical analyses and simulation results show that the way LNC operates, i.e., conscious overhearing and the prerequisite of successfully decoding, could naturally diminish its advantages in convergecast. And LNC-aided convergecast schemes may even be inferior to none-LNC ones when the wireless link delivery ratio is high enough. The conclusion drawn in this paper casts a new light on how to effectively apply LNC to practical WSNs.
Cites methods from "E-MiLi: energy-minimizing idle list..."
...For example, the method of how to recognize from imposes a significant effect on the overall performance....
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TL;DR: In this paper , a novel battery-free backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors is presented, which makes decoding both data possible with only a single personal radio.
Abstract: We present multiscatter, a novel battery-free backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Moreover, we introduce a low-power listening scheme to improve energy efficiency. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications. We prototype multiscatter using an FPGA and various commodity radios. Extensive experiments show that for mixed 802.11b&n, Bluetooth and ZigBee signals, the average identification accuracy of four protocols is more than 93%. The maximal aggregate throughput of both productive and tag data is 278.4 kbps with a single Bluetooth radio. When the transmitter-to-tag distance is increased from 0.2 to 1.8 m, the maximal communication for BLE drops from 71 m to 29 m. And it can leverage excitation diversity to provide uninterrupted communication and greater throughput gains, whereas the single-protocol tag being idle when carrier signals are unavailable. With indoor office light as harvesting sources, the low-power listening scheme can support backscatter rate at 12 pkts/s.
01 Jan 2015
TL;DR: This dissertation describes the effort on customizable Wi-Fi technology and proposes LLRA, a new latency-aware RA scheme that reduces the tail latency and EERA, an energy-efficient RA solution that balances throughput for energy savings while meeting the data rate quest by applications.
Abstract: As the Wi-Fi technology becomes pervasive in reality, its usage pattern is also turning highly diversified in operation settings and application scenarios. This consequently leads to new design requirements for Wi-Fi networking solutions in terms of various combinations in energy efficiency and latency, in addition to the throughput. However, the state-of-the-art solutions typically chase for high speed in the different generations of Wi-Fi technologies (from 802.11a/g to 802.11n/ac) at the cost of other metrics. For example, Multiple-Input Multiple-Output (MIMO) is widely used to boost speed, yet it consumes much more power. Higher throughput may yield long-tail loss behaviors and compromise the perceived latency for data transfer. Fundamentally, we believe that both the user demand pull and the technology push call for customizable Wi-Fi solutions.In this dissertation, we describe our effort on customizable Wi-Fi technology. We propose solutions that seek to meet the diverse requirements (i.e., energy, throughput, and latency). Specifically, we have come up with technical results on three topics. The first one explores to use rate adaptation (RA), the mechanism critical to performance yet unspecified by the 802.11 standards, for energy efficiency. It is shown that current MIMO RA algorithms in 802.11n/ac are not energy efficient despite ensuring high throughput. Marginal throughput gain is achieved at much higher energy cost. We then propose EERA, an energy-efficient RA solution. It balances throughput for energy savings while meeting the data rate quest by applications. In the second topic, we target home Wi-Fi scenario and interactive gaming applications. We examine the millisecond-level latency requirements of such applications. We show that current solutions work well for throughput but not for latency, due to the long tail of the packet delay distribution. We thus propose LLRA, a new latency-aware RA scheme that reduces the tail latency. It takes concerted design in rate control, frame aggregation scheduling and software/hardware retransmission dispatching. The implementation and evaluation confirm the viability of both EERA and LLRA. In the third topic, we propose HetRA, which can meet heterogeneous goals at each client. It explores a new theoretical approach, called piecewise linear wireless service curve. Using this new solution framework, we can meet minimum throughput on a per-flow basis, while simultaneously improving energy efficiency at the device level. We show in both analysis and experiments that, the resulting design outperforms all existing RA algorithms that only pursue a single goal. In all three concrete designs, we confirm that, the upcoming Wi-Fi technology has to be customized to the given usage scenario and designated goals, and this involves complex tradeoffs along multiple performance metrics of throughput, latency and energy saving and along various granularities of data flows, flow aggregates, and devices within a single user client and among multiple users.
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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