Arda Gumusalan
ABSTRACT
Dynamic Modulation Scaling (DMS) is a well-known mechanism that can effectively exploit the tradeoff between communication time and energy consumption. In recent years a number of studies have suggested that DMS techniques can reduce energy consumption while maintaining performance objectives in low-power wireless transmission technologies such as those defined in IEEE 802.15.4. These studies tend to rely on theoretical or simulation DMS models to predict network performance metrics. However, there is little, if any, work that is based upon empirically verified network performance outcomes using DMS. This paper fills that gap. Our contribution is four-fold; first, using GNU~Radio and SDR hardware we show how to emulate DMS in low power wireless systems. Second, we measure the impact of varying Signal-to-Noise levels on throughput and delivery rates for different DMS control strategies. Third, using DMS we quantify the impact of distance and finally, we measure the impact of different elevations between sender and receiver on network performance. Our results provide an empirical basis for future work in this area.
- {n. d.}. https://forums.ni.com/t5/USRP-Software-Radio/How-to-set-the-trasmitpower-of-USRP/td-p/2202190. https://forums.ni.com/t5/USRP-Software-Radio/How-to-set-the-trasmit-power-of-USRP/td-p/2202190Google Scholar
- IEEE 802.11p 2010 Standard. {n. d.}. IEEE 802.11p-2010. https://www.ietf.org/mail-archive/web/its/current/pdfqf992dHy9x.pdf Last accessed on 2018-Feb-21.Google Scholar
- IEEE 802.15.4e Standard. {n. d.}. https://standards.ieee.org/findstds/standard/802.15.4e-2012.html Last accessed on 2017-May-22.Google Scholar
- Giuseppe Anastasi, Marco Conti, Mario Di Francesco, and Andrea Passarella. 2009. Energy conservation in wireless sensor networks: A survey. Ad hoc networks 7, 3 (2009), 537--568. Google ScholarDigital Library
- KR Damindra S Bandara, Anthony Melaragno, Duminda Wijesekera, and Paulo Costa. 2017. A case study of cognitive radio networks: Secure spectrum management for positive train control operations. In Spectrum Access and Management for Cognitive Radio Networks. Springer, 121--152.Google Scholar
- Maryam Bandari, Robert Simon, and Hakan Aydin. 2016. On minimizing expected energy usage of embedded wireless systems with probabilistic workloads. Sustainable Computing: Informatics and Systems 11 (2016), 50--62.Google ScholarCross Ref
- Bastian Bloessl, Michele Segata, Christoph Sommer, and Falko Dressler. 2013. Towards an Open Source IEEE 802.11 p stack: A full SDR-based transceiver in GNU Radio. In Vehicular Networking Conference (VNC), 2013 IEEE. IEEE, 143--149.Google Scholar
- Alberto Cerpa and Deborah Estrin. 2002. Ascent: Adaptive self-configuring sensor network topologies. ACM SIGCOMM Computer Communication Review 32, 1 (2002), 62--62. Google ScholarDigital Library
- Benjie Chen, Kyle Jamieson, Hari Balakrishnan, and Robert Morris. 2002. Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wireless networks 8, 5 (2002), 481--494. Google ScholarDigital Library
- Shuguang Cui, Andrea J Goldsmith, and Ahmad Bahai. 2005. Energy-constrained modulation optimization. IEEE transactions on wireless communications 4, 5 (2005), 2349--2360. Google ScholarDigital Library
- Franz Edbauer. 1992. Bit error rate of binary and quaternary DPSK signals with multiple differential feedback detection. IEEE Transactions on Communications 40, 3 (1992), 457--460.Google ScholarCross Ref
- Benazir Fateh and Manimaran Govindarasu. 2013. Energy minimization by exploiting data redundancy in real-time wireless sensor networks. Ad Hoc Networks 11, 6 (2013), 1715--1731.Google ScholarCross Ref
- B. Fateh and M. Govindarasu. 2015. Joint Scheduling of Tasks and Messages for Energy Minimization in Interference-aware Real-time Sensor Networks. Mobile Computing, IEEE Transactions on 14, 1 (2015), 86--98.Google Scholar
- Arda Gumusalan, Robert Simon, and Hakan Aydin. 2016. Adaptive Transmission Scheduling for Energy-Aware Real-Time Wireless Communication. In Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks (EWSN '16). Junction Publishing, USA, 1--12. http://dl.acm.org/citation.cfm?id=2893711.2893713 Google ScholarDigital Library
- Arda Gumusalan, Robert Simon, and Hakan Aydin. 2018. Flexible Real-time Transmission Scheduling for Wireless Networks with Non-deterministic Workloads. Ad Hoc Networks (2018). Google ScholarDigital Library
- Paul Ho and Dominic Fung. 1991. Error performance of multiple symbol differential detection of PSK signals transmitted over correlated Rayleigh fading channels. In Communications, 1991. ICC'91, Conference Record. IEEE International Conference on. IEEE, 568--574.Google ScholarCross Ref
- Texas Instruments. {n. d.}. Sub1GHz radios. http://www.ti.com/wireless-connectivity/simplelink-solutions/sub-1-ghz/products.html Last accessed on 2018-March-5.Google Scholar
- Tomas Lennvall, Stefan Svensson, and Fredrik Hekland. 2008. A comparison of WirelessHART and ZigBee for industrial applications. In Proceedings of IEEE International Workshop on Factory Communication Systems.Google ScholarCross Ref
- Minyoung Park. 2015. IEEE 802.11 ah: sub-1-GHz license-exempt operation for the internet of things. IEEE Communications Magazine 53, 9 (2015), 145--151.Google ScholarCross Ref
- Ettus Research. {n. d.}. Ettus USRP B210. https://www.ettus.com/product/details/UB210-KIT Last accessed on 2018-Feb-22.Google Scholar
- Curt Schurgers, Vijay Raghunathan, and Mani B Srivastava. 2003. Power management for energy-aware communication systems. ACM Transactions on Embedded Computing Systems 2, 3 (2003), 431--447. Google ScholarDigital Library
- Jianping Song, Song Han, Aloysius K Mok, Deji Chen, Margaret Lucas, and Mark Nixon. 2008. WirelessHART: Applying wireless technology in real-time industrial process control. In Proceedings of IEEE Real-Time and Embedded Technology and Applications Symposium. Google ScholarDigital Library
- IEEE 802.15.4--2015 Standard. {n. d.}. https://standards.ieee.org/findstds/standard/802.15.4--2015.html Last accessed on 2018-Feb-21.Google Scholar
- Hai Wang and Abraham O Fapojuwo. 2017. A survey of enabling technologies of low power and long range machine-to-machine communications. IEEE Communications Surveys & Tutorials 19, 4 (2017), 2621--2639.Google ScholarCross Ref
- Xiong Xiong, Kan Zheng, Rongtao Xu, Wei Xiang, and Periklis Chatzimisios. 2015. Low power wide area machine-to-machine networks: key techniques and prototype. IEEE Communications Magazine 53, 9 (2015), 64--71.Google ScholarDigital Library
- Yang Yu, Viktor K Prasanna, and Bhaskar Krishnamachari. 2006. Energy minimization for real-time data gathering in wireless sensor networks. IEEE Transactions on Wireless Communications 5, 11 (2006). Google ScholarDigital Library
- Bo Zhang, Robert Simon, and Hakan Aydin. 2013. Harvesting-aware energy management for time-critical wireless sensor networks with joint voltage and modulation scaling. Industrial Informatics, IEEE Transactions on 9, 1 (2013), 514--526.Google ScholarCross Ref
Index Terms
- A Software-Defined Radio Analysis of the Impact of Dynamic Modulation Scaling within Low-Power Wireless Systems
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