access icon free Algorithm for energy consumption minimisation in wireless sensor network

© The Institution of Engineering and Technology
Received 01/05/2019, Accepted 14/02/2020, Revised 22/11/2019, Published 20/02/2020

Wireless sensor network (WSN) consists of spatially distributed miniature size and autonomous nodes along with batteries as a power source. The major bottleneck of WSN is efficient energy utilization. The energy consumption for transmission of signals increases with the distance. This problem of energy consumption is addressed in this study. This study presents a strategy, namely distance-based dynamic duty-cycle allocation (DBDDCA) algorithm. In DBDDCA, longer distance nodes from cluster head (CH) transmit relatively less time in order to save energy. Conversely, transmit for the higher time when the distance is near to CH. The proposed DBDDCA is compared with the other existing strategies: low-energy adaptive cluster hierarchy (LEACH), modified leach, and stable election protocol and with two existing medium access control (MAC) protocols: sensor (S)-MAC and timeout (T)-MAC. The performance of the proposed and existing strategies is evaluated with the following network parameters: energy consumption, network energy utilization, network lifetime, latency, and packets delivery. These parameters have been evaluated with different network scenarios such as number of nodes increases, number of rounds, and with variation in initial energy of nodes. Simulation results show the performance of the proposed strategy is significantly better than the existing strategies under the investigated network parameters.

Inspec keywords: access protocols; wireless sensor networks; minimisation; pattern clustering; energy consumption; telecommunication power management; energy conservation; routing protocols

Other keywords: network energy utilisation; disaster management; wireless sensor network; unmanned aerial vehicle; cluster head; T-MAC protocols; environmental monitoring; energy consumption minimisation algorithm; distance-based dynamic duty-cycle allocation algorithm; CH; healthcare monitoring; medium access control protocols; WSN; S-MAC protocols; network lifetime; low-energy adaptive cluster hierarchy protocols; DBDDCA; LEACH protocols; energy consumption; stable election protocol

Subjects: Wireless sensor networks; Energy conservation; Protocols; Optimisation techniques; Telecommunication systems (energy utilisation); Communication network design, planning and routing

References

    1. 1)
      • 18. Hawbani, A., Wang, X., Sharabi, Y., et al: ‘LORA: load-balanced opportunistic routing for asynchronous duty-cycled WSN’, IEEE Trans. Mob. Comput., 2019, 8, (7), pp. 1601–1615.
    2. 2)
      • 27. Ling, Z., Hu, F., Shao, M.: ‘The optimal control policy for point-to-point wireless body area network based on simultaneous time-ratio and transmission power allocation’, IEEE Access, 2019, 7, pp. 46454–46460.
    3. 3)
      • 25. Islam, M.M., Matin, M.A., Mondol, T. K.: ‘Extended stable election protocol (SEP) for three-level hierarchical clustered heterogeneous WSN’. IET Conf. Wireless Sensor Systems (WSS 2012), London, 2012, pp. 1–4.
    4. 4)
      • 30. Khiati, M., Djenouri, D.: ‘BOD-LEACH: broadcasting over duty-cycled radio using LEACH clustering for delay/power efficient dissimilation in wireless sensor network’, Int. J. Commun. Syst. Archit., 2015, 28, (2), pp. 296–308.
    5. 5)
      • 6. Jurdak, R., Baldi, P., Videira Lopes, C.: ‘Adaptive low-power listening for wireless sensor networks’, IEEE Trans. Mob. Comput., 2007, 6, (8), pp. 988–1004.
    6. 6)
      • 36. Niafar, S., Shahhoseini, S.: ‘A new sink-based energy efficient and delay-sensitive MAC protocol for large-scale WSNs’. Proc. Int. Symp. Performance Evaluation Computer Telecommunication Systems (SPECTS), Istanbul, Turkey, 2009, vol. 41, pp. 178–184.
    7. 7)
      • 2. Sheng, Z., Yang, S., Yu, Y., et al: ‘A survey on the IETF protocol suite for the Internet of things: standards, challenges, and opportunities’, IEEE Wirel. Commun., 2013, 20, (6), pp. 91–98.
    8. 8)
      • 44. Gupta, N., Gupta, H., Yadav, R.: ‘Life time enhancement of sensor network by using concept of SEP & LEACH (LEACH-P)’. Second Int. Conf. Advances in Computing and Communication Engineering, Dehradun, 2015, pp. 198–201.
    9. 9)
      • 12. Sung, S., Kang, H., Kim, E., et al: ‘Energy consumption analysis of S-MAC protocol in single-hop wireless sensor networks’. Asia-Pacific Conf. Communications, Busan, South Korea, 2006, pp. 1–5.
    10. 10)
      • 5. Zheng, T., Radhakrishnan, S., Sarangan, V.: ‘PMAC: an adaptive energy-efficient MAC protocol for wireless sensor networks’. Proc. IPDPS 05, Denver, CO, USA, 2005, p. 237.
    11. 11)
      • 38. Kumar, A., Zhao, M., Wong, K.Y., et al: ‘A comprehensive study of IoT and WSN MAC protocols: research issues, challenges and opportunities’, IEEE Access, 2018, 6, pp. 76228–76262.
    12. 12)
      • 14. Hasan, N.U., Ejaz, W., Lee, S., et al: ‘Knapsack-based energy-efficient node selection scheme for cooperative spectrum sensing in cognitive radio sensor networks’, IET Commun., 2012, 6, (17), pp. 2998–3005.
    13. 13)
      • 9. Ye, W., Heidemann, J., Estrin, D.: ‘An energy-efficient MAC protocol for wireless sensor networks’. INFOCOM 2002 21st Annual Joint Conf. IEEE Computer and Communications Societies Proc. IEEE, New York, NY, USA, 2002, vol. 3, pp. 1567–1576.
    14. 14)
      • 31. van Dam, T., Langendoen, K.: ‘An adaptive energy-efficient MAC protocol for wireless sensor networks’. First ACM Conf. Embedded Networked Sensor Systems (SenSys), New York, NY, USA, November 2003.
    15. 15)
      • 41. Heinzelman, W.B.: ‘An application-specific protocol architecture for wireless microsensor networks’, IEEE Trans. Wirel. Commun., 2002, 1, (4), pp. 660–670.
    16. 16)
      • 16. Carlier, M., García Algora, C.M., Braeken, A., et al: ‘Analysis of Internet protocol-based multicast on duty-cycled wireless sensor networks’, IEEE Sens. J., 2018, 18, (10), pp. 4317–4327.
    17. 17)
      • 11. Pei, G., Chien, C: ‘Low-power TDMA in large wireless sensor networks’. Military Communications Conf. 2001 (MILCOM 2001) Communications for Network-Centric Operations: Creating the Information Force, McLean, VA, USA, 2001, vol. 1, pp. 347–351.
    18. 18)
      • 33. Suh, C., Ko, Y.-B.: ‘A traffic aware, energy-efficient MAC protocol for wireless sensor networks’. IEEE Int. Symp. Circuits Systems (ISCAS), Kobe, Japan, May 2005.
    19. 19)
      • 17. Cheng, L., Niu, J., Gu, Y., et al: ‘Achieving efficient reliable flooding in low-duty-cycle wireless sensor networks’, IEEE/ACM Trans. Netw., 2016, 24, (6), pp. 3676–3689.
    20. 20)
      • 13. Ye, W., Heidemann, J., Estrin, J.: ‘Medium access control with coordinated adaptive sleeping for wireless sensor networks’, IEEE/ACM Trans. Netw., 2004, 12, (3), pp. 493–506.
    21. 21)
      • 28. Pau, G., Salerno, V.M.: ‘Wireless sensor networks for smart homes: a fuzzy-based solution for an energy-effective duty cycle’, Electronics (Basel), 2019, 8, p. 131.
    22. 22)
      • 4. Othman, S.B., Bahattab, A.A., Trad, A., et al: ‘Confidentiality and integrity for data aggregation in WSN using holomorphic encryption’, Wirel. Pers. Commun., 2015, 80, (2), pp. 867–889.
    23. 23)
      • 32. Lu, G., Krishnamachari, B., Raghavendra, C.S.: ‘An adaptive energy efficient and low-latency MAC for data gathering in wireless sensor networks’. Workshop Energy-Efficient Wireless Communications and Networks (EWCN), Santa Fe, NM, USA, April 2004.
    24. 24)
      • 42. Singh, K.: ‘WSN LEACH-based protocols: a structural analysis’. Int. Conf. Workshop on Computing and Communication (IEMCON), Vancouver, BC, Canada, 2015, pp. 1–7.
    25. 25)
      • 1. Salim, A., Osamy, W., Khedr, A.: ‘IBLEACH: intra-balanced LEACH protocol for wireless sensor networks’, Wirel. Netw., 2014, 20, (6), pp. 1515–1525.
    26. 26)
      • 10. Buettner, M., Yee, G.V., Anderson, E., et al: ‘X-MAC: a short preamble MAC protocol for duty-cycled wireless sensor networks’. Proc. Fourth Int. Conf. Embedded Networked Sensor Systems, New York, USA, 2006, pp. 307–320.
    27. 27)
      • 39. Du, S., Saha, A.K., Johnson, D.B.: ‘RMAC: a routing-enhanced duty-cycle MAC protocol for wireless sensor networks’. 26th IEEE Int. Conf. Computer Communications (INFOCOM), Barcelona, Spain, May 2007.
    28. 28)
      • 15. Li, F., Li, W., Meng, L., et al: ‘Time-pattern design for transmission energy allocation in wireless sensor networks’, IET Commun., 2017, 11, (7), pp. 1028–1035.
    29. 29)
      • 43. Ihsan, A., Saghar, K., Fatima, T., et al: ‘Formal comparison of LEACH and its extensions’, Comput. Stand. Interfaces, 2019, 62, pp. 119–127.
    30. 30)
      • 22. Mahmood, D., Javaid, N., Mahmood, S., et al: ‘MODLEACH: a variant of LEACH for WSNs’, broadband and wireless computing, communication and applications (BWCCA)’. Eighth Int. Conf. Broadband and Wireless Computing, Communication and Applications, Compiegne, 2013, pp. 158–163.
    31. 31)
      • 8. Miller, M.J., Vaidya, N.H.: ‘Power save mechanisms for multi-hop wireless networks’. Proc. First Int. Conf. Broadband Networks, Washington, D.C., USA, 2004, pp. 518–526.
    32. 32)
      • 20. He, H., Xu, Z., Yang, L.: ‘Delay-aware data collecting protocol for low-duty-cycle wireless sensor networks’, IET Netw., 2018, 7, (1), pp. 44–49.
    33. 33)
      • 40. Hefeida, M.S., Canli, T., Khokhar, A.: ‘CL-MAC: a cross-layer MAC protocol for heterogeneous wireless sensor networks’, Ad Hoc Netw., 2013, 11, (1), pp. 213–225.
    34. 34)
      • 24. Ayoob, M., Zhen, Q., Adnan, S., et al: ‘Research of improvement on LEACH and SEP routing protocols in wireless sensor networks’. IEEE Int. Conf. Control and Robotics Engineering (ICCRE), Singapore, 2016, pp. 1–5.
    35. 35)
      • 23. Dhehibi, H., Zouinkhi, A., Kanoun, O., et al: ‘An enhancement of MOD-LEACH protocol for wireless sensor network’. 14th Int. Multi-Conf. Systems, Signals & Devices (SSD), Marrakech, 2017, pp. 744–749.
    36. 36)
      • 29. Jain, N.K., Verma, A.: ‘Relay node selection in wireless sensor network using fuzzy inference system’, J. Commun., 2019, 14, (6), pp. 423–431.
    37. 37)
      • 35. Yadav, R., Varma, S., Malaviya, N.: ‘Optimized medium access control for wireless sensor network’, Int. J. Comput. Sci. Netw. Secur., 2008, 8, pp. 334–338.
    38. 38)
      • 37. Tanmoy, M., Sarbani, R.: ‘A comparative study on popular MAC protocols for mixed wireless sensor networks: from an implementation viewpoint’, Comput. Sci. Rev., 2016, 22, pp. 107–134.
    39. 39)
      • 3. Jain, N.K., Yadav, D.S., Verma, A.: ‘A fuzzy decision scheme for relay selection in cooperative wireless sensor network’, Int. J. Commun. Syst., 2019, 32, (16), p. e4121.
    40. 40)
      • 19. Chen, Q., Gao, H., Cai, Z., et al: ‘Distributed low-latency data aggregation for duty-cycle wireless sensor networks’, IEEE/ACM Trans. Netw., 2018, 26, (5), pp. 2347–2360.
    41. 41)
      • 7. Medidi, M., Zhou, Y.: ‘Extending lifetime with differential duty cycles in wireless sensor networks’. Proc. Globecom 07, Washington, DC, USA, 2007.
    42. 42)
      • 34. Nam, Y., Lee, H., Jung, H., et al: ‘An adaptive MAC (A-MAC) protocol guaranteeing network lifetime for wireless sensor networks’, Comput. Commun., 2007, 30, (13), pp. 1–7.
    43. 43)
      • 21. Zhang, Y., Li, W.W.: ‘Energy consumption analysis of a duty-cycle wireless sensor network model’, IEEE Access, 2019, 7, pp. 33405–33413.
    44. 44)
      • 26. Pak, W., Choi, J.G., Bahk, S.: ‘Duty-cycle allocation to maximize network lifetime of wireless sensor networks with delay constraints’, Wirel. Commun. Mob. Comput., 2014, 14, (6), pp. 613–628.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2019.0465
Loading

Related content

content/journals/10.1049/iet-com.2019.0465
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading