A Novel Power Saving Strategy for Greening IEEE 802.11 Based Wireless Networks

Tamma, Bheemarjuna Reddy; Manoj, B. S.

doi:10.1109/glocom.2010.5684071

Cited by 15 publications

(23 citation statements)

References 3 publications

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“…The transitions between the awake state (either the transmission, reception, or idle state) and the sleep state can take some hundreds or few thousands of microseconds, as shown by measurements in [15][16][17][18][19]. However, few tens of microseconds for these transitions are assumed in [9,11] with no experimental validation. Likewise, no information about the transition time is given in [12].…”

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

“…On the contrary, the low-power sleep state employed in the mechanisms in [9][10][11][12] is commonly available in most commercial 802.11 interfaces. The transitions between the awake state (either the transmission, reception, or idle state) and the sleep state can take some hundreds or few thousands of microseconds, as shown by measurements in [15][16][17][18][19].…”

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

“…Various papers [7][8][9][10][11][12] proposed mechanisms based on the microsleep operation of TXOP PSM to tackle the problem of energy consumption due to overhearing in WLANs. The mechanisms introduced in [7,8] allow an STA to switch to a low-power idle state during the transmission of a data frame sent to another STA.…”

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

“…In addition, the mechanism in [8] allows an STA to enter the low-power idle state during the execution of the 802.11 backoff procedure employed to get access to the channel. The mechanisms proposed in [9,11] specify that an STA can go into the sleep state for the payload duration of a data frame sent to another STA. Using the mechanism defined in [10], an STA can sleep during an exchange of data frames between other STAs.…”

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

“…In addition, an extension of the PSMP microsleep was defined in the 802.11ac Transmission Opportunity Power Save Mode (TXOP PSM) [6]. An overview of these and other power save mechanisms including microsleep [7][8][9][10][11][12] is presented in Section 2.…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of a Burst Transmission Mechanism Using Microsleep Operation for Green IEEE 802.11 WLANs

et al. 2017

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This paper evaluates the performance of a burst transmission mechanism using microsleep operation to support high energy efficiency in IEEE 802.11 Wireless Local Area Networks (WLANs). This mechanism is an implementation of the IEEE 802.11ac Transmission Opportunity Power Save Mode (TXOP PSM). A device using the TXOP PSM-based mechanism can switch to a low-power sleep state for the time that another device transmits a burst of data frames to a third one. This operation is called microsleep and its feasibility strongly depends on the time and energy consumption that a device incurs in the transitions from and to the sleep state. This paper accounts for the impact of these transitions in the derivation of an analytical model to calculate the energy efficiency of the TXOP PSM-based mechanism under network saturation. Results obtained show that the impact of the transition requirements on the feasibility of microsleep operation can be significant depending on the selected system parameters, although it can be reduced by using burst transmissions. When microsleep operation is feasible, the TXOP PSM-based mechanism can improve the energy efficiency of other legacy mechanisms by up to 424% under high traffic loads.

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Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

Section: 11-based Microsleep Mechanismsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of a Burst Transmission Mechanism Using Microsleep Operation for Green IEEE 802.11 WLANs

et al. 2017

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Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

et al. 2015

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García Pineda, M.; Ramos Pascual, F.; Lloret, J. (2015). Improving energyefficiency with a green cognitive algorithm to overcome weather's impact in 2. Abstract: The necessity of energy-efficient systems in order to protect our environment, cope with global warming, and facilitate sustainable development is paramount for the researching world because the survival of the planet is at stake. Thus, optimizing the energy efficiency of wireless communications not only reduces environmental impact, but also cuts overall network costs and helps make communication more practical and affordable in a pervasive setting. This paper is focused on a solution to enhance the energy efficiency in outdoor wireless local area networks using the standard IEEE 802.11b/g. So, from a previous study about the weather's impact on the number of control frame errors and retransmissions, we propose a green cognitive algorithm that adapts wireless transmissions to the channel conditions caused by the weather. The goal is to reduce retransmissions and control errors in order to save energy and to enhance network performance. Our proposal is based on a mathematical analysis in which we see how the frame error rate is related to the power consumption according to the modulation scheme and data rate used by transmitters. Finally, several simulations show that the green cognitive algorithm presented in this paper involves significant energy savings for outdoors WLANs.

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