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Energy Management Techniques for WSNs (1): Duty-Cycling Approach

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Wireless Sensor Networks

Part of the book series: Signals and Communication Technology ((SCT))

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Abstract

Along this chapter, duty-cycling is methodically described and categorized, protocols are analyzed and compared. As abundantly detailed, duty-cycling can be achieved through two different and yet complementary approaches; specifically, topology control and power management. Topology control is by finding the optimal subset of nodes that guarantee connectivity. This scheme exploits node redundancy, which is typical in WSNs, and adaptively selects only a minimum subset of nodes to remain active for maintaining connectivity. Nodes that are not currently needed for ensuring connectivity can go to sleep and save energy. Therefore, the basic idea behind topology control is to exploit the network redundancy to prolong the network longevity, typically increasing the network lifetime by a factor of 2–3 with respect to a network with all nodes always ON. Topology control protocols encompass location-driven protocols and connectivity-driven protocols. Power management is by operating duty-cycling on active nodes. Active nodes are those selected by the topology control protocol; they do not need to maintain their radio continuously ON. They can switch OFF the radio, by putting it in the low-power sleep mode, when there is no network activity, thus alternating between sleep and wakeup periods.

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Notes

  1. 1.

    Percolation is the process of a liquid slowly passing through a filter; it is how coffee is usually made. In statistical physics and mathematics, percolation theory describes the behavior of connected clusters in a random graph.

  2. 2.

    In physics, it means of unequal physical properties along different axes.

    In Botany, it means of different dimensions along different axes.

  3. 3.

    First published in SenSys’03.

  4. 4.

    Starvation is a problem encountered in concurrent computing where a process is perpetually denied necessary resources to process its work. Starvation may be caused by errors in a scheduling or mutual exclusion algorithm, but can also be caused by resource leaks and can be intentionally caused via a denial-of-service attack. In computer networks, especially wireless networks, scheduling algorithms may suffer from scheduling starvation; an example is maximum throughput scheduling.

  5. 5.

    CCA is a technique used by MAC protocols to effectively avoid collisions, and it accurately determines if the channel is clear.

  6. 6.

    A value that “lies outside” (is much smaller or larger than) most of the other values in a set of data.

References

  • Al-Karaki, J.N., and A.E. Kamal. 2004. “Routing Techniques in Wireless Sensor Networks: A Survey.” Wireless Communications (IEEE) 11 (6): 6–28.

    Article  Google Scholar 

  • Anastasi, G., E. Borgia, M. Conti, E. Gregori, and A. Passarella. 2005. “Understanding the Real Behavior of Mote and 802.11 Ad Hoc Networks: An Experimental Approach.” Pervasive and Mobile Computing 1 (2): 237–256.

    Article  Google Scholar 

  • Anastasi, G., M. Conti, M. Di Francesco, and A. Passarella. 2009. “Energy Conservation in Wireless Sensor Networks: A Survey.” Ad Hoc Networks 7 (3): 537–568.

    Article  Google Scholar 

  • Ansari, J., D. Pankin, and P. Mähönen. 2009. “Radio-Triggered Wake-Ups with Addressing Capabilities for Extremely Low Power Sensor Network Applications.” International Journal of Wireless Information Networks 16 (3): 118.

    Google Scholar 

  • Arisha, K., M. Youssef, and M. Younis. 2002. “Energy-Aware TDMA-Based MAC for Sensor Networks.” In System-Level Power Optimization for Wireless Multimedia Communication, ed. R. Karri and D. Goodman, 21–40. Boston, MA: Springer.

    Google Scholar 

  • Atmel. 8-bit Atmel Microcontroller with 128KBytes in-System Programmable Flash. Atmel. January 1, 2011. http://www.atmel.com/Images/doc2467.pdf. Accessed 21 Mar 2014.

  • Bachir, A., M. Dohler, T. Watteyne, and K.K. Leung. 2010. “MAC Essentials for Wireless Sensor Networks.” IEEE Communications Surveys & Tutorials (IEEE) 12 (2): 222–248.

    Article  Google Scholar 

  • Bao, L., and L.L. Garcia-Luna-Aceves. 2001. “A New Approach to Channel Access Scheduling for Ad Hoc Networks.” In The 7th Annual International Conference on Mobile Computing and Networking (MobiCom), 210–221. Rome, Italy: ACM.

    Google Scholar 

  • Bao, L., and J.J. Garcia-Luna-Aceves. 2003. “Topology Management in Ad Hoc Networks.” In The 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 129–140. Annapolis, MD: ACM.

    Google Scholar 

  • Bharghavan, V., A. Demers, S. Shenker, and L. Zhang. 1994. “MACAW: A Media Access Protocol for Wireless LAN’s.” In The Conference on Communications Architectures, Protocols and Applications (SIGCOMM), 212–225. London, UK: ACM.

    Article  Google Scholar 

  • Cao, Q., T. Abdelzaher, T. He, and J. Stankovic. 2005. “Towards Optimal Sleep Scheduling in Sensor Networks for Rare-Event Detection.” In The 4th International Symposium on Information Processing in Sensor Networks (IPSN), Los Angeles, CA: ACM.

    Google Scholar 

  • Casari, P., A. Marcucci, M. Nati, C. Petrioli, and M. Zorzi. 2005. “A Detailed Simulation Study of Geographic Random Forwarding (GeRaF) in Wireless Sensor Networks.” In Military Communications Conference (MILCOM), 59–68. Atlantic City, NJ: IEEE.

    Google Scholar 

  • Cerpa, A., and D. Estrin. 2004. “ASCENT: Adaptive Self-Configuring Sensor Networks Topologies.” Transactions on Mobile Computing (IEEE) 3 (3): 272–285.

    Article  Google Scholar 

  • Chen, B., K. Jamieson, H. Balakrishnan, and R. Morris. 2002. “Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks.” Wireless Networks 8 (5): 481–494.

    Google Scholar 

  • Cohen, R., and B. Kapchits. 2009. “An Optimal Wake-Up Scheduling Algorithm for Minimizing Energy Consumption While Limiting Maximum Delay in a Mesh Sensor Network.” Transactions on Networking (TON) 17 (2): 570–581.

    Article  Google Scholar 

  • Cooklev, T. 2004. Wireless Communication Standards: A Study of IEEE 802.11, 802.15, and 802.16. NY: Standards Information Network - IEEE Press.

    Google Scholar 

  • Crossbow. January 1, 2002. MICA2. http://www.eol.ucar.edu/isf/facilities/isa/internal/CrossBow/DataSheets/mica2.pdf. Accessed 3 Feb 2014.

  • Crossbow. January 1, 2002. MICA2DOT. http://www.eol.ucar.edu/isf/facilities/isa/internal/CrossBow/DataSheets/mica2dot.pdf. Accessed 5 Feb 2014.

  • Dai, H., and R. Han. 2004. “TSync: A Lightweight Bidirectional Time Synchronization Service for Wireless Sensor Networks.” ACM SIGMOBILE Mobile Computing and Communications Review (ACM) 8 (1): 125–139.

    Article  Google Scholar 

  • Demirkol, I., C. Ersoy, and F. Alagoz. 2006. “MAC Protocols for Wireless Sensor Networks: A Survey.” Communications Magazine (IEEE) 44 (4): 115–121.

    Article  Google Scholar 

  • Dictionary.com. January 1, 2017. Anisotropic. Dictionary.com, LLC. http://www.dictionary.com/browse/anisotropy. Accessed 8 Apr 2017.

  • Dousse, O., P. Mannersalo, and P. Thiran. 2004. “Latency of Wireless Sensor Networks with Uncoordinated Power Saving Mechanisms.” In The 5th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 109–120. Tokyo, Japan: ACM.

    Google Scholar 

  • Dousse, O., F. Baccelli, and P. Thiran. 2005. “Impact of Interferences on Connectivity in Ad Hoc Networks.” Transactions on Networking (TON) 13 (2): 425–436.

    Article  Google Scholar 

  • Dousse, O., M. Franceschetti, N. Macris, and R. Meester. 2006. “Percolation in the Signal to Interference Ratio Graph.” Journal of Applied Probability 43 (2): 552–562.

    Article  MathSciNet  MATH  Google Scholar 

  • Dulman, S.O., and P.J.M Havinga. 2003. A Simulation Template for Wireless Sensor Networks, vol. 6. Enschede, The Netherlands: University of Twente, Centre for Telematica and Information Technology (CTIT).

    Google Scholar 

  • Dutta, P., M. Grimmer, A. Arora, S. Bibyk, and D. Culler. 2005. “Design of a Wireless Sensor Network Platform for Detecting Rare, Random, and Ephemeral Events.” In The 4th International Symposium on Information Processing in Sensor Networks (IPSN). Los Angeles, CA: ACM SIGBED and IEEE Signal Processing Society.

    Google Scholar 

  • Elson, J., L. Girod, and D. Estrin. 2002. “Fine-Grained Network Time Synchronization using Reference Broadcasts.” In The 5th Symposium on Operating Systems Design and Implementation (OSDI), 147–163. Boston, MA: ACM.

    Article  Google Scholar 

  • Engstrom, J.C., and C. Gray. 2008. “Clear channel assessment in wireless sensor networks.” In The 46th Annual Southeast Regional Conference (ACM-SE), 464–468. Auburn, AL: ACM.

    Google Scholar 

  • Ephremides, A., and O.A. Mowafi. 1982. “Analysis of A Hybrid Access Scheme for Buffered Users-Probabilistic Time Division.” Transactions on Software Engineering SE-8 (1): 52–61.

    Article  Google Scholar 

  • Fahmy, H.M.A. 2016. “Simulators and Emulators for WSNs.” In Wireless Sensor Networks: Concepts, Applications, Experimentation and Analysis, 381–491. Singapore: Springer.

    Google Scholar 

  • Faizulkhakov, Y.R. 2007. “Time Synchronization Methods for Wireless Sensor Networks: A Survey.” Programming and Computer Software 33 (4): 214–226.

    Article  MathSciNet  MATH  Google Scholar 

  • Fang, Q., J. Gao, and L.J. Guibas. 2006. “Locating and Bypassing Holes in Sensor Networks.” Mobile Networks and Applications 11 (2): 187–200.

    Article  Google Scholar 

  • Ganeriwal, S., R. Kumar, and M.B. Srivastava. 2003. “Timing-Sync Protocol for Sensor Networks.” In The 1st International Conference on Embedded Networked Sensor Systems (SenSys), 138–149. Los Angeles, CA: ACM.

    Google Scholar 

  • Ganesan, D., D. Estrin, A. Woo, and D. Culler. 2002. Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks. Los Angeles, CA: Technical, Computer Science Department, University of California Los Angeles (UCLA).

    Google Scholar 

  • Ganesan, D., A. Cerpa, W. Ye, Y. Yu, J. Zhao, and D. Estrin. 2004. “Networking Issues in Wireless Sensor Networks.” Journal of Parallel and Distributed Computing 64 (7): 799–814.

    Article  Google Scholar 

  • Garey, M.R., and D.S. Johnson. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. New York: W.H. Freeman and Company.

    Google Scholar 

  • Godfrey, P.B., and D. Ratajczak. 2004. “Naps: Scalable, Robust Topology Management in Wireless Ad Hoc Networks.” In The 3rd International Symposium on Information Processing in Sensor Networks (IPSN), 443–451. Berkeley, CA: ACM.

    Google Scholar 

  • Grimmett, G. 1999. “What is Percolation?” In Percolation, ed. G. Grimmett, 1–31. Berlin: Springer.

    Google Scholar 

  • Gu, L., and J.A. Stankovic. 2005. “Radio-Triggered Wake-Up for Wireless Sensor Networks”. Real-Time Systems 29 (2): 157–182.

    Article  Google Scholar 

  • Gupta, P., and P.R. Kumar. 1999. “Critical power for asymptotic connectivity in wireless networks.” In Stochastic Analysis, Control, Optimization and Applications, ed. W.M. McEneaney, G.G. Yin, and Q. Zhang, 547–566. Cambridge, MA: Birkhäuser Boston.

    Chapter  Google Scholar 

  • Gupta, P., and P.R. Kumar. 2000. “The Capacity of Wireless Networks.” Transactions on Information Theory (IEEE) 46 (2): 388–404.

    Article  MathSciNet  MATH  Google Scholar 

  • Haartsen, J.C. 2000. “The Bluetooth Radio System.” Personal Communications 7 (1): 28–36.

    Article  Google Scholar 

  • Halkes, G.P., and K.G. Langendoen. 2007. “Crankshaft: An Energy-Efficient MAC-Protocol for Dense Wireless Sensor Networks.” In The 4th European Conference on Wireless Sensor Networks (EWSN), 228–244. Delft, The Netherlands: Springer.

    Google Scholar 

  • Havinga, P., et al. 2003. “EYES—Energy Efficient Sensor Networks.” In Lecture Notes in Computer Science: Personal Wireless Communications (PWC), vol. 2775, ed. M. Conti, S. Giordano, E. Gregori, and S. Olariu, 198–201. Berlin, Heidelberg: Springer.

    Google Scholar 

  • He, T., J.A. Stankovic, C. Lu, and T. Abdelzaher. 2003. “SPEED: A Stateless Protocol for Real-Time Communication in Sensor Networks.” In The 23rd International Conference on Distributed Computing Systems (ICDCS), 46–55. Providence, RI: IEEE.

    Google Scholar 

  • Heinzelman, W.R., A. Chandrakasan, and H. Balakrishnan. 2000. “Energy-Efficient Communication Protocol for Wireless Microsensor Networks.” In The 33rd Annual Hawaii International Conference on System Sciences (HICSS). Maui, Hawaii: IEEE.

    Google Scholar 

  • Hill, J.L., and D.E. Culler. 2002. “Mica: A Wireless Platform for Deeply Embedded Networks.” IEEE Micro 22 (6): 12–24.

    Article  Google Scholar 

  • Intanagonwiwat, C., D. Estrin, R. Govindan, and J. Heidemann. 2002. “Impact of Network Density on Data Aggregation in Wireless Sensor Networks.” In The 22nd International Conference on Distributed Computing Systems, 457–458. Vienna, Austria: IEEE.

    Google Scholar 

  • Jain, R.K., D.-M. Chiu, and W.R. Hawe. 1984. A Quantitative Measure of Fairness and Discrimination for Resource Allocation in Shared Computer Systems. Hudson, MA: Technical, Eastern Research Lab., Digital Equipment Corporation.

    Google Scholar 

  • Jamieson, K., H. Balakrishnan, and Y.C. Tay. 2006. “Sift: A MAC protocol for event-driven wireless sensor networks.” In Lecture Notes in Computer Science: European Workshop on Wireless Sensor Networks (EWSN), vol. 3868, ed. K. Römer, H. Karl, and F. Mattern, 260–275. Berlin, Heidelberg: Springer.

    Google Scholar 

  • Johnson, D.B., and D.A. Maltz. 1996. “Dynamic Source Routing in Ad Hoc Wireless Networks.” In Mobile Computing, vol. 353, ed. T. Imielinski and H.F. Korth, 153–181. Berlin: Springer.

    Google Scholar 

  • Kansal, A., J. Hsu, S. Zahedi, and M.B. Srivastava. 2007. “Power Management in Energy Harvesting Sensor Networks.” In ACM Transactions on Embedded Computing Systems (TECS)—Special Section LCTES’05 (p. 6, no. 4). ACM.

    Google Scholar 

  • Karl, H., and A. Willig. 2007. Protocols and Architectures for Wireless Sensor Networks. Chichester, West Sussex: Wiley.

    Google Scholar 

  • Karp, B., and H.T. Kung. 2000. “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks.” In The 6th Annual International Conference on Mobile Computing and Networking (MobiCom), 243–254. Boston, MA: ACM.

    Google Scholar 

  • Keshavarzian, A., H. Lee, and L. Venkatraman. 2006. “Wakeup Scheduling in Wireless Sensor Networks.” In The 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 322–333. Florence, Italy: ACM.

    Google Scholar 

  • Koushanfar, F., N. Taft, and M. Potkonjak. 2006. “Sleeping Coordination for Comprehensive Sensing Using Isotonic Regression and Domatic Partitions.” In The 25th IEEE International Conference on Computer Communications (INFOCOM), 1–13. Barcelona, Spain: IEEE.

    Google Scholar 

  • Krishnamachari, L., D. Estrin, and S. Wicker. 2002. “The Impact of Data Aggregation in Wireless Sensor Networks.” In The 22nd International Conference on Distributed Computing Systems Workshops (ICDCS), 575–578. Vienna, Austria: IEEE.

    Google Scholar 

  • Lai, W., and I. Paschalidis. 2006. “Routing Through Noise and Sleeping Nodes in Sensor Networks: Latency vs. Energy Trade-Offs.” In The 45th IEEE Conference on Decision and Control (CDC), 2716–2721. San Diego, CA: IEEE.

    Google Scholar 

  • LAN MAN Standards Committee. 1997. Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specification. New York, NY: IEEE Std 802.11, LAN MAN Standards Committee, IEEE Computer Society.

    Google Scholar 

  • Langendoen, K., and N. Reijers. 2003. “Distributed Localization in Wireless Sensor Networks: A Quantitative Comparison.” Computer Networks 43 (4): 499–518.

    Article  MATH  Google Scholar 

  • Lee, M., and V.W.S. Wong. 2005. “An Energy-Aware Spanning Tree Algorithm for Data Aggregation in Wireless Sensor Networks.” In The Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM), 300–303. Victoria, B.C., Canada: IEEE.

    Google Scholar 

  • Li, J., and G.Y. Lazarou. 2004. “A Bit-Map-Assisted Energy-Efficient MAC Scheme for Wireless Sensor Networks.” In The 3rd International Symposium on Information Processing in Sensor Networks (IPSN), 55–60. Berkeley, CA: ACM.

    Google Scholar 

  • Li, J., C. Blake, D.S.J. De Couto, H.I. Lee, and R. Morris. 2001. “Capacity of Ad Hoc Wireless Networks.” In The 7th Annual International Conference on Mobile Computing and Networking (MobiCom), 61–69. Rome, Italy: ACM.

    Google Scholar 

  • Li, Y., W. Ye, and J. Heidemann. 2005. “Energy and Latency Control in Low Duty Cycle MAC Protocols.” In: Wireless Communications and Networking Conference (WCNM). New Orleans, LA: IEEE.

    Google Scholar 

  • Liggett, T.M. 1985. “An Improved Subadditive Ergodic Theorem.” The Annals of Probability 13 (4): 1279–1285.

    Article  MathSciNet  MATH  Google Scholar 

  • Liu, X. 2012. “A Survey on Clustering Routing Protocols in Wireless Sensor Networks.” Sensors (MDPI) 12 (8): 11113–11153.

    Article  Google Scholar 

  • Lu, G., B. Krishnamachari, and C.S. Raghavendra. 2004. “An Adaptive Energy-Efficient and Low-Latency MAC for Data Gathering in Wireless Sensor Networks.” In The 18th International Parallel and Distributed Processing Symposium (IPDPS). Santa Fe, NM: IEEE.

    Google Scholar 

  • Lu, G., N. Sadagopan, B. Krishnamachari, and A. Goel. 2005. “Delay Efficient Sleep Scheduling in Wireless Sensor Networks.” In The 24th Annual Joint Conference of the IEEE Computer and Communications Societies (Infocom), 2470–2481. Miami, FL: IEEE.

    Google Scholar 

  • Mainwaring, A., D. Culler, J. Polastre, R. Szewczyk, and J. Anderson. 2002. “Wireless Sensor Networks for Habitat Monitoring.” In The 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA), 88–97. Atlanta, GA: ACM.

    Google Scholar 

  • Malesci, U., and S. Madden. 2006. “A measurement-based analysis of the interaction between network layers in TinyOS.” In Lecture Notes in Computer Science: Wireless Sensor Networks (EWSN), vol. 3868, ed. K. Römer, H. Karl, and F. Mattern, 292–309. Berlin, Heidelberg: Springer.

    Google Scholar 

  • Mangione-Smith, W., P. Ghang, S. Nazareth, P. Lettieri, W. Boring, and R. Jain. 1996. “A Low Power Architecture for Wireless Multimedia Systems: Lessons Learned from Building A Power Hog.” In International Symposium on Low Power Electronics and Design (ISLPED), 23–28. Monterey, CA: ACM.

    Google Scholar 

  • Mao, G., B. Fidan, and B.D.O. Anderson. 2007. “Wireless Sensor Network Localization Techniques.” Computer Networks 51 (10): 2529–2553.

    Article  MATH  Google Scholar 

  • McGlynn, M.J., and S.A. Borbash. 2001. “Birthday Protocols for Low Energy Deployment and Flexible Neighbor Discovery in Ad Hoc Wireless Networks.” In The 2nd ACM International Symposium on Mobile Ad Hoc Networking & Computing (MobiHoc), 137–145. Long Beach, CA: ACM.

    Google Scholar 

  • Meester, R., and R. Roy. 1996. Continuum Percolation. New York, NY: Cambridge University Press.

    Google Scholar 

  • Melodia, T., D. Pompili, and I.F. Akyildiz. 2005. “On the Interdependence of Distributed Topology Control and Geographical Routing in Ad Hoc and Sensor Networks.” Journal on Selected Areas in Communications (IEEE) 23 (3): 520–533.

    Article  Google Scholar 

  • Miller, M.J., and N.H. Vaidya. 2004. “Power Save Mechanisms for Multi-Hop Wireless Networks.” In First International Conference on Broadband Networks, 518–526. San Jose, CA: IEEE.

    Google Scholar 

  • Murata Electronics. December 31, 2014. TR1001: 868.35 MHz Hybrid Transceiver. Murata Electronics N.A., Inc. http://wireless.murata.com/RFM/data/tr1001.pdf. Accessed 27 Sept 2017.

  • Murata Electronics. December 31, 2015a. TR3000: 433.92 MHz Hybrid Transceiver. Murata Electronics N.A., Inc. http://wireless.murata.com/datasheet?/RFM/data/tr3000.pdf?ref=rfm.com. Accessed 25 Sept 2017.

  • Murata Electronics. January 1, 2015b. TR1000: 916.50 MHz Hybrid Transceiver. Murata Electronics N.A., Inc. http://wireless.murata.com/RFM/data/tr1000.pdf. Accessed 17 Mar 2017.

  • Nieberg, T., S. Dulman, P. Havinga, L. van Hoesel, and J. Wu. 2003. “Collaborative Algorithms for Communication in Wireless Sensor Networks.” In Ambient Intelligence: Impact on Embedded System Design, ed. T. Basten, M. Geilen, and H. de Groot, 271–294. Boston, MA: Springer.

    Chapter  Google Scholar 

  • NIST/SEMATECH. October 30, 2013. What Are Outliers in the Data? NIST/SEMATECH. http://www.itl.nist.gov/div898/handbook/prc/section1/prc16.htm. Accessed 24 Oct 2017.

  • Pantazis, N.A., and D.D. Vergados. 2007. “A Survey on Power Control Issues in Wireless Sensor Networks.” Communications Surveys & Tutorials 9 (4): 86–107.

    Article  Google Scholar 

  • Paruchuri, V., S. Basavaraju, A. Durresi, R. Kannan, and S.S. Iyengar. 2004. “Random Asynchronous Wakeup Protocol for Sensor Networks.” In First International Conference on Broadband Networks (BroadNets), 710–717. San Jose, CA: IEEE.

    Google Scholar 

  • Penrose, M. 2003. Random Geometric Graphs. New York: Oxford University Press.

    Google Scholar 

  • Perkins, C., E. Belding-Royer, and S. Das July 1, 2003. RFC 3561-Ad Hoc On-Demand Distance Vector (AODV) routing. Network Working Group. http://www.rfc-editor.org/rfc/pdfrfc/rfc3561.txt.pdf. Accessed 15 July 2015.

  • Polastre, J., J. Hill, and D. Culler. 2004. “Versatile Low Power Media Access for Wireless Sensor Networks.” In The 2nd International Conference on Embedded Networked Sensor Systems (SenSys), 95–107. Baltimore, MD: ACM.

    Google Scholar 

  • Proakis, J.G., and M. Salehi. 2007. Digital Communications. New York, NY: McGraw-Hill Education.

    Google Scholar 

  • Raghunandan, G.H., and B.N. Lakshmi. 2011. “A Comparative Analysis of Routing Techniques for Wireless Sensor Networks.” In National Conference on Innovations in Emerging Technology (NCOIET), 17–22. Erode, India: IEEE.

    Google Scholar 

  • Raghunathan, V., C. Schurgers, S. Park, and M.B. Srivastava. 2002. “Energy-Aware Wireless Microsensor Networks.” Signal Processing Magazine 19 (2): 40–50.

    Article  Google Scholar 

  • Rajendran, V., J.J. Garcia-Luna-Aveces, and K. Obraczka. 2005. “Energy-Efficient, Application-Aware Medium Access for Sensor Networks.” In International Conference on Mobile Ad Hoc and Sensor Systems Conference (MASS), 623–630. Washington, DC: IEEE.

    Google Scholar 

  • Rajendran, V., K. Obraczka, and J.J. Garcia-Luna-Aceves. 2006. “Energy-Efficient, Collision-Free Medium Access Control for Wireless Sensor Networks”. Wireless Networks 12 (1): 63–78.

    Article  Google Scholar 

  • Ramanathan, S. 1999. “A Unified Framework and Algorithm for Channel Assignment in Wireless Networks.” Wireless Networks 5 (2): 81–94.

    Google Scholar 

  • Rao, A., S. Ratnasamy, C. Papadimitriou, S. Shenker, and I. Stoica. 2003. “Geographic Routing Without Location Information.” In The 9th Annual International Conference on Mobile Computing and Networking (MobiHoc), 96–108. San Diego, CA: ACM.

    Google Scholar 

  • Raynal, M. 2013. Concurrent Programming: Algorithms, Principles, and Foundations. Berlin, Heidelberg: Springer.

    Book  MATH  Google Scholar 

  • RFM. May 19, 2004. ASH Transceiver Designer’s Guide. https://wireless.murata.com/RFM/data/tr_des24.pdf. Accessed 23 Nov 2017.

  • Rhee, I., A. Warrier, J. Min, and L. Xu. 2006. “DRAND: Distributed Randomized Tdma Scheduling for Wireless Ad-Hoc Networks.” In The 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 190–201. Florence, Italy: ACM.

    Google Scholar 

  • Rhee, I., A. Warrier, M. Aia, J. Min, and L.S. Mihail. 2008. “Z-MAC: A Hybrid MAC for Wireless Sensor Networks.” IEEE/ACM Transactions on Networking (TON) 16 (3): 511–524.

    Article  Google Scholar 

  • Santi, P. 2005. “Topology Control in Wireless Ad Hoc and Sensor Networks.” Computing Surveys (CSUR) 37 (2): 164–194.

    Google Scholar 

  • Schurgers, C., V. Tsiatsis, S. Ganeriwal, and M. Srivastava. 2002. “Optimizing Sensor Networks in The Energy-Latency-Density Design Space.” Transactions on Mobile Computing 99 (1): 70–80.

    Article  Google Scholar 

  • Shih, E., P. Bahl, and M.J. Sinclair. 2002. “Wake on Wireless: An Event Driven Energy Saving Strategy for Battery Operated Devices.” The 8th Annual International Conference on Mobile Computing and Networking (MobiCom), 160–171. Atlanta, GA: ACM.

    Google Scholar 

  • Singh, S., and C.S. Raghavendra. 1998. “PAMAS: Power Aware Multi-Access Protocol with Signalling for Ad Hoc Networks.” Computer Communication 28 (3): 5–26.

    Article  Google Scholar 

  • Sinha, A., and A. Chandrakasan. 2001. “Dynamic Power Management in Wireless Sensor Networks.” Design & Test of Computers 18 (2): 62–74.

    Article  Google Scholar 

  • Sivrikaya, F., and B. Yener. 2004. “Time Synchronization in Sensor Networks: A Survey.” Network 18 (4): 45–50.

    Article  Google Scholar 

  • SparkFun Electronics. January 1, 2016. The Basics of GPS. SparkFun Electronics. https://learn.sparkfun.com/tutorials/gps-basics. Accessed 16 Aug 2016.

  • Stemm, M., and R.H. Katz. 1997. “Measuring and Reducing Energy Consumption of Network Interfaces in Hand-Held Devices.” Transactions on Communications E80-B (8): 1125–1131.

    Google Scholar 

  • Tang, L., Y. Sun, O. Gurewitz, and D.B. Johnson. 2011. “PW-MAC: An Energy-Efficient Predictive-Wakeup MAC Protocol for Wireless Sensor Networks.” In The 30th IEEE International Conference on Computer Communications (INFOCOM), 1305–1313. Shanghai, China: IEEE.

    Google Scholar 

  • Texas Instruments. 2007. CC1000: Single Chip Very Low Power RF Transceiver. Texas Instruments. http://www.ti.com/lit/ds/symlink/cc1000.pdf. Accessed 23 Dec 2013.

  • Texas Instruments. January 1, 2005. CC1100: Low-Cost Low-Power Sub-1 GHz RF Transceiver. Texas Instruments. http://datasheet.octopart.com/CC1100RTKR-Texas-Instruments-datasheet-10422951.pdf. Accessed 3 Feb 2014.

  • Texas Instruments. August 1, 2004. MSP430x11x2, MSP430x12x2 Mixed Signal Microcontroller. Texas Instruments, Inc. http://www.ti.com/lit/ds/symlink/msp430f1122.pdf. Accessed 8 Oct 2016.

  • TinyOS. August 20, 2012. TinyOS. http://www.tinyos.net. Accessed 9 Oct 2013.

  • Tseng, Y.-C., C.-S. Hsu, and C.-S. Hsu. 2003. “Power-Saving Protocols for IEEE 802.11-Based Multi-Hop Ad Hoc Networks.” Computer Networks 43 (3): 317–337.

    Article  MATH  Google Scholar 

  • Ungjin, J., L. Sunggu, and S. Yoo. 2012. “Optimal Wake-Up Scheduling of Data Gathering Trees for Wireless Sensor Networks.” Journal of Parallel and Distributed Computing 72 (4): 536–546.

    Article  MATH  Google Scholar 

  • Van Dam, T., and K. Langendoen. 2003. “An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks.” In The 1st International Conference on Embedded Networked Sensor Systems (SenSys), 171–180. Los Angeles, CA: ACM.

    Google Scholar 

  • van Hoesel, L.F.W., and P.J.M. Havinga. 2004. “A Lightweight Medium Access Protocol (LMAC) for Wireless Sensor Networks: Reducing Preamble Transmissions and Transceiver State Switches.” In The 1st International Workshop on Networked Sensing Systems (INSS), 205–208. Tokyo, Japan: Society of Instrument and Control Engineers (SICE).

    Google Scholar 

  • Vasudevan, S., J. Kurose, and D. Towsley. 2005. “On Neighbor Discovery in Wireless Networks with Directional Antennas.” In The 24th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 2502–2512. Miami, FL: IEEE.

    Google Scholar 

  • Vigorito, C.M., D. Ganesan, and A.G. Barto. 2007. “Adaptive Control of Duty Cycling in Energy-Harvesting Wireless Sensor Networks.” In The 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, 21–30. San Diego, CA: IEEE.

    Google Scholar 

  • Want, R. 2006. “An Introduction to RFID Technology.” Pervasive Computing 5 (1): 25–33.

    Article  Google Scholar 

  • Warrier, A., S. Park, J. Min, and I. Rhee. 2007. “How Much Energy Saving Does Topology Control Offer for Wireless Sensor Networks?—A Practical Study.” Computer Communications 30 (14/15): 2867–2879.

    Article  Google Scholar 

  • Woo, A., T. Tong, and D. Culler. 2003. “Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks. In The 1st International Conference on Embedded Networked Sensor Systems (SenSys), 14–27. Los Angeles, CA: ACM.

    Google Scholar 

  • Xiao, Y., and J. Rosdahl. 2002. “Throughput and Delay Limits of IEEE 802.11.” Communications Letters 6 (8): 355–357.

    Google Scholar 

  • Xu, Y., J. Heidemann, and D. Estrin. 2000. Adaptive Energy-Conserving Routing for Multihop Ad Hoc Networks. Marina del Rey, CA: Information Sciences Institute, University of Southern California.

    Google Scholar 

  • Xu, Y., J. Heidemann, and D. Estrin. 2001. “Geography-Informed Energy Conservation for Ad Hoc Routing.” In The 7th Annual International Conference on Mobile Computing and Networking (MobiCom), 70–84. Rome, Italy: ACM.

    Google Scholar 

  • Xu, Y., S. Bien, Y. Mori, J. Heidemann, and D. Estrin. 2003. Topology Control Protocols to Conserve Energy in Wireless Ad Hoc Networks. Los Angeles, CA: Technical, Center for Embedded Network Sensing (CENS), University of California.

    Google Scholar 

  • Yang, X., and N.H. Vaidya. 2004. “A Wakeup Scheme for Sensor Networks: Achieving Balance Between Energy Saving and End-To-End Delay.” In The 10th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), 19–26. Toronto, Canada: IEEE.

    Google Scholar 

  • Ye, W., and J. Heidemann. 2004. “Medium Access Control in Wireless Sensor Networks.” In Wireless Sensor Networks, ed. C.S. Raghavendra, K.M. Sivalingam, and T. Znati, 73–91. Boston, MA: Springer.

    Google Scholar 

  • Ye, W., J. Heidemann, and D. Estrin. 2002a. A Flexible and Reliable Radio Communication Stack on Motes. USC/ISI Technical Report ISI-TR-565. Los Angeles, CA: Information Sciences Institute, University of Southern California.

    Google Scholar 

  • Ye, W., J. Heidemann, and D. Estrin. 2002b. “An Energy-Efficient MAC Protocol for Wireless Sensor Networks.” In The 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 1567–1576. New York, NY: IEEE.

    Google Scholar 

  • Ye, W., J. Heidemann, and D. Estrin. 2004. “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks.” IEEE/ACM Transactions on Networking 12 (3): 493–506.

    Article  Google Scholar 

  • Zheng, R., J.C. Hou, and L. Sha. 2003. “Asynchronous Wakeup for Ad Hoc Networks.” In The 4th ACM International Symposium on Mobile Ad hoc Networking and Computing (MobiHoc), 35–45. Annapolis, MD: ACM SIGMOBILE.

    Google Scholar 

  • Zheng, T., S. Radhakrishnan, and V. Sarangan. 2005. “PMAC: An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks.” In 19th IEEE International Parallel and Distributed Processing Symposium. Denver, CO: IEEE.

    Google Scholar 

  • Zheng, T., S. Radhakrishnan, and V. Sarangan. 2012. “A Switch Agent for Wireless Sensor Nodes with Dual Interfaces: Implementation and Evaluation.” Tsinghua Science and Technology 17 (5): 586–598.

    Article  Google Scholar 

  • Zhou, G., T. He, S. Krishnamurthy, and J.A. Stankovic. 2004. “Impact of Radio Irregularity on Wireless Sensor Networks.” In The 2nd International Conference on Mobile Systems, Applications, and Services (MobiSys), 125–138. Boston, MA: ACM.

    Google Scholar 

  • Zorzi, M., and R.R. Rao. 2003a. “Geographic Random Forwarding (Geraf) for Ad Hoc and Sensor Networks: Energy and Latency Performance.” Transactions on Mobile Computing 2 (4): 349–365.

    Article  Google Scholar 

  • Zorzi, M., and R.R. Rao. 2003b. “Geographic Random Forwarding (Geraf) for Ad Hoc and Sensor Networks: Multihop Performance.” Transactions on Mobile Computing 2 (4): 337–348.

    Article  Google Scholar 

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  1. Department of Computer Engineering and Systems, Ain Shams University, Cairo, Egypt

    Prof. Hossam Mahmoud Ahmad Fahmy

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Fahmy, H. (2020). Energy Management Techniques for WSNs (1): Duty-Cycling Approach. In: Wireless Sensor Networks. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-29700-8_4

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