[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Solutions for energy hole problem in wireless sensor networks (WSNs) have been excessively explored using mobile sink (MS). Although, MS provides a considerable amount of energy saving and extends network lifetime. However, MS introduces varying degree of data acquisition latency depending on the trajectory followed. Therefore, rendezvous based data acquisition methods are proposed to mitigate this issue which are aimed to provide a trade-off between energy consumption and data acquisition latency. There exists a list of surveys that focus on issues related to sink mobility such as mobility aware energy efficient data acquisition schemes, mobility aware data acquisition and routing, etc. However, none of these surveys concern about the issue of providing a trade-off between energy consumption and data acquisition latency. Therefore, this review addresses the same issue and presents a taxonomy of rendezvous based data acquisition methods along with the design goals and associated designing requirements. The methods are grouped into two categories: rendezvous point (RP) based and rendezvous area (RA) based. Furthermore, a phase-wise comprehensive overview of these methods is provided which clearly unfold the way of resolving the targeted issue. Finally, the research issues and challenges are discussed in pursuit of data acquisition by MS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Kumar, D. P., Tarachand, A., & Rao, A. C. S. (2018). ACO-based mobile sink path determination for wireless sensor networks under non-uniform data constraints. Applied Soft Computing, 69, 528–540.

    Article  Google Scholar 

  2. Filippini, D. (2012). Autonomous sensor networks: Collective sensing strategies for analytical purposes. Berlin: Springer.

    Google Scholar 

  3. Anisi, M. H., Abdul-Salaam, G., Idris, M. Y. I., Wahab, A. W. A., & Ahmedy, I. (2017). Energy harvesting and battery power based routing in wireless sensor networks. Wireless Networks, 23(1), 249–266.

    Article  Google Scholar 

  4. Guerroumi, M., Badache, N., & Moussaoui, S. (2015). Mobile sink and power management for efficient data dissemination in wireless sensor networks. Telecommunication Systems, 58(4), 279–292.

    Article  Google Scholar 

  5. Yadav, S., & Yadav, R. S. (2016). A review on energy efficient protocols in wireless sensor networks. Wireless Networks, 22(1), 335–350.

    Article  Google Scholar 

  6. Chong, C.-Y., & Kumar, S. P. (2003). Sensor networks: Evolution, opportunities, and challenges. Proceedings of the IEEE, 91(8), 1247–1256.

    Article  Google Scholar 

  7. Molina-Pico, A., Cuesta-Frau, D., & Araujo, A. (2016). Forest monitoring and wildland early fire detection by a hierarchical wireless sensor network. Journal of Sensors, 2016, 1–8.

    Article  Google Scholar 

  8. Ghosh, K., Neogy, S., Das, P. K., & Mehta, M. (2018). Intrusion detection at international borders and large military barracks with multi-sink wireless sensor networks: An energy efficient solution. Wireless Personal Communications, 98(1), 1083–1101.

    Article  Google Scholar 

  9. Bokareva, T., Hu, W., Kanhere, S., Ristic, B., Gordon, N., Bessell, T., Rutten, M., & Jha, S. (2006). Wireless sensor networks for battlefield surveillance. In Proceeding of land warfare conference, Australia (pp. 1–8).

  10. Habibzadeh, H., Qin, Z., Soyata, T., & Kantarci, B. (2017). Large-scale distributed dedicated and non-dedicated smart city sensing systems. IEEE Sensors Journal, 17(23), 7649–7658.

    Article  Google Scholar 

  11. Wu, F., Xu, L., Kumari, S., & Li, X. (2017). An improved and anonymous two-factor authentication protocol for health-care applications with wireless medical sensor networks. Multimedia Systems, 23(2), 195–205.

    Article  Google Scholar 

  12. Nam, W. H., Kim, T., Hong, E.-M., Choi, J.-Y., & Kim, J.-T. (2017). A wireless sensor network (WSN) application for irrigation facilities management based on information and communication technologies (ICTs). Computers and Electronics in Agriculture, 143, 185–192.

    Article  Google Scholar 

  13. Yang, L., Lu, Y.-Z., Zhong, Y.-C., & Yang, S. X. (2018). An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks. Telecommunication Systems, 68(1), 11–26.

    Article  Google Scholar 

  14. Lian, J., Naik, K., & Agnew, G. B. (2006). Data capacity improvement of wireless sensor networks using non-uniform sensor distribution. International Journal of Distributed Sensor Networks, SAGE Journals, 2(2), 121–145.

    Article  Google Scholar 

  15. Jaichandran, R., Irudhayaraj, A. A., & Raja, J. E. (2010). Effective strategies and optimal solutions for hot spot problem in wireless sensor networks (WSN). In Proceedings of 10th international conference on information sciences signal processing and their applications (ISSPA) (pp. 389–392).

  16. Yetgin, H., Cheung, K. T. K., El-Hajjar, M., & Hanzo, L. H. (2017). A survey of network lifetime maximization techniques in wireless sensor networks. IEEE Communications Surveys & Tutorials, 19(2), 828–854.

    Article  Google Scholar 

  17. Long, J., Dong, M., Ota, K., Liu, A., & Hai, S. (2015). Reliability guaranteed efficient data gathering in wireless sensor networks. IEEE Access, 3, 430–444.

    Article  Google Scholar 

  18. Ben-Othman, J., & Yahya, B. (2010). Energy efficient and QoS based routing protocol for wireless sensor networks. Journal of Parallel and Distributed Computing, 70(8), 849857.

    Article  MATH  Google Scholar 

  19. Saleem, M., Ullah, I., & Farooq, M. (2012). Beesensor: An energy efficient and scalable routing protocol for wireless sensor networks. Information Sciences, 200, 38–56.

    Article  Google Scholar 

  20. Kong, L., Pan, J.-S., Snel, V., Tsai, P.-W., & Sung, T.-W. (2018). An energy-aware routing protocol for wireless sensor network based on genetic algorithm. Telecommunication Systems, 67(3), 451–463.

    Article  Google Scholar 

  21. Younis, O., & Fahmy, S. (2004). Heed: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transaction on Mobile Computing, 3(4), 366–379.

    Article  Google Scholar 

  22. Sabet, M., & Naji, H. R. (2015). A decentralized energy efficient hierarchical cluster-based routing algorithm for wireless sensor networks. AEU - International Journal of Electronics and Communications, 69(5), 790–799.

    Article  Google Scholar 

  23. Gherbi, C., Aliouat, Z., & Benmohammed, M. (2016). An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networks. Energy, 114, 647–662.

    Article  Google Scholar 

  24. Zhu, C., Han, G., & Zhang, H. (2017). A honeycomb structure based data gathering scheme with a mobile sink for wireless sensor network. Peer-to-Peer Networking and Applications, 10(3), 484–499.

    Article  Google Scholar 

  25. Shah, R. C., Roy, S., Jain, S., & Brunette, W. (2003). Data mules: Modeling a three-tier architecture for sparse sensor networks. Ad Hoc Networks, 1(2), 215–233.

    Article  Google Scholar 

  26. Chatzigiannakis, I., Kinalis, A., & Nikoletseas, S. (2008). Efficient data propagation strategies in wireless sensor networks using a single mobile sink. Computer Communications, 31(5), 896–914.

    Article  Google Scholar 

  27. Hamida, E. B., & Chelius, G. (2008). Strategies for data dissemination to mobile sinks in wireless sensor networks. IEEE Wireless Communications, 15(6), 31–37.

    Article  Google Scholar 

  28. Rao, J., & Biswas, S. (2010). Network-assisted sink navigation for distributed data gathering: Stability and delay-energy trade-offs. Computer Communication, 33(2), 160–175.

    Article  Google Scholar 

  29. Bhushan, B., & Sahoo, G. (2018). Recent advances in attacks, technical challenges, vulnerabilities and their countermeasures in wireless sensor networks. Wireless Personal Communications, 98(2), 2037–2077.

    Article  Google Scholar 

  30. Zhang, X., Bao, H., Ye, J., Yan, K., & Zhang, H. (2013). A data gathering scheme for WSN/WSAN based on partitioning algorithm and mobile sinks. In Proceedings of 10th IEEE international conference on high performance computing and communications, China (pp. 1968–1973).

  31. Arora, S. (1998). Polynomial time approximation schemes for euclidean traveling salesman and other geometric problems. Journal of ACM, 45(5), 753–782.

    Article  MathSciNet  MATH  Google Scholar 

  32. Alhasanat, A. I., Matrouk, K. D., Alasha’ary, H. A., & Al-Qadi, Z. A. (2014). Connectivity-based data gathering with path-constrained mobile sink in wireless sensor networks. Wireless Sensor Network, 6(6), 118–128.

    Article  Google Scholar 

  33. Lee, E., Park, S., Oh, S., & Kim, S.-H. (2014). Rendezvous-based data dissemination for supporting mobile sinks in multi-hop clustered wireless sensor networks. Wireless Networks, 20(8), 2319–2336.

    Article  Google Scholar 

  34. Jea, D., Somasundara, A., & Srivastava, M. (2005). Multiple controlled mobile elements (data mules) for data collection in sensor networks. In Proceedings of the 1st IEEE international conference on distributed computing in sensor systems, (DCOSS’05), California (pp. 244–257)

  35. Ghosh, A., & Das, S. K. (2008). Coverage and connectivity issues in wireless sensor networks: A survey. Pervasive Mobile Computing, 4(3), 303–334.

    Article  Google Scholar 

  36. Wang, B., Lim, H. B., & Ma, D. (2009). A survey of movement strategies for improving network coverage in wireless sensor networks. Computer Communication, 32(13/14), 1427–1436.

    Article  Google Scholar 

  37. Zhu, C., Zhen, C., Shu, L., & Han, G. (2012). A survey on coverage and connectivity issues in wireless sensor networks. Journal of Network and Computer Applications, 35(2), 619–632.

    Article  Google Scholar 

  38. Anastasi, G., Conti, M., Francesco, M. D., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537568.

    Article  Google Scholar 

  39. Pantazis, N., Nikolidakis, S., & Vergados, D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communication Surveys Tutorials, 15(2), 551–591.

    Article  Google Scholar 

  40. Khan, A. W., Abdullah, A. H., Anisi, M. H., & Bangash, J. I. (2014). A comprehensive study of data collection schemes using mobile sinks in wireless sensor networks. Sensors, 14(2), 2510–2548.

    Article  Google Scholar 

  41. Yu, S., Zhang, B., Li, C., & Mouftah, H. (2014). Routing protocols for wireless sensor networks with mobile sinks: A survey. IEEE Communication Magazine, 52(7), 150–157.

    Article  Google Scholar 

  42. Tunca, C., Isik, S., Donmez, M., & Ersoy, C. (2014). Distributed mobile sink routing for wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 16(2), 877–897.

    Article  Google Scholar 

  43. Ngo, V., & Anpalagan, A. (2010). A detailed review of energy-efficient medium access control protocols for mobile sensor networks. Computers & electrical engineering, 36(2), 383–396.

    Article  MATH  Google Scholar 

  44. Dong, Q., & Dargie, W. (2013). A survey on mobility and mobility-aware MAC protocols in wireless sensor networks. IEEE Communications Surveys & Tutorials, 15(1), 88–100.

    Article  Google Scholar 

  45. Zareei, M., Islam, A. K. M. M., Vargas-Rosales, C., Mansoor, N, Goudarzi, S., & Rehmani, M. H. (2018). Mobility-aware medium access control protocols for wireless sensor networks: A survey. Journal of Network and Computer Application, 104, 21–37.

    Article  Google Scholar 

  46. Halder, S., & Ghosal, A. (2016). A survey on mobile anchor assisted localization techniques in wireless sensor networks. Wireless Networks, 22(7), 2317–2336.

    Article  Google Scholar 

  47. Chelouah, L., Semchedine, F., & Bouallouche-Medjkoune, L. (2017). Localization protocols for mobile wireless sensor networks: A survey. Computers & Electrical Engineering, 71, 733–751. https://doi.org/10.1016/j.compeleceng.2017.03.024.

    Article  Google Scholar 

  48. Gu, Y., Ren, F., Ji, Y., & Li, J. (2015). The evolution of sink mobility management in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 18(1), 507–524.

    Article  Google Scholar 

  49. Hawbani, A., Wang, X., Kuhlani, H., Karmoshi, S., Ghoul, R., Sharabi, Y., et al. (2017). Sink-oriented tree based data dissemination protocol for mobile sinks wireless sensor networks. Wireless Networks, 24, 2723–2734. https://doi.org/10.1007/s11276-017-1497-y.

    Article  Google Scholar 

  50. Wang, C.-F., Shih, J.-D., Pan, B.-H., & Wu, T.-Y. (2014). A network lifetime enhancement method for sink relocation and its analysis in wireless sensor networks. IEEE Sensors Journal, 14(6), 1932–1943.

    Article  Google Scholar 

  51. De, S., Caruso, A., Chaira, T., & Chessa, S. (2006). Bounds on hop distance in greedy routing approach in wireless ad hoc networks. International Journal of Wireless and Mobile Computing, 1(2), 131–140.

    Article  Google Scholar 

  52. Jiang, C., Li, T.-S., Liang, J.-B., & Wu, H. (2017). Low-latency and energy-efficient data preservation mechanism in low-duty-cycle sensor networks. Sensors, 17(5), 1–17.

    Article  Google Scholar 

  53. Pazzi, R. W., Boukerche, A., Grande, R. E. D., & Mokdad, L. (2017). A clustered trail-based data dissemination protocol for improving the lifetime of duty cycle enabled wireless sensor networks. Wireless Network, 23(1), 177–192.

    Article  Google Scholar 

  54. Afsar, M. M., & Tayarani-N, M.-H. (2014). Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications, 46, 198–226.

    Article  Google Scholar 

  55. Rostami, A. S., Badkoobe, M., Mohanna, F., Keshavarz, H., Hosseinabadi, A. A. R., & Sangaiah, A. K. (2018). Survey on clustering in heterogeneous and homogeneous wireless sensor networks. The Journal of Supercomputing, 74(1), 277–323.

    Article  Google Scholar 

  56. Randhawa, S., & Jain, S. (2017). Data aggregation in wireless sensor networks: Previous research, current status and future directions. Wireless Personal Communications, 97(3), 3355–3425.

    Article  Google Scholar 

  57. Almi’ani K., Viglas, A., & Libman, L. (2010). Energy-efficient data gathering with tour length constrained mobile element in wireless sensor networks. In Proceeding of 35th IEEE conference on local computer networks, Colorado (pp. 582–589).

  58. Kaswan, A., Nitesh, K., & Jana, P. K. (2017). Energy efficient path selection for mobile sink and data gathering in wireless sensor networks. International Journal of Electronics and Communications, 73, 110–118.

    Article  Google Scholar 

  59. Hartigan, J. A., & Wong, M. A. (1979). Algorithm as 136: A k-means clustering algorithm. Journal of the Royal Statistical Society, 28(1), 100–8.

    MATH  Google Scholar 

  60. Kumar, A. K., Sivalingam, K. M., & Kumar, A. (2013). On reducing delay in mobile data collection based wireless sensor networks. Wireless Networks, 19(3), 285–299.

    Article  Google Scholar 

  61. Zhu, R., Qin, Y., & Wang, J. (2011). Energy-aware distributed intelligent data gathering algorithm in wireless sensor networks. International Journal of Distributed Sensor Networks, 7(4), 272–280.

    Google Scholar 

  62. Alnuaimi, M., Shuaib, K., Alnuaimi, K., & Hafez, M. A. (2015). Data gathering in delay tolerant wireless sensor networks using a ferry. Sensors, 15(10), 25809–25830.

    Article  Google Scholar 

  63. Johnson, D. S., & McGeoch, L. A. (2007). Experimental analysis of heuristics for the step. In G. Gutin & A. P. Punnen (Eds.), The traveling salesman problem and its variations (pp. 369–443). Boston: Springer.

    Chapter  Google Scholar 

  64. Cook, W. (2005). Concorde TSP solver. http://www.math.uwaterloo.ca/tsp/concorde/index.html.

  65. Xing, G., Wang, T., Jia, W., & Li, M. (2008). Rendezvous design algorithms for wireless sensor networks with a mobile base station. In Proceeding of 9th ACM international symposium on mobile ad-hoc networking and computing, China (pp. 231–240).

  66. Xing, G., Wang, T., Xie, Z., & Jia, W. (2008). Rendezvous planning in wireless sensor networks with mobile elements. IEEE Transaction on Mobile Computing, 7(12), 1430–1443.

    Article  Google Scholar 

  67. Zhao, M., & Yang, Y. (2012). Bounded relay hop mobile data gathering in wireless sensor networks. IEEE Transaction on Computers, 61(2), 265–277.

    Article  MathSciNet  MATH  Google Scholar 

  68. Wen, W., Zhao, S., Shang, C., & Chang, C.-Y. (2018). EAPC: Energy-aware path construction for data collection using mobile sink in wireless sensor networks. IEEE Sensors Journals, 18(2), 890–901.

    Article  Google Scholar 

  69. Salarian, H., Chin, K. W., & Naghdy, F. (2014). An energy-efficient mobile-sink path selection strategy for wireless sensor networks. IEEE Transaction on Vehicular Technology, 63(5), 2407–2419.

    Article  Google Scholar 

  70. Zhu, C., Wu, S., Han, G., Shu, L., & Wu, H. (2015). A tree-cluster-based data-gathering algorithm for industrial WSNs with a mobile sink. IEEE Access, 3, 381–396.

    Article  Google Scholar 

  71. Sofreavia, M. A local search based TSP solver. http://www3.cs.stonybrook.edu/~algorith/implement/tsp/distrib/maugis/README.

  72. Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2001). Introduction to algorithms (2nd ed.). Cambridge: The MIT Press.

    MATH  Google Scholar 

  73. Cholissodin, I. (2007). To solving traveling salesman problem (TSP) for 10 till 100 city with local search. https://ro.uow.edu.au/cgi/viewcontent.cgi?referer=https://scholar.google.com/&httpsredir=1&article=5009&context=theses.

  74. Balid, W., Tafish, H., & Refai, H. H. (2018). Intelligent vehicle counting and classification sensor for real-time traffic surveillance. IEEE Transactions on Intelligent Transportation Systems, 19(6), 1784–1794.

    Article  Google Scholar 

  75. Boubrima, A., Bechkit, W., & Rivano, H. (2017). Optimal WSN deployment models for air pollution monitoring. IEEE Transactions on Wireless Communications, 16(5), 2723–2735.

    Article  Google Scholar 

  76. Konstantopoulos, C., Pantziou, G., Gavalas, D., Mpitziopoulos, A., & Mamalis, B. (2012). A rendezvous-based approach enabling energy efficient sensory data collection with mobile sinks. IEEE Transaction on Parallel and Distributed Systems, 23(5), 809–817.

    Article  Google Scholar 

  77. Chen, G., Li, C., Ye, M., & Wu, J. (2007). An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks, 15, 193–207.

    Article  Google Scholar 

  78. Huang, H., & Savkin, A. V. (2017). An energy efficient approach for data collection in wireless sensor network using public transportation vehicles. International Journal of Electronics and Communication, 75, 108–118.

    Article  Google Scholar 

  79. Mottaghi, S., & Zahabi, M. R. (2014). Optimizing LEACH clustering algorithm with mobile sink and rendezvous nodes. International Journal of Electronics and Communications, 69, 507–514.

    Article  Google Scholar 

  80. Heizelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless micro sensor networks. In Proceedings of the 33rd IEEE Hawaii international conference on system sciences, USA (pp. 10–20).

  81. Khan, A. W., Abdullah, A. H., Razzaque, M. A., & Bangash, J. I. (2015). VGDRA: A virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks. IEEE Sensors Journal, 15(1), 526–534.

    Article  Google Scholar 

  82. Arthi, K., & Lochana, A. S. L. (2018). Zone-based dual sub sink for network lifetime maximization in wireless sensor network. Cluster Computing. https://doi.org/10.1007/s10586-018-2563-7.

    Article  Google Scholar 

  83. Djiroun, F. Z., & Djenouri, D. (2017). MAC protocols with wake-up radio for wireless sensor networks: A review. IEEE Communications Surveys & Tutorials, 19(1), 587–618.

    Article  Google Scholar 

  84. Intanagonwiwat, C., Govindan, R., & Estrin, D. (2000). Directed diffusion: a scalable and robust communication paradigm for sensor networks. In Proceedings of the 6th annual international conference on mobile computing and networking, (MobiCom 2000), USA (pp. 56–67)

  85. Hamida, E. B. & Chelius, G. (2008). A line-based data dissemination protocol for wireless sensor networks with mobile sink. In Proceedings of IEEE international conference on communications, (ICC 08), China (pp. 2201–2205).

  86. Shin, J.-H., Kim, J., Park, K. & Park, D. (2005). Railroad: Virtual infrastructure for data dissemination in wireless sensor networks. In Proceedings of 2nd ACM international workshop on performance evaluation of wireless ad hoc, sensor, and ubiquitous networks (PE-WASUN 05), Canada (pp. 168–174).

  87. Erman, A., Dilo, A., & Havinga, P. (2012). A virtual infrastructure based on honeycomb tessellation for data dissemination in multi-sink mobile wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2012(17), 1–27.

    Google Scholar 

  88. Tunca, C., Isik, S., Donmez, M. Y., & Ersoy, C. (2015). Ring routing: An energy-efficient routing protocol for wireless sensor networks with a mobile sink. IEEE Transactions on Mobile Computing, 14(9), 1947–1960.

    Article  Google Scholar 

  89. Sharma, S., Puthal, D., Jena, S. K., Zomaya, A. Y., & Ranjan, R. (2016). Rendezvous based routing protocol for wireless sensor networks with mobile sink. The Journal of Supercomputing, 73(3), 1168–1188.

    Article  Google Scholar 

  90. Yarinezhad, R., & Sarabi, A. (2018). Reducing delay and energy consumption in wireless sensor networks by making virtual grid infrastructure and using mobile sink. AEU - International Journal of Electronics and Communications, 84, 144–152.

    Article  Google Scholar 

  91. Shen, C.-C., Srisathapornphat, C., & Jaikaeo, C. (2001). Sensor information networking architecture and applications. IEEE Personal Communication, 8(4), 52–59.

    Article  Google Scholar 

  92. Jain, S., Sharma, S., & Bagga, N. (2015). A vertical and horizontal segregation based data dissemination protocol. In Proceedings of 3rd emerging research in computing, information, communication and applications, (ERCICA-15), India (pp. 401–412).

Download references

Author information

Authors and Affiliations

  1. ABV-Indian Institute of Information Technology and Management, Gwalior, India

    Anjula Mehto, Shashikala Tapaswi & K. K. Pattanaik

Authors
  1. Anjula Mehto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shashikala Tapaswi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. K. Pattanaik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to K. K. Pattanaik.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mehto, A., Tapaswi, S. & Pattanaik, K.K. A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink. Wireless Netw 26, 2639–2663 (2020). https://doi.org/10.1007/s11276-019-02022-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-019-02022-6

Keywords

Search

Navigation