Abstract
Some have argued that the dichotomy between high-performance operation and low resource utilization is false – an artifact that will soon succumb to Moore’s Law and careful engineering. If such claims prove to be true, then the traditional 8/16- vs. 32-bit power-performance tradeoffs become irrelevant, at least for some low-power embedded systems. We explore the veracity of this thesis using the 32-bit ARM Cortex-M3 microprocessor and find quite substantial progress but not deliverance. The Cortex-M3, compared to 8/16-bit microcontrollers, reduces latency and energy consumption for computationally intensive tasks as well as achieves near parity on code density. However, it still incurs a ~2× overhead in power draw for “traditional” sense-store-send-sleep applications. These results suggest that while 32-bit processors are not yet ready for applications with very tight power requirements, they are poised for adoption everywhere else. Moore’s Law may yet prevail.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abdelzaher, T., Anokwa, Y., Boda, P., Burke, J., Estrin, D., Guibas, L., Kansal, A., Madden, S., Reich, J.: Mobiscopes for human spaces. IEEE Pervasive Computing 6, 20–29 (2007)
Ali, A.M., Yao, K., Collier, T.C., Taylor, C.E., Blumstein, D.T., Girod, L.: An empirical study of collaborative acoustic source localization. In: IPSN (2007)
ARM Holdings. Cortex-M3 Processor, http://www.arm.com/products/processors/cortex-m/cortex-m3.php
Aslam, F., Schindelhauer, C., Ernst, G., Spyra, D., Meyer, J., Zalloom, M.: Introducing takatuka: a java virtualmachine for motes. In: SenSys (2008)
Atmel Corporation. Atmel ATMega 128 Microcontroller Datasheet, http://www.atmel.com/dyn/resources/prod_documents/doc2467.pdf
Atmel Corporation. AT91 ARM Cortex-M3 based MCUs: SAM3U Specifications (2009)
Chen, Y., Gnawali, O., Kazandjieva, M., Levis, P., Regehr, J.: Surviving Sensor Network Software Faults. In: SOSP (2009)
Coalition for American Trauma Care. Action Needed to Bolster Nation’s Emergency Care System (June 2006)
Crossbow Inc. Imote2: High-Performance Wireless Sensor Network Node (2007), http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/Imote2_Datasheet.pdf
Crossbow Technology Inc. MICAz wireless measurement system (June 2004), http://www.xbow.com
Free2move AB. Low power Audio BluetoothTM Module with antenna F2M03ALA Datasheet (2007), http://www.free2move.se
Freescale Semiconductor. Three axis low-g micromachined accelerometer, http://www.freescale.com
Hui, J.W., Culler, D.: The dynamic behavior of a data dissemination protocol for network programming at scale. In: SenSys (November 2004)
Klues, K., Handziski, V., Lu, C., Wolisz, A., Culler, D., Gay, D., Levis, P.: Integrating Concurrency Control and Energy Management in Device Drivers. In: SOSP (2007)
Klues, K., Liang, C.J., Paek, J., Musaloiu-E, R., Govindan, R., Terzis, A., Levis, P.: TOSThreads: Safe and Non-invasive Preemption in TinyOS. In: SenSys (November 2009)
Ko, J., Dawson-Haggerty, S., Gnawali, O., Culler, D., Terzis, A.: Evaluating the Performance of RPL and 6LoWPAN in TinyOS. In: Proceedings of the Workshop on Extending the Internet to Low Power and Lossy Networks (IP+SN 2011) (April 2011)
Ko, J., Lim, J., Chen, Y., Musaloiu-E., R., Terzis, A., Masson, G., Gao, T., Destler, W., Selavo, L., Dutton, R.: MEDiSN: Medical Emergency Detection in Sensor Networks. ACM Transactions on Embedded Computing Systems, TECS (2010)
Kusy, B., Richter, C., Hu, W., Afanasyev, M., Jurdak, R., Brunig, M., Abbott, D., Huynh, C., Ostry, D.: Radio diversity for reliable communication in wsns. In: IPSN (April 2011)
Liang, C.-J.M., Priyantha, N.B., Liu, J., Terzis, A.: Surviving wi-fi interference in low power zigbee networks. In: SenSys (2010)
Lorincz, K., Chen, B.R., Challen, G.W., Chowdhury, A.R., Patel, S., Bonato, P., Welsh, M.: Mercury: A Wearable Sensor Network Platform for High-Fidelity Motion Analysis. In: SenSys (2009)
Luo, L., Cao, Q., Huang, C., Abdelzaher, T., Stankovic, J.A., Ward, M.: Enviromic: Towards cooperative storage and retrieval in audio sensor networks. In: ICDCS (2007)
Malan, D., Fulford-Jones, T., Welsh, M., Moulton, S.: CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care. In: MobiSys 2004 Workshop on Applications of Mobile Embedded Systems (June 2004)
McIntire, D., Ho, K., Yip, B., Singh, A., Wu, W., Kaiser, W.: The low power energy aware processing (LEAP) embedded networked sensor system. In: IPSN/SPOTS (2006)
Moss, D., Hui, J., Klues, K.: TEP 105: Low Power Listening (2008), http://www.tinyos.net/tinyos-2.x/doc/pdf/tep105.pdf
Paek, J., Greenstein, B., Gnawali, O., Jang, K.-Y., Joki, A., Vieira, M., Hicks, J., Estrin, D., Govindan, R., Kohler, E.: The tenet architecture for tiered sensor networks. ACM Transactions on Sensor Networks (TOSN) 6(4) (2010)
Polastre, J., Szewczyk, R., Culler, D.: Telos: enabling ultra-low power wireless research. In: IPSN (2005)
Reddy, P.G., Sridhar, N.: Lakon: a middle-ground approach to high-frequency data acquisition and in-network processing in sensor networks. In: IPSN. ACM (2010)
Rumberg, B., Graham, D.W., Kulathumani, V.: Hibernets: energy-efficient sensor networks using analog signal processing. In: IPSN (2010)
Sadasivan, S.: An Introduction to the ARM Cortex-M3 Processor. Technical report (2006)
Sadler, C., Martonosi, M.: Data compression algorithms for energy-constrained devices in delay tolerant networks. In: SenSys (November 2006)
Schmid, T., Shea, R., Srivastava, M.B., Dutta, P.: Disentangling wireless sensing from mesh networking. In: HotEmNets (2010)
Schott, B., Bajura, M., Czarnaski, J., Flidr, J., Tho, T., Wang, L.: A modular power-aware microsensor with >1000x dynamic power range. In: IPSN (2005)
Simon, D., Cifuentes, C., Cleal, D., Daniels, J., White, D.: Java on the bare metal of wireless sensor devices: the squawk java virtual machine. In: International Conference on Virtual Execution Environments (2006)
Skraba, P., Guibas, L.: Energy Efficient Intrusion Detection in Camera Sensor Networks. In: Aspnes, J., Scheideler, C., Arora, A., Madden, S. (eds.) DCOSS 2007. LNCS, vol. 4549, pp. 309–323. Springer, Heidelberg (2007)
Smith, R.B.: Spotworld and the sun spot. In: IPSN (April 2007)
Texas Instruments. CC2520: Second generation 2.4 GHz IEEE 802.15.4 / ZigBee-ready RF Transceiver (2007), http://www.ti.com/lit/gpn/cc2520
Texas Instruments Incorporated. MSP430 Datasheet
Wood, A., Stankovic, J., Virone, G., Selavo, L., He, Z., Cao, Q., Doan, T., Wu, Y., Fang, L., Stoleru, R.: Context-Aware Wireless Sensor Networks for Assisted Living and Residential Monitoring. IEEE Network (2008)
Xu, N., Rangwala, S., Chintalapudi, K.K., Ganesan, D., Broad, A., Govindan, R., Estrin, D.: A Wireless Sensor Network for Structural Monitoring. In: SenSys (November 2004)
Zephyr Technology. BioHarness BT (2010), http://www.zephyr-technology.com
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ko, J. et al. (2012). Low Power or High Performance? A Tradeoff Whose Time Has Come (and Nearly Gone). In: Picco, G.P., Heinzelman, W. (eds) Wireless Sensor Networks. EWSN 2012. Lecture Notes in Computer Science, vol 7158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28169-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-28169-3_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28168-6
Online ISBN: 978-3-642-28169-3
eBook Packages: Computer ScienceComputer Science (R0)