Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Multi-hop decision gathering scheme for target-detection wireless sensor networks

© The Institution of Engineering and Technology
Received 04/02/2019, Accepted 27/08/2019, Revised 05/08/2019, Published 29/08/2019

Most of the energy consumed in target-detection wireless sensor networks (WSNs) is due to the decision gathering process. As such, several energy-efficient decision gathering schemes have been proposed to improve energy efficiency. In this study, a new multi-hop decision gathering scheme for target-detection WSNs is presented. The proposed scheme creates paths to gather the nodes' decisions, where each path includes a set of nodes. Nodes in the same path cooperate to deliver their decisions by using multi-hop transmissions. At each hop, the relay node combines the received decisions with its own decision and uses a higher modulation order to forward them to the next node in the path. Two different setup scenarios are considered to evaluate the proposed scheme, namely, fixed transmit power scenario and fixed bit error rate scenario. In the former scenario, results demonstrate that the proposed scheme achieves better error rate at short hop distances when compared to the conventional single hop scheme. On the other hand, results of the fixed bit error rate scenario show that a significant amount of the saved power can be attained by the proposed scheme with a slight loss in the decision error rate.

Inspec keywords: error statistics; telecommunication power management; energy conservation; object detection; wireless sensor networks; decision theory

Other keywords: decision error rate; fixed bit error rate scenario; target-detection wireless sensor networks; energy efficiency; fixed transmit power scenario; target-detection WSN; single hop scheme; multihop transmissions; multihop decision gathering scheme

Subjects: Game theory; Telecommunication systems (energy utilisation); Wireless sensor networks; Probability theory, stochastic processes, and statistics; Signal detection

References

    1. 1)
      • 40. Sefuba, M., Walingo, T.: ‘Energy-efficient medium access control and routing protocol for multihop wireless sensor networks’, IET Wirel. Sens. Syst., 2018, 8, (3), pp. 99–108.
    2. 2)
      • 22. Zhao, Z., Zhang, B., Zheng, J., et al: ‘Providing scalable location service in wireless sensor networks with mobile sinks’, IET Commun., 2009, 3, (10), pp. 1628–1637.
    3. 3)
      • 39. El Monser, M., Chikha, H.B., Attia, R.: ‘Prolonging the lifetime of large-scale wireless sensor networks using distributed cooperative transmissions’, IET Wirel. Sens. Syst., 2018, 8, (5), pp. 229–236.
    4. 4)
      • 32. Kim, D., Kim, J., Kim, K.H.: ‘An energy-efficient data gathering technique using multiple paths in wireless sensor networks’. IEEE Consumer Communications and Networking Conf. (CCNC), Las Vegas, NV, USA, 2006, pp. 346–350.
    5. 5)
      • 9. Ma, X.-P., Dong, H.-H., Li, P., et al: ‘Adaptive optimization of multi-hop communication protocol for linear wireless monitoring networks on high-speed railways’, IEEE Trans. Intell. Transp. Syst., 2019, 20, (6), pp. 2313–2327.
    6. 6)
      • 6. Ebrahimi, D., Sharafeddine, S., Ho, P., et al: ‘UAV-aided projection-based compressive data gathering in wireless sensor networks’, IEEE Internet Things J., 2019, 6, (2), pp. 1893–1905.
    7. 7)
      • 12. Wang, Y., Chen, K.: ‘Efficient path planning for a mobile sink to reliably gather data from sensors with diverse sensing rates and limited buffers’, IEEE Trans. Mob. Comput., 2019, 18, (7), pp. 1527–1540.
    8. 8)
      • 24. Gao, Y., Li, X., Li, J., et al: ‘Distributed and efficient minimum-latency data aggregation scheduling for multi-channel wireless sensor networks’, IEEE Internet Things J., doi: 10.1109/JIOT.2019.2919639.
    9. 9)
      • 18. Jiang, Y., Zhang, L., Liu, J., et al: ‘The path planning of mobile sink based on wolf pack algorithm’. 2019 Int. Conf. on Intelligent Transportation, Big Data & Smart City (ICITBS), Changsha, China, 2019, pp. 147–150.
    10. 10)
      • 11. Lu, Y., Sun, N., Pan, X., et al: ‘Mobile sink-based path optimization strategy in wireless sensor networks using artificial bee colony algorithm’, IEEE Access, 2019, 7, pp. 11668–11678.
    11. 11)
      • 7. Jain, N., Bohara, V.A., Gupta, A.: ‘iDEG: integrated data and energy gathering framework for practical wireless sensor networks using compressive sensing’, IEEE Sens. J., 2019, 19, (3), pp. 1040–1051.
    12. 12)
      • 33. Ren, F., Zhang, J., He, T., et al: ‘EBRP: energy-balanced routing protocol for data gathering in wireless sensor networks’, IEEE Trans. Parallel Distrib. Syst., 2011, 22, (12), pp. 2108–2125.
    13. 13)
      • 13. Gu, X., Zhou, X., Yuan, B., et al: ‘A Bayesian compressive data gathering scheme in wireless sensor networks with one mobile sink’, IEEE Access, 2018, 6, pp. 47897–47910.
    14. 14)
      • 42. Lin, H., Üster, H.: ‘Exact and heuristic algorithms for data-gathering cluster-based wireless sensor network design problem’, IEEE/ACM Trans. Netw., 2014, 22, (3), pp. 903–916.
    15. 15)
      • 48. Zhang, D., Ge, H., Zhang, T., et al: ‘New multi-hop clustering algorithm for vehicular ad hoc networks’, IEEE Trans. Intell. Transp. Syst., 2019, 20, (4), pp. 1517–1530.
    16. 16)
      • 4. Li, J., Liu, W., Wang, T., et al: ‘Battery-friendly relay selection scheme for prolonging the lifetimes of sensor nodes in the internet of things’, IEEE Access, 2019, 7, pp. 33180–33201.
    17. 17)
      • 8. Fariborzi, H., Moghavvemi, M.: ‘EAMTR: energy aware multi-tree routing for wireless sensor networks’, IET Commun., 2009, 3, (5), pp. 733–739.
    18. 18)
      • 15. Sha, C., Song, D., Yang, R., et al: ‘A type of energy-balanced tree based data collection strategy for sensor network with mobile sink’, IEEE Access, 2019, 7, pp. 85226–85240.
    19. 19)
      • 25. Santi, P.: ‘On the data gathering capacity and latency in wireless sensor networks’, IEEE J. Sel. Areas Commun., 2010, 28, (7), pp. 1211–1221.
    20. 20)
      • 28. Kim, E., Shon, T., Park, J.J.H., et al: ‘Latency bounded and energy efficient MAC for wireless sensor networks’, IET Commun., 2012, 6, (14), pp. 2120–2127.
    21. 21)
      • 34. Yu, Y., Prasanna, V.K., Krishnamachari, B.: ‘Energy minimization for real-time data gathering in wireless sensor networks’, IEEE Trans. Wirel. Commun., 2006, 5, (11), pp. 3087–3096.
    22. 22)
      • 50. Khan, F.A., Khan, M., Asif, M., et al: ‘Hybrid and multi-hop advanced zonal-stable election protocol for wireless sensor networks’, IEEE Access, 2019, 7, pp. 25334–25346.
    23. 23)
      • 10. Qadori, H.Q., Zukarnain, Z.A., Hanapi, Z.M., et al: ‘FuMAM: fuzzy-based mobile agent migration approach for data gathering in wireless sensor networks’, IEEE Access, 2018, 6, pp. 15643–15652.
    24. 24)
      • 35. He, S., Chen, J., Yau, D.K.Y., et al: ‘Cross-layer optimization of correlated data gathering in wireless sensor networks’, IEEE Trans. Mob. Comput., 2012, 11, (11), pp. 1678–1691.
    25. 25)
      • 52. Althunibat, S., Abu-Al-Aish, A., Abu Shehab, W.F., et al: ‘Auction-based data gathering scheme for wireless sensor networks’, IEEE Commun. Lett., 2016, 20, (6), pp. 1223–1226.
    26. 26)
      • 49. Olawole, A.A., Takawira, F., Oyerinde, O.O., et al: ‘Fusion rule and cluster head selection scheme in cooperative spectrum sensing’, IET Commun., 2019, 13, (6), pp. 758–765.
    27. 27)
      • 2. Zhu, Y., Li, E., Chi, K., et al: ‘Designing prefix code to save energy for wirelessly powered wireless sensor networks’, IET Commun., 2018, 12, (17), pp. 2137–2144.
    28. 28)
      • 46. Nguyen Quoc, D., Bi, L., Wu, Y., et al: ‘Energy efficiency clustering based on Gaussian network for wireless sensor network’, IET Commun., 2019, 13, (6), pp. 741–747.
    29. 29)
      • 44. Behera, T.M., Mohapatra, S.K., Samal, U.C., et al: ‘Residual energy-based cluster-head selection in WSNs for IoT application’, IEEE Internet Things J., 2019, 6, (3), pp. 5132–5139.
    30. 30)
      • 51. Rashid, A., Tripathi, Y., Prakash, A., et al: ‘Load aware energy-balanced data gathering approach in CRSNs’, IET Wirel. Sens. Syst., 2019, 9, (3), pp. 143–150.
    31. 31)
      • 21. Zhao, M., Yang, Y.: ‘Optimization-based distributed algorithms for mobile data gathering in wireless sensor networks’, IEEE Trans. Mob. Comput., 2012, 11, (10), pp. 1464–1477.
    32. 32)
      • 19. Wang, T., Li, Y., Wang, G., et al: ‘Sustainable and efficient data collection from WSNs to cloud’, IEEE Trans. Sustain. Comput., 2019, 4, (2), pp. 252–262.
    33. 33)
      • 3. Zhang, Y., Zhu, Y., Yan, F., et al: ‘Energy-efficient radio resource allocation in software-defined wireless sensor networks’, IET Commun., 2018, 12, (3), pp. 349–358.
    34. 34)
      • 30. Kumar, S., Chaurasiya, V.K.: ‘A strategy for elimination of data redundancy in internet of things (IoT) based wireless sensor network (WSN)’, IEEE Syst. J., 2019, 13, (2), pp. 1650–1657.
    35. 35)
      • 45. Althunibat, S., Mesleh, R.: ‘Index modulation for cluster-based wireless sensor networks’, IEEE Trans. Veh. Technol., 2018, 67, (8), pp. 6943–6950.
    36. 36)
      • 31. Liu, X., Qiu, T., Wang, T.: ‘Load-balanced data dissemination for wireless sensor networks: a nature-inspired approach’, IEEE Internet Things J., doi: 10.1109/JIOT.2019.2900763.
    37. 37)
      • 36. Weng, H., Chen, Y., Wu, E.H., et al: ‘Correlated data gathering with double trees in wireless sensor networks’, IEEE Sens. J., 2012, 12, (5), pp. 1147–1156.
    38. 38)
      • 1. Shorey, R., Ananda, A., Chan, M.C., et al: ‘Field gathering wireless sensor networks’ in ‘Mobile, wireless, and sensor networks: technology, applications and future directions’ (John Wiley & Sons, Inc., Hoboken, New Jersey, 2006).
    39. 39)
      • 38. Lambor, S.M. and, Sangeeta, M.J.: ‘Optimal hops for minimal route power under SINR constraints in wireless sensor networks’, IET Wirel. Sens. Syst., 2018, 8, (4), pp. 176–182.
    40. 40)
      • 14. Cheng, C., Yu, C.: ‘Mobile data gathering with bounded relay in wireless sensor networks’, IEEE Internet Things J., 2018, 5, (5), pp. 3891–3907.
    41. 41)
      • 27. Barani, H., Jaradat, Y., Huang, H., et al: ‘Effect of sink location and redundancy on multi-sink wireless sensor networks: a capacity and delay analysis’, IET Commun., 2018, 12, (8), pp. 941–947.
    42. 42)
      • 26. Gong, D., Yang, Y.: ‘Low-latency SINR-based data gathering in wireless sensor networks’, IEEE Trans. Wirel. Commun., 2014, 13, (6), pp. 3207–3221.
    43. 43)
      • 16. Lin, L., Yan, S., Nian, Y.: ‘A load balancing data gathering scheme in wireless sensor networks with mobile sinks’. 2010 6th Int. Conf. on Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, 2010, pp. 1–4.
    44. 44)
      • 47. Ogundile, O., Balogun, M.B., Ijiga, O.E., et al: ‘Energy-balanced and energy-efficient clustering routing protocol for wireless sensor networks’, IET Commun., 2019, 13, (10), pp. 1449–1457.
    45. 45)
      • 43. Chang, B., Zhang, X.: ‘An energy-efficient cluster-based data gathering protocol for wireless sensor networks’. 6th Int. Conf. on Wireless Communications Networking and Mobile Computing (WiCOM), Chengdu, 2010, pp. 1–5.
    46. 46)
      • 23. Guo, S., Wang, C., Yang, Y.: ‘Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks’, IEEE Trans. Mob. Comput., 2014, 13, (12), pp. 2836–2852.
    47. 47)
      • 41. Liu, Y., Xiong, N., Zhao, Y., et al: ‘Multi-layer clustering routing algorithm for wireless vehicular sensor networks’, IET Commun., 2010, 4, (7), pp. 810–816.
    48. 48)
      • 29. Zhang, J., Hu, P., Long, J.: ‘A hybrid transmission based data collection scheme with delay and reliability guaranteed for lossy WSNs’, IEEE Access, 2019, 7, pp. 70474–70485.
    49. 49)
      • 17. Cheng, C., Yu, C.: ‘Data gathering in wireless sensor networks: a combine–TSP–reduce approach’, IEEE Trans. Veh. Technol., 2016, 65, (4), pp. 2309–2324.
    50. 50)
      • 5. Dezfuli, N.N., Barati, H.: ‘Distributed energy efficient algorithm for ensuring coverage of wireless sensor networks’, IET Commun., 2019, 13, (5), pp. 578–584.
    51. 51)
      • 37. Chang, B., Zhang, X.: ‘An energy-efficient routing algorithm for data gathering in wireless sensor networks’. Cross Strait Quad-Regional Radio Science and Wireless Technology Conf. (CSQRWC 2012), New Taipei City, 2012, pp. 137–141.
    52. 52)
      • 20. Zhao, M., Gong, D., Yang, Y.: ‘Network cost minimization for mobile data gathering in wireless sensor networks’, IEEE Trans. Commun., 2015, 63, (11), pp. 4418–4432.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2019.0137
Loading

Related content

content/journals/10.1049/iet-com.2019.0137
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address