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Proceedings ArticleDOI

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.

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Citations
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Journal ArticleDOI
TL;DR: TailTheft is proposed, a scheme that leverages the tail time for batching and prefetching to reduce energy consumption and can achieve significant savings on battery energy and dedicated radio resources compared to the default policy.
Abstract: In cellular networks, inactivity timers are used to control the release of radio resources. However, during the timeout period of inactivity timers, known as the tail time, a large proportion of energy in user devices and a considerable amount of radio resources are wasted. In this paper, we propose TailTheft, a scheme that leverages the tail time for batching and prefetching to reduce energy consumption. For network requests from a number of applications that can be deferred or prefetched, TailTheft provides a customized application programming interface to distinguish requests and then schedules delay-tolerant and prefetchable requests in the tail time to save energy. TailTheft employs a virtual tail time mechanism to determine the amount of tail time that can be used and a dual queue scheduling algorithm to schedule transmissions. We implement TailTheft in the Network Simulator with a model for calculating energy consumption that is based on parameters measured from mobile phones. We evaluate TailTheft using real application traces, and the experimental results show that TailTheft can achieve significant savings on battery energy (up to 65%) and dedicated radio resources (up to 56%), compared to the default policy.

19 citations

Proceedings ArticleDOI
26 Mar 2012
TL;DR: This work indicates the feasibility and possibility of deploying this mechanism into real network devices for energy saving, and implements a prototype of this scheme in the data path of a general IPv4 router based on a real hardware platform - NetFPGA.
Abstract: In this paper, we have designed a Multi-Frequency Scaling scheme for energy conservation of network devices, especially routers and switches. The frequency of components in a network device is scaled dynamically according to the real time workload. A Markov model is developed for performance analysis of this mechanism. We implement a prototype of this scheme in the data path of a general IPv4 router based on a real hardware platform - NetFPGA. Experimental results show excellent energy savings at the cost of a tolerable latency, under various ranges of traffic loads. Our work indicates the feasibility and possibility of deploying this mechanism into real network devices for energy saving.

19 citations


Cites methods from "E-MiLi: energy-minimizing idle list..."

  • ...This section describes the general power consumption model of network device, and proposes the Multi-Frequency Scaling scheme as well as methodology used for validation....

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Journal ArticleDOI
TL;DR: Green wireless local area networks, where idle access points are put into sleep and activated upon the request of mobile nodes, are realized by exploiting WLAN signals to convey wake-up messages, which helps to greatly improve the reliability of wake-ups compared with state-of-the-art methods.
Abstract: In this paper, green wireless local area networks (WLANs), where idle access points (APs) are put into sleep and activated upon the request of mobile nodes, are realized by exploiting WLAN signals to convey wake-up messages. Specifically, wake-up messages, sent by nodes, are modulated onto frame lengths (physical transmission time) of successive WLAN signals and detected by non-WLAN low-cost receivers equipped at APs. This method, however, is susceptible to serious 1) false negative events due to low signal quality or collisions with background WLAN frames and 2) false positive events where background WLAN frames happen to have the same frame lengths as those of wake-up messages. In the proposed scheme, WLAN frames forming a wake-up message are transmitted in a burst and interpreted as an equivalent message. On this basis, false probability is reduced from two aspects: 1) Modulation constellations of frame lengths are optimized to maximize the Hamming distance between equivalent messages, and 2) preamble frame and envelope smoothing are used to mitigate false events. In addition to theoretical analysis and simulation, a prototype test bed is built and experimented on. Extensive evaluations confirm that the proposed scheme helps to greatly improve the reliability of wake-up control compared with state-of-the-art methods.

19 citations

Proceedings ArticleDOI
25 Jun 2012
TL;DR: This paper proposes a light-weight battery charge monitoring scheme during the draining and charging of a battery on a per application or per application class basis and proposes a device power manager that allocates device resources to the different applications in accordance with device-level power management policies set by the user.
Abstract: This paper presents a system called PowerVisor that is aimed at the virtualization of the battery resource of mobile devices across application classes While other resources in a mobile device are virtualized, no similar sharing mechanism exists for the battery resource In PowerVisor, each application class is assigned a virtual battery based on user level policies We propose a light-weight battery charge monitoring scheme during the draining and charging of a battery on a per application or per application class basis Leveraging this monitoring scheme, a device power manager is designed that allocates device resources (eg, CPU, memory) to the different applications in accordance with device-level power management policies set by the user

18 citations


Cites background from "E-MiLi: energy-minimizing idle list..."

  • ..., [11, 7]) has been proposed to reduce power consumption in wireless network interface cards....

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Journal ArticleDOI
TL;DR: The implications of facilitating higher energy efficiency in cognitive radio networks from the perspective of fundamental trade-offs are discussed, identified as QoS, fairness, PU interference, network architecture, and security which are also essential network design dimensions.
Abstract: This article discusses the implications of facilitating higher energy efficiency in cognitive radio networks from the perspective of fundamental trade-offs (i.e, what needs to be sacrificed to be energy-efficient). These trade-offs are identified as QoS, fairness, PU interference, network architecture, and security, which are also essential network design dimensions. We analyze these dimensions and their interactions focusing on energy efficiency. Furthermore, future research directions related to the integration of CRN with other networking paradigms and energy efficiency are introduced and discussed.

18 citations

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

Proceedings ArticleDOI
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....

    [...]

Proceedings ArticleDOI
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....

    [...]

Proceedings ArticleDOI
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....

    [...]