Published on June 24, 2008
Gateway Design for Data Gathering Sensor Networks Presented by Raluca Musaloiu-E. Johns Hopkins University That’s Razvan Andreas Me Musaloiu-E. Terzis
Easier to deploy a WSN than years ago. TinyOS MANTIS OS MICAz Contiki SOS RETOS Tmote Sky
Life Under Your Feet WSNs for studying the effects of abiotic factors on soil animals. http://lifeunderyourfeet.org
Koala System for reliably extracting bulk data from duty-cycled nodes.
Current solutions for WSN gateways are not energy efﬁcient and bulky.
Back-End Server Internet Commands Data Requests WSN WSN
CPU 400 MHz Intel PXA255 Memory 64 MB SDRAM Stargate 32 MB Flash CF and PCMCIA connectors 51-pin expansion connector Low power consumption < 500 mA http://www.xbow.com
CPU Low-power PIC, 32768 Hz PowerNut Supply voltage 7-30 V Power 180 uA (worst case) consumption (downstream device shutoff) 58-100 uA (typical) http://www.jkmicro.com
Normal operation cycle Establish the Download Download data from the motes Sleep Boot uplink connection commands Upload previous data Fig. 2. The gateway’s normal operation cycle. s state and the PowerNut itself consumes very little energy, This command speciﬁes the number of seconds that s solution is more efﬁcient than putting the gateway to gateway should go to sleep at the end of the curr ep-sleep mode. On the other hand, the gateway must go activity period. The gateway uses this value to set ough its boot process every time power is restored. This time period for deep-sleep or to conﬁgure the amo ot sequence, including loading the operating system, can of time the PowerNut power controller will disconn ke tens of seconds. Section IV explores the trade-off between the power from the gateway itself. wering off the gateway and using its deep-sleep mode. 3) REPORT <count> This command speciﬁes the number of operation cyc
Commands TIME <curent time> REPORT <count> SLEEP <seconds> SEND_LOG UPDATE <ﬁle_location> wsn|gw
WSN interface Koala Deluge Typhoon download data network programming
Long haul connectivity
Deep-sleep versus Power-off mode 1 2 Energy efﬁciency of long haul radios Lifetime estimation 3
1 Deep-sleep versus Power-off mode Decision is based on inactivity time.
Network up Network down Deep-sleep 500 mA 306 mA 247 mA 375 mA 144 mA 250 mA 123 mA 125 mA 102 mA 63 mA 83 mA 6 mA 23 mA 42 mA 0 mA No cards Wi-Fi 3G No cards No daughter-board With daughter-board
Average current drawn during the booting sequence 300 mA 225 mA 150 mA 280 mA 268 mA 203 mA 176 mA 75 mA 0 mA No cards Wi-Fi 3G DB, no cards
Power-off mode is preferred if time > 3.9 min for 3G (5.2 min for Wi-Fi, 16.5 min with no cards). 100 3G - deep-sleep Wi-Fi - deep-sleep no cards - deep-sleep 80 3G - power-off Wi-Fi - power-off no cards - power-off Average Current (mA) A 60 40 B C 20 0 0 500 1000 1500 2000 Inactivity Time (s)
2 Energy efﬁciency of long haul radios Measure the time to transfer a ﬁle.
1.2 mAh to transfer 1 MB ﬁle in deep-sleep with Wi-Fi (16 mAh with 3G). 18 Wi-Fi - deep-sleep 3G - deep-sleep 16 Wi-Fi - power-off 3G - power-off 14 Energy Consumption (mAh) 12 3G 10 8 6 Wi-Fi 4 2 0 100KB 250KB 500KB 750KB 1M
Energy consumption to transfer 1 MB ﬁle in power-off mode. 700 700 600 B C E 600 B Current (mA) Current (mA) 500 D 500 400 300 A 3G 400 300 A 200 200 100 100 0 0 0 20 40 60 80 100 120 140 160 180 0 20 Time (s) Fig. 7. Current drawn during the transfer of a 1 MB ﬁle using the 3G radio Fig. 8. Current dr in the power-off conﬁguration. radio in the power-o 700 600 B C D E Current (mA) 500 loading, PPP dial-up connection is set in section C, followed A 400 300 Wi-Fi 55 in section D by the actual transfer, and a short section E in 200 50 100 which the connection is terminated. Figure 8 presents the same 0 45 0 20 40 60 80 100 120 140 160 180 stages when the Wi-Fi card is Time (s) used. 40 ime [minutes] Fig. 8. Current drawn during the transfer of a 1 MB ﬁle using the Wi-Fi 35 radioLifetime Estimation C. in the power-off conﬁguration. 30 We can now estimate the lifetime of a battery-operated
3 Lifetime estimation Estimate the life of a battery-operated gateway.
N number of WSN nodes 25 alpha storage threshold 0.25 M mote storage capacity 1 MB B1 data generation rate 18 bytes/min B2 data generation rate 180 bytes/min
1. Deep-sleep 23 mA Wi-Fi Energy consumed in 42 mA 3G sleep-mode. Power-off 180 uA
ower-off conﬁguration. radio in the power-off conﬁguration. g, PPP dial-up connection is set in section C, followed 55 ion D by the actual transfer, and a short section E in 50 the connection is terminated. Figure 8 presents the same 45 when the Wi-Fi card is used. 40 Radio-on time [minutes] etime Estimation 35 30 can now estimate the lifetime of a battery-operated y for each of the four conﬁgurations (deep-sleep/power- 25 de with Wi-Fi/3G radio). 20 do so, we consider a WSN of N = 25 motes, each with 15 e capacity of M bytes. Each mote generates measure- 2. 10 at a rate of B bytes/min. We assume that there are no 5 y requirements in delivering the measurements to the Energy consumed nd server so the only constraint is to ofﬂoad the data 0 0 50 100 150 200 250 300 350 400 450 500 550 the motes overﬂow their local storage. Therefore, the Data-size [kilobytes] to retrieve y must retrieve the motes’ measurements after each of Fig. 9. Total time the gateway is active downloading data as a function of KoalatheUltra-Low Power Data RetrievalwithWireless Sensor Networks - per-mote download size for a network in 25 nodes. These download otes has collected α · M , (α ≤ 1) bytes of data. For times were reported in . WSN data. le, when α = 0.25, the gateway must collect 256 KB Razvan Musaloiu-E, Chieh-Jan Mike Liang, Andreas Terzis, IPSN ‘08 a from each mote (6.25 MB in total), approximately 10 days when the data generation rate B = 18 bytes/min proximately every day if B =180 bytes/min. Table IV data uploaded to the back-end server. Note that in the power- es a list of all the model’s parameters. 102 mA Wi-Fi off conﬁguration this energy includes the cost of booting the stimate the gateway’s expected lifetime, we must com- gateway (cf. Sec.IV-B). s total energy consumption over time. This quantity is We combine the three factors to derive the results shown in 124 mA 3G m of three factors: (1) the energy consumption while the Figures 10 and 11. These ﬁgures show the cumulative energy y is sleeping (either in deep-sleep or power-off mode), consumption as a function of time in deep-sleep and power-off consumption when the gateway is actively collecting modes for both long-haul radios, when the gateway downloads (interface down) ata, and (3) the consumption while the gateway uploads data every one and every ten days respectively. Based on o the back-end server. We estimate each of these three these consumption rates, we estimate gateway lifetimes in two next. scenarios. First when the gateway is powered by standard AA- cell lithium batteries with a capacity of 3,000 mAh and second
18 Wi-Fi - deep-sleep 3G - deep-sleep 16 Wi-Fi - power-off 3G - power-off 14 Energy Consumption (mAh) 12 10 3. 8 6 Energy consumed 4 to 2 0 upload data. 100KB 250KB 500KB 750KB 1M Use a linear function of the amount of data uploaded.
ti on a tim Es 20000 Deep-sleep Energy Consumption (mAh) 15000 Power-off 10000 5000 3G - deep-sleep Wi-Fi - deep-sleep 3G - power-off Wi-Fi - power-off 0 0 50 100 150 200 250 300 19,000 mAh Days
2,000 days 1,860 days 1,500 days 300 days 1,071 days 300 days 1,000 days 225 days 150 days 137 days 500 days 75 days 31 days 16 days 18 days 34 days 0 days 0 days Deep-sleep Power-off Deep-sleep Power-off 3G 18 bytes/min Wi-Fi 180 bytes/min
Hardware Flashlite 186 RCM4500W RabbitCore Verdex XM4 JK microsystems Rabbit Semiconductors Gumstix Mod2570 Wildﬁre 5282 Imote2 Nerburner Intec Automation CrossBow
Software framework for WSN gateways. Battery-operated mote gateway. Investigate software and hardware alternatives.
Mike Acknowledgments LUYF Crew, Robert Szewczyk National Science Foundation, JHU/APL, Microsoft Research, Moore Foundation, Seaver Institute
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