In [GNC. +. 01] a formula for determining the average current drain in wireless sensor nodes was introduced. We enhance this equation by considering one more ...
Sensor Lifetime Using SendOnDelta Mario Neugebauer, Klaus Kabitzsch Dresden University of Technology E-mail: {mn7,kk10}@inf.tu-dresden.de
Abstract: Energy is a scarce resource in wireless field bus systems. Strategies for power saving while coping with the application task are needed. This paper introduces the sendOnDelta-principle known from wired field bus systems. In the context of wireless sensor networks the method is analyzed and conclusions for power saving reserves are drawn.
1 Introduction In wireless sensor networks the energy is the scarce resource. Current research has focused on all OSI layers below the application (i. e. hardware [HSW+ 00] and MAC [YHE02]) in order to save power. The focus of this paper is on application layer issues. Data are only sent if something happened in the environment. In wired fi eld bus system this is referred as the sendOnDelta-principle. In this paper the sendOnDelta-principle [NK04] is adapted from wired fi eld bus systems. This method allows reduction of transmission activity while meeting the requirements of depending automation tasks. It is analyzed in an analytical model for the current drain. We show that certain model parameters reveal potential for energy-saving. The next section introduces the analytical model for the current drain, depending on application layer parameters. In the third section an example to show the parameter dependencies is provided.
2 Lifetime Model In [GNC+ 01] a formula for determining the average current drain in wireless sensor nodes was introduced. We enhance this equation by considering one more state: the time T app (with current drain Iapp ) while the application senses the environment and decides to send new data or not. Iavg
=
Ttxon · Itxon + Trxon · Irxon + Tapp · Iapp + (1 − Ttxon − Trxon − Tapp ) · Istby
(1)
The time needed for switching between the different modes (transmit, receive, sleep, application) is neglected.
360
Now, information about the current drain and the fraction of time spend in application mode is needed additionally. Therefore, the arrival rate for the event application senses m the environment is introduced with λapp (measured in time with m as the number of occurrences during time). It is a confi gured rate and determines the reciprocal of the time elapsing between two successive sensing events. For approximation of λ tx (rate for transmission) the gradient r (measured in units time ) of the signal, monitored by the sensor, is necessary. Together with ∆1 we get r ∆
λtx =
(2)
which is the achieved transmission rate if continuous sampling in the application is performed. This enables the application to react immediately after transcending ∆. But since the application actually samples the environmental signal with the rate λapp the real transmission rate λtx results in λtx =
λapp n
(3)
with n as a positive integer. The sensor can perceive that ∆ was transcended only when the application is active. Hence, we calculate the corresponding factor by λapp . (4) n= λtx It means that the time between two successive transmissions (1/λtx ) is a multiple of the time between two consecutive application cycles (1/λapp ). Combining the latter with the Equations 2 and 3 we get λtx =
λapp ∆·λapp r
(5)
whereby r can be replaced with rmean for determining λtx,mean and rmax instead would lead to λtx,max . The ∆ in Equation 5 is to confi gure according to the physical process characterized in its dynamic behavior by r. To assure that in the case of the steepest rise of the process signal, the application still checks the process often enough, the parameter λapp is to determine with λapp =
rmax ∆
(6)
as the minimum rate for sampling in the application. Here, for simplifi cation, time spend in receive mode trx equals the time spend for transmission ttx and λtx ≈ λrx . This is approximately true because in average on each transmitted 1 ∆ determines which range has to be transcended such that a new message has to be sent. It implies a sensor resolution. For further details consult [NK04].
361
packet follows a received packet and the packets have the same length. We neglect that packet dropping due to bad channel conditions can occur. With t app for the time spend in the application for detecting if the ∆ was transcended, Equation 1 can be rewritten as Iavg
=
Iavg
=
(Irx + Itx ) λtx ttx + λapp tapp Iapp + (1 − 2Ttxon − Tapp ) Istby rmax ttx (Irx + Itx ) rmax + tapp Iapp rmax ∆ rmean ∆ ⎞ ⎛ 2r rmax t max tx ⎠ Istby − tapp Istby + ⎝1 − rmax ∆ ∆
(7)
rmean
This equation only depends on the process parameter r, the corresponding ∆ and processor specifi c processing times and current drains in each mode. Having a specifi c processor, a certain implementation, a transceiver and mean parameters of the process of interest allows an approximation of the average current drain Iavg . Further, it enables estimation of the life time tlive by applying Equation (1) from Gutierrez et al. [GNC+ 01] tlive =
C Iavg
(8)
with C for the capacity of the battery (measured in [mAh]).
3 Hardware and Process Example As an example for the given approach, the lifetime for a sensor which monitors the temperature will be computed. For the hardware we suppose a combination of the RFB433 [Bl03] (Irx = 8 mA, Itx = 45 mA) and an Atmel microcontroller [At03] (Iapp = 3 mA, Istby = 3 µA).The current drain in stand-by mode results from both, the stand-by current drain of the RF-unit and the microcontroller. For the time ttx it is assumed that the 28 bytes in the frame are transmitted with 19.2 kbps. This leads to ttx = 11.7 ms. The time tapp spend in the application mode for checking ∆ is to estimate with low accuracy only. Detailed information about the application which is running is essential. We estimate tapp = 0.25s, which is a conservative value for the time needed to wake-up the microcontroller, check the environment and go to sleep. The parameter ∆ is set to 0.5 ◦ C and the Capacity C of the battery is 0.4 Ah. Assumptions about the process dynamics (temperature course during a year in an average building) are taken from a compound project [KSDK03] currently running: rmean = 0.000185 ◦C/s and rmax = 0.001167 ◦C/s.
3.1 Continuous vs. sendOnDelta Assuming these values for Equation 7 a sensor lifetime of about 9.2 years is determined. Keeping in mind that initialization, error handling and battery self discharge are neglected
362
14
(a) tlive (rmean, data rate)
14
19.2 kbps 9.6 kbps
12
tlive in years
tlive in years
10
8 6
6 4
2
2 −3
−2
(c) t
live
(r
0 −4 10
−1
10 10 rmean in [ °C/s ]
14
10
,I )
mean
−3
−2
live
14 45 mA 22.5 mA
(r
10
, ∆)
mean
0.5 °C 1 °C
12 10
tlive in years
10
−1
10 10 rmean in [ °C/s ] (d) t
tx
12 tlive in years
8
4
8 6 4
8 6 4
2 0 −4 10
250 ms 125 ms
12
10
0 −4 10
(b) tlive (rmean, tapp)
2 −3
−2
10 10 rmean in [ °C/s ]
0 −4 10
−1
10
−3
−2
10 10 rmean in [ °C/s ]
−1
10
Figure 1: Sensor lifetime depending on process dynamics rmean and (a) data rate (b) application duration tapp (c) current drain during transmission Itx (d) ∆ as the resolution
in the calculation, it still is a reasonable lifetime for a temperature sensor. The same process can be monitored with time triggered sampling and transmitting as well. We presume that the sampling interval is adjusted to 120s which is a reasonable value for a slow process like course of the room temperature. With Equation 7 we get 3.2 years which is less than half of the lifetime of the sensor working with the sendOnDelta approach. This result reveals that knowledge about the process to monitor allows a customized confi guration of the sensor in order to consume less power. This result reveals that knowledge about the process to monitor allows a customized confi guration of the sensor in order to consume less power. Here we do not take into account that increased traffi c load leads to a higher collision rate and therewith to higher power consumption.
3.2 Energy-Saving Potential Since the lifetime depends on the process monitored we vary the values rmean and rmax such that 0.0001 ◦C/s < rmean < 0.1 ◦ C/s, and rmean 0.000185 ◦C/s = rmax 0.001167 ◦C/s
(9)
363
is valid. The result is shown in Figure 1 (solid line in all graphs). As expected, with a more vital process (increasing rmean ) the predicted lifetime of the sensor decreases signifi cantly. For faster processes the tlive goes far below several years. The circle marks the lifetime for the process mentioned above (temperature course during a year). In order to examine the impact of the main parameters in Equation 7 the data rate, current drain, application duration and ∆ was varied. The result is shown in Figure 1. Figure 1 (a) and (c) reveal that the data rate and the current drain during transmission do not impact the lifetime signifi cantly. However, a shorter application duration and a greater ∆ respectively can prolong the sensor lifetime.
4 Conclusion We developed an analytical model for the energy consumption in a sensor based on the sendOnDelta-principle. The example has shown that during the sensor design, attention must be paid on the implementation and confi guration of the sensor application. Even small changes can have a large impact on the sensor lifetime. Using the sendOnDeltaprinciple signifi cantly prolongs the sensor lifetime compared to time-triggered sampling. However, certain layers were neglected (i. e. medium access and network layer) and will be the subject of further research.
References [At03]
Atmel Corporation: Datasheet AT90S2323/LS2323/S2343/LS2343 Summary. 2003. www.atmel.com.
[Bl03]
BlueChip Communication AS: www.bluechip.no.
Datasheet RFB433.
Lysaker, Norway.
2003.
[GNC+ 01] Gutierrez, J. A., Naeve, M., Callaway, E., Bourgeois, M., Mitter, V., und Heile, B.: IEEE 802.15.4: A Developing Standard for Low-Power Low-Cost Wireless Personal Area Networks. IEEE Network. 15(5):12–19. September/October 2001. [HSW+ 00] Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., und Pister, K.: System Architecture Directions for Networked Sensors. In: ASPLOS 2000. April 2000. [KSDK03] Kabitzsch, K., Schwarz, W., Donath, U., und Knabe, G.: Zwischenbericht zum verbundprojekt netplan. Technical report. Dresden University of Technology. April 2003. [NK04]
Neugebauer, M. und Kabitzsch, K.: A New Protocol for a Low Power Sensor Network. In: Hassanein, H., Oliver, R. L., III, G. G. R., und Wilson, L. F. (Hrsg.), Proceedings of the 23rd IEEE International Performance, Computing and Communications Conference (IPCCC 2004). S. 393–399. Phoenix, Arizona. April 2004. IEEE.
[YHE02]
Ye, W., Heidemann, J., und Estrin, D.: An Energy-Efficient MAC Protocol for Wireless Sensor Networks. In: Proceedings of the IEEE Infocom. S. 1567–1576. New York, NY, USA. June 2002. USC/Information Sciences Institute. IEEE.
364
