A case for preamble compression in multi-clock-rate sampling devices for energy efficient idle listening
- 129 Downloads
The state of the art in wireless communication is highly spectrum efficient but performs poorly in terms of energy efficiency. With widespread deployment, battery operated devices, escalating energy cost, and inherent energy inefficiency of the Carrier Sense Multiple Access protocol in wireless, it is of prime importance today to look for improved energy efficiency in wireless communication. One promising solution is to use multi clock-rate sampling devices in conjunction with frequency agnostic preamble detection. This reduces the power consumed by wireless devices in idle listening, without significantly affecting the throughput and spectrum efficiency. In this paper, we model such a device as a Markov chain and determine its performance in terms of power consumption and goodput, and discuss the elemental trade-off between the two. The analytical results are verified using extensive simulation and compared with existing techniques. A preamble construction scheme that allows devices with different downclocking levels to coexist in the same network is also explored. Finally, we propose a novel preamble compression scheme based on Robust Header Compression to provide improved performance and scalability.
KeywordsEnergy efficiency CSMA Multi-clock-rate sampling Frequency agnostic preamble Header compression
This research work was supported by the Department of Science and Technology (DST), New Delhi, India.
- 1.Agarwal, Y., Chandra, R., Wolman, A., Bahl, P., Chin, K., & Gupta, R. (2007). Wireless wakeups revisited: Energy management for VOIP over WiFi smartphones. In Proceedings of the ACM international conference on mobile systems, applications and services (pp. 179–191).Google Scholar
- 2.Artheros Inc. (2004). Power consumption and energy efficiency of WLAN products. www.atheros.com/media/resource/resource_15_file2.
- 3.Bormann, C., Burmeister, C., Degermark, M., Fukushima, H., Hannu, H., Jonsson, L. E., Hakenberg, R., Koren, T., Le, K., Liu, Z., Martensson, A., Miyazaki, A., Svanbro, K., Wiebke, T., Yoshimura, T., & Zheng, H. (2001). RFC 3095: RObust Header Compression (ROHC): Framework and four profiles: RTP, UDP, ESP, and uncompressed. URL https://tools.ietf.org/html/rfc3095.
- 6.Dieter, W. R., Datta, S., & Kai, W. K. (2005). Power reduction by varying sampling rate. In Proceedings of the IEEE international symposium on low power electronics and design (pp. 227–232).Google Scholar
- 7.Dischler, J. (2015). Google Inside AdWords - Building for the next moment https://adwords.googleblog.com/2015/05/building-for-next-moment.html.
- 8.Elsayed, K. (1994). On the superposition of discrete-time Markov renewal processes and application to statistical multiplexing of bursty traffic sources. Proceedings of the IEEE Global Telecommunications Conference, 2, 1113–1117.Google Scholar
- 9.Feeney, L., & Nilsson, M. (2001). Investigating the energy consumption of a wireless network interface in an ad hoc networking environment. Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies, 3, 1548–1557.Google Scholar
- 10.Fracchia, R., Gomez, C., & Tripodi, A. (2011). R-RoHC: A single adaptive solution for header compression. In Proceedings of the IEEE vehicular technology conference (pp. 1–5).Google Scholar
- 13.IEEE Computer Society LAN-MAN Standards Committee (2007). Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. IEEE Strandard 802.11-2007.Google Scholar
- 14.Karl, H. (2003). An overview of energy efficiency techniques for mobile communication systems. Tech. Rep. TKN-03-017, Telecommunication Networks Group, Technische Universität Berlin. URL http://www2.tkn.tu-berlin.de/publications/papers/TechReport_03_017.
- 16.Klemm, A., Lindemann, C., & Lohmann, M. (2001). Traffic modeling and characterization for UMTS networks. In Proceedings of the IEEE global telecommunications conference (pp. 1741–1746).Google Scholar
- 17.Lella, A., & Lipsman, A. (2014). The U.S. mobile app report. http://www.comscore.com/Insights/Presentations-and-Whitepapers/2014/The-US-Mobile-App-Report.
- 18.Liu, J., & Zhong, L. (2008). Micro power management of active 802.11 interfaces. In Proceedings of the ACM international conference on mobile systems, applications and services (pp. 146–159).Google Scholar
- 19.Lu, F., Voelker, G. M., & Snoeren, A. C. (2013). SloMo: Downclocking WiFi communication. In Proceedings of the USENIX conference on networked systems design and implementation.Google Scholar
- 20.Manweiler, J., & Choudhury, R.R. (2011). Avoiding the rush hours: WiFi energy management via traffic isolation. In Proceedings of the ACM international conference on mobile systems, applications and services (pp. 253–266).Google Scholar
- 22.Polastre, J., Hill, J., & Culler, D. (2004). Versatile low power media access for wireless sensor networks. In Proceedings of the ACM international conference on embedded networked sensor systems (pp. 95–107).Google Scholar
- 23.Ren, Q., & Liang, Q. (2005). An energy-efficient MAC protocol for wireless sensor networks. Proceedings of the IEEE Global Telecommunications Conference, 1, 1–5.Google Scholar
- 24.Rozner, E., Navda, V., Ramjee, R., & Rayanchu, S. (2010). NAPman: Network-assisted power management for WiFi devices. In Proceedings of the international conference on mobile systems, applications and services (pp. 91–106).Google Scholar
- 25.Saulnier, E., & Vastola, K. (1992). A ‘HI-LO’ Markov chain model for multimedia traffic in ATM networks. In Proceedings of the IEEE global telecommunications conference (pp. 1450–1454).Google Scholar
- 26.Shih, E., Bahl, P., & Sinclair, M. J. (2002). Wake on wireless: An event driven energy saving strategy for battery operated devices. In Proceedings of the ACM annual international conference on mobile computing and networking (pp. 160–171).Google Scholar
- 27.Spiegel, M. R. (1992). Theory and problems of probability and statistics. New York: McGraw-Hill.Google Scholar
- 28.Thomson, J., & Baas, B., et al. (2002). An integrated 802.11a baseband and MAC processor. In Proceedings of the IEEE international solid-state circuits conference (pp. 92–415).Google Scholar
- 30.Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies, 3, 1567–1576.Google Scholar