Skip to main content

Advertisement

SpringerLink
Log in

An Integrated Exploration on Internet of Things and Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The ability to access data from remote locations is meant possible with the help of computer networks. These networks may be wired or wireless. Modern improvements in wireless infrastructure brought wireless sensor networks (WSN) into existence. WSN is utilized to monitor, report, and supervise tasks or events occurring in the environment. The relaying of data in such systems takes place by utilizing different routing schemes. These routing schemes were proposed to augment the throughput of communication networks. In addition, perception regarding the Internet of Things (IoT) gained momentum via making it feasible for things to interact and act smartly. In this paper, a meticulous survey of solutions proposed in both the domains i.e. WSN and IoT is conferred. Later, comprehensive scrutiny of various solutions proposed in the WSN and IoT domain is deliberated regarding their features, pros, and cons. Moreover, this work compares various proposed solutions based on performance measures like heterogeneity, interoperability, mobility, reusability, flexibility, energy efficiency, scalability, delay, security as well as big data. This knowledge enables the network architect to pick the apt solution in support of a specific application. As the integration of WSN and IoT raised numerous open issues, this work deliberated the afore-mentioned performance measures as the key open issues of interest. Furthermore, novel exploration guidelines in the said domain have been elaborated. These guidelines are expected to act as a key component in the upcoming enhancements of communication networks.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

Not applicable.

Code Availability

Not applicable.

References

  1. Botta, A., Donato, W. D., Persico, V., & Pescape, A. (2016). Integration of Cloud computing and Internet of Things: A survey. Future Generation Computer Systems, 56, 684–700.

    Article  Google Scholar 

  2. Zhao, D., Yan, Z., Wang, M., Zhang, P., & Song, B. (2021). Is 5G handover secure and private? A survey. IEEE Internet of Things Journal, 8(16), 12855–12879.

    Article  Google Scholar 

  3. Kocakulak, M., & Butun, I. (2017). An overview of wireless sensor networks towards Internet of Things. In IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), pp. 1–6.

  4. Gagliordi, N. (2018). IoT to drive growth in connected devices through 2022: Cisco. Between the Lines. https://www.zdnet.com/article/iot-to-drive-growth-in-connected-devices-through-2022-cisco/

  5. Dai, H. N., Zheng, Z., & Zhang, Y. (2019). Blockchain for Internet of Things: A survey. IEEE Internet Of Things Journal, 6(5), 8076–8094.

    Article  Google Scholar 

  6. Washizaki, H., Ogata, S., Hazeyama, A., Okubo, T., Fernandez, E. B., & Yoshioka, N. (2020). Landscape of architecture and design patterns for IoT systems. IEEE Internet of Things Journal, 7(10), 10091–10101.

    Article  Google Scholar 

  7. Paniagua, C., & Delsing, J. (2021). Industrial frameworks for Internet of Things: A survey. IEEE Systems Journal, 15(1), 1149–1159.

    Article  Google Scholar 

  8. Liu, D., Yan, Z., Ding, W., & Atiquzzaman, M. (2019). A survey on secure data analytics in edge computing. IEEE Internet of Things Journal, 6(3), 4946–4967.

    Article  Google Scholar 

  9. Feng, X., Wei, T., Chen, Y., Ge, N., & Wang, C. X. (2021). 5G embraces satellites for 6G ubiquitous IoT: Basic models for integrated satellite terrestrial networks. IEEE Internet of Things Journal, 8(18), 14399–14417.

    Article  Google Scholar 

  10. Ali, Z. H., & Ali, H. A. (2021). Towards sustainable smart IoT applications architectural elements and design: Opportunities, challenges, and open directions. The Journal of Supercomputing, 77, 5668–5725. https://doi.org/10.1007/s11227-020-03477-7

    Article  Google Scholar 

  11. Arvanitou, E. M., Ampatzoglou, A., Chatzigeorgiou, A., & Carver, J. C. (2021). Software engineering practices for scientific software development: A systematic mapping study. The Journal of Systems & Software, 172, 110848.

    Article  Google Scholar 

  12. Hustad, E., & Olsen, D. H. (2021). Creating a sustainable digital infrastructure: The role of service-oriented architecture. Procedia Computer Science, 181, 597–604.

    Article  Google Scholar 

  13. Xu, L., Collier, R., & Hare, G. M. P. O. (2017). A survey of clustering techniques in WSNs and consideration of the challenges of applying such to 5G IoT scenarios. IEEE Internet of Things Journal, 4(5), 1229–1249.

    Article  Google Scholar 

  14. Piao, Z., Peng, M., Liu, Y., & Daneshmand, M. (2019). Recent advances of edge cache in radio access networks for Internet of Things: Techniques, performances, and challenges. IEEE Internet of Things Journal, 6(1), 1010–1028.

    Article  Google Scholar 

  15. Sodhro, A. H., Pirbhulal, S., Luo, Z., Muhammad, K., & Zahid, N. (2021). Toward 6G architecture for energy-efficient communication in IoT-enabled smart automation systems. IEEE Internet of Things Journal, 8(7), 5141–5148.

    Article  Google Scholar 

  16. Jin, F., Zhang, H., Ng, J. K. Y., Guo, S., Lee, V. C. S., & Son, S. H. (2020). Toward scalable and robust indoor tracking: Design, implementation, and evaluation. IEEE Internet of Things Journal, 7(2), 1192–1204.

    Article  Google Scholar 

  17. Sobin, C. C. (2020). A survey on architecture, protocols and challenges in IoT. Wireless Personal Communications, 2020(112), 1383–1429. https://doi.org/10.1007/s11277-020-07108-5

    Article  Google Scholar 

  18. Zhu, S., Yang, S., Gou, X., Xu, Y., Zhang, T., & Wan, Y. (2021). Survey of testing methods and testbed development concerning Internet of Things. Wireless Personal Communications. https://doi.org/10.1007/s11277-021-09124-5

    Article  Google Scholar 

  19. Shirmarz, A., & Ghaffari, A. (2020). Performance issues and solutions in SDN-based data center: A survey. The Journal of Supercomputing, 2020(76), 7545–7593. https://doi.org/10.1007/s11227-020-03180-7

    Article  Google Scholar 

  20. Gasmi, K., Dilek, S., Tosun, S., & Ozdemir, S. (2021). A survey on computation offloading and service placement in fog computing-based IoT. The Journal of Supercomputing. https://doi.org/10.1007/s11227-021-03941-y

    Article  Google Scholar 

  21. Hu, M., Luo, X., Chen, J., Lee, Y. C., Zhou, Y., & Wu, D. (2021). Virtual reality: A survey of enabling technologies and its applications in IoT. Journal of Network and Computer Applications, 178, 102970.

    Article  Google Scholar 

  22. Khan, M. A., & Salah, K. (2018). IoT security: Review, blockchain solutions, and open challenges. Future Generation Computer Systems, 82, 395–411.

    Article  Google Scholar 

  23. Ghaleb, B., Al-Dubai, Y. A., Elias, E., Ayoub, A., Youssef, N., Mackenzie, L. M., & Azzedin, B. (2018). A survey of limitations and enhancements of the IPv6 routing protocol for low-power and Lossy networks: A focus on core operations. IEEE Communications Surveys & Tutorials, 21, 1607–1635.

    Article  Google Scholar 

  24. Adat, V., & Gupta, B. B. (2018). Security in Internet of Things: Issues, challenges, taxonomy, and architecture. Telecommunication Systems, 67, 423–441.

    Article  Google Scholar 

  25. Javed, F., Afzal, M. K., Sharif, M., & Kim, B. S. (2018). Internet of Things (IoTs) operating systems support, networking technologies, applications, and challenges: A comparative review. IEEE Communications Surveys & Tutorials, 20, 2062–2100.

    Article  Google Scholar 

  26. Costa, K. A. P. D., Papa, J. P., Lisboa, C. O., Munoz, R., & Albuquerque, V. H. C. D. (2019). Internet of Things: A survey on machine learning-based intrusion detection approaches. Computer Networks, 151, 147–157.

    Article  Google Scholar 

  27. Sengupta, J., Ruj, S., & Bit, S. D. (2019). A comprehensive survey on attacks, security issues and blockchain solutions for IoT and IIoT. Journal of Network and Computer Applications, 149, 102481.

    Article  Google Scholar 

  28. Verma, A., & Ranga, V. (2020). Security of RPL based 6LoWPAN Networks in the Internet of Things: A Review. IEEE Sensors Journal, 10, 6472.

    Google Scholar 

  29. Verma, V. K., Ntalianis, K., Moreno, C. M., & Yang, C. T. (2019). Next-generation Internet of things and cloud security solutions. International Journal of Distributed Sensor Networks, 15(3). ISSN: 15501477, SAGE Publishing. https://doi.org/10.1177/1550147719835098

  30. Verma, V. K., Singh, S., & Pathak, N. P. (2016). Analytical event based investigations over Delphi random generator distributions for data dissemination routing protocols in highly dense wireless sensor networks. Wireless Personal Communications: An International Journal, 87(4), 1209–1222., ISSN: 0929-6212 (Print) 1572-834X (Online).

  31. Avila, K., Jabba, D., & Gomez, J. (2020). Security aspects for Rpl-based protocols: A systematic review in IoT. Applied Sciences, 10(6472), 1–20.

    Google Scholar 

  32. Almusaylim, Z. A., Alhumam, A., & Jhanjhi, N. Z. (2020). Proposing a secure RPL based Internet of Things routing protocol: A review. Ad Hoc Networks, 101, 102096.

    Article  Google Scholar 

  33. Simha, S. N. V., Mathew, R., Sahoo, S., & Biradar, R. C. (2020). A review of RPL protocol using Contiki operating system. In Proceedings of the Fourth International Conference on Trends in Electronics and Informatics (ICOEI 2020), pp. 259–264.

  34. Thakkar, A., & Lohiya, R. (2021). A review on machine learning and deep learning perspectives of IDS for IoT: Recent updates, security issues, and challenges. Archives of Computational Methods in Engineering, 28, 3211–3243. https://doi.org/10.1007/s11831-020-09496-0

    Article  Google Scholar 

  35. Alfandi, O., Khanji, S., Ahmad, L., & Khattak, A. (2021). A survey on boosting IoT security and privacy through blockchain. Cluster Computing, 24, 37–55. https://doi.org/10.1007/s10586-020-03137-8

    Article  Google Scholar 

  36. Xu, L. D., Lu, Y., & Li, L. (2021). Embedding blockchain technology into IoT for security: A survey. IEEE Internet of Things Journal, 8(13), 10452–10473.

    Article  Google Scholar 

  37. Aversano, L., Bernardi, M. L., Cimitile, M., & Picori, R. (2021). A systematic review on Deep Learning approaches for IoT security. Computer Science Review, 40, 100389.

    Article  MathSciNet  Google Scholar 

  38. Raj, A., & Shetty, S. D. (2021). IoT eco-system, layered architectures, security and advancing technologies: A comprehensive survey. Wireless Personal Communications. https://doi.org/10.1007/s11277-021-08958-3

    Article  Google Scholar 

  39. Sezer, O. B., Dogdu, E., & Ozbayoglu, A. M. (2018). Context-aware computing, learning, and big data in Internet of Things: A survey. IEEE Internet of Things Journal, 5(1), 1–27.

    Article  Google Scholar 

  40. Nazir, S., Nawaz, M., & Adnan, A. (2019). Big data features, applications, and analytics in cardiology—A systematic literature review. IEEE Access, 7, 143742–143771.

    Article  Google Scholar 

  41. Hajaji, Y., Boulila, W., Farah, I. R., Romdhani, I., & Hussain, A. (2021). Big data and IoT-based applications in smart environments: A systematic review. Computer Science Review, 39, 100318.

    Article  Google Scholar 

  42. Kumar, D., & Jha, V. K. (2021). A review on recent trends in query processing and optimization in big data. Wireless Personal Communications. https://doi.org/10.1007/s11277-021-09375-2

    Article  Google Scholar 

  43. Ferreira, H. G. C., & Desousa, R. T. (2017). Security analysis of a proposed Internet of Things middleware. Cluster Computing, 20, 651–660.

    Article  Google Scholar 

  44. Niaraki, M. J., Niaraki, A. S., & Choi, S. M. (2018). Semantic interoperability of GIS and MCDA tools for environmental assessment and decision making. Environment Modelling and Software, 100, 104–122.

    Article  Google Scholar 

  45. Koo, J., Oh, S. R., & Kim, Y. G. (2019). Device identification interoperability in heterogeneous IoT platforms. Sensors, 19(6), 1–16. https://doi.org/10.3390/s19061433

    Article  Google Scholar 

  46. Cimmino, A., Villalon, M. P., & Castro, R. G. (2020). eWoT: A semantic interoperability approach for heterogeneous IoT ecosystems based on the web of things. Sensors, 20(3), 1–19. https://doi.org/10.3390/s20030822

    Article  Google Scholar 

  47. Abbasi, M. A., Memon, Z. A., Durrrani, N. M., Haider, W., Laeeq, K., & Mallah, G. A. (2021). A multi-layer trust-based middleware framework for handling interoperability issues in heterogeneous IOTs. Cluster Computing, 24, 2133–2160. https://doi.org/10.1007/s10586-021-03243-1

    Article  Google Scholar 

  48. Fotouhi, H., Moreira, D., Alves, M., & Yomsi, P. M. (2017). mRPL+: A mobility management framework in RPL/6LoWPAN. Computer Communications, 104, 34–54.

    Article  Google Scholar 

  49. Yong, B., Xu, Z., Wang, X., Cheng, L., Li, X., Wu, X., & Zhou, Q. (2018). IoT-based intelligent fitness system. Journal of Parallel and Distributed Computing, 118, 14–21.

    Article  Google Scholar 

  50. Alsaeedy, A. A. R., & Chong, E. K. P. (2019). Mobility management for 5G IoT devices: Improving power consumption with lightweight signaling overhead. IEEE Internet of Things Journal, 6(5), 8237–8247.

    Article  Google Scholar 

  51. Pirbhulal, S., Wu, W., Muhammad, K., Mehmood, I., Li, G., & Albuquerque, V. H. C. (2020). Mobility-enabled security for optimizing IoT-based intelligent applications. Recent Advances in Security and Privacy for Future Intelligent Networks, 34(2), 72–77.

    Google Scholar 

  52. Hu, H., Wang, Q., Hu, R. Q., & Zhu, H. (2021). Mobility-aware offloading and resource allocation in an MEC-enabled IoT network with energy harvesting. IEEE Internet of Things Journal, 8(24), 17541–17556.https://doi.org/10.1109/JIOT.2021.308198

    Article  Google Scholar 

  53. Li, W., & Kara, S. (2017). Methodology for monitoring manufacturing environment by using Wireless Sensor Networks (WSN) and the Internet of Things (IoT). In The 24th CIRP Conference on Life Cycle Engineering, Procedia CIRP, Vol. 61, pp. 323–328.

  54. Jarwar, M. A., Kibria, M. G., Ali, S., & Chong, I. (2018). Microservices in web objects enabled IoT environment for enhancing reusability. Sensors, 18(2), 352. https://doi.org/10.3390/s18020352

    Article  Google Scholar 

  55. Lo, S. K., Liew, C. S., Tey, K. S., & Mekhilef, S. (2019). An interoperable component-based architecture for data-driven IoT system. Sensors, 19(20), 4354. https://doi.org/10.3390/s19204354

    Article  Google Scholar 

  56. Bhandari, K. S., Ra, I. H., & Cho, G. (2020). Multi-topology based QoS-differentiation in RPL for Internet of Things applications. IEEE Access, 8, 96686–96705.

    Article  Google Scholar 

  57. Rafique, W., Zhao, X., Yu, S., Yaqoob, I., Imran, M., & Dou, W. (2020). An application development framework for Internet-of-Things service orchestration. IEEE Internet of Things Journal, 7(5), 4543–4556.

    Article  Google Scholar 

  58. Smiari, P., Bibi, S., & Feitosa, D. (2020). Examining the reuse potentials of IoT application frameworks. The Journal of Systems & Software, 169, 110706.

    Article  Google Scholar 

  59. Pradeep, P., Krishnamoorthy, S., & Pathinarupothi, R. K. (2021). Leveraging context-awareness for Internet of Things ecosystem: Representation, organization, and management of context. Computer Communications, 177, 33–50.

    Article  Google Scholar 

  60. Wang, J., Cao, Y., Li, B., Kim, H., & Lee, S. (2017). Particle swarm optimization based clustering algorithm with mobile sink for WSNs. Future Generation Computer Systems, 76, 452–457.

    Article  Google Scholar 

  61. Al-Turjman, F., Radwan, A., Mumtaz, S., & Rodriguez, J. (2017). Mobile traffic modeling for wireless multimedia sensor networks in IoT. Computer Communications, 112, 109–115.

    Article  Google Scholar 

  62. Sadek, R. A. (2018). Hybrid energy-aware clustered protocol for IoT heterogeneous network. Future Computing and Informatics Journal, 37, 1–14.

    Google Scholar 

  63. Farman, H., Jan, B., Javed, H., Ahmad, N., Iqbal, J., Arshad, M., & Ali, S. (2018). Multi-criteria based Zone Head Selection in Internet of Things based Wireless Sensor Networks. Future Generation Computer System, 4169, 1–21.

    Google Scholar 

  64. Sheth, J., & Dezfouli, B. (2019). Enhancing the energy-efficiency and timeliness of IoT communication in WiFi networks. IEEE Internet of Things Journal, 6(5), 9085–9097.

    Article  Google Scholar 

  65. Song, K., Zhang, J., Ji, Z., Jiang, J., & Li, C. (2020). Energy-efficiency for IoT system with cache-enabled fixed-wing UAV relay. IEEE Access, 8, 117503–117512.

    Article  Google Scholar 

  66. López-Morales, J. A., Martínez, J. A., & Skarmeta, A. F. (2021). Improving energy efficiency of irrigation wells by using an IoT-based platform. Electronics, 10(3), 250. https://doi.org/10.3390/electronics10030250

    Article  Google Scholar 

  67. Ren, J., Guo, H., Xu, C., & Zhang, Y. (2017). Serving at the edge: A scalable IoT architecture based on transparent computing. IEEE Network, 31(5), 96–105.

    Article  Google Scholar 

  68. Verma, V. K., Ntalianis, K., Singh, S., & Pathak, N. P. (2018). Data proliferation based estimations over distribution factor in heterogeneous wireless sensor networks. Computer Communications, 124, 111–118.

    Article  Google Scholar 

  69. Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2019). LSB : A Light weight Scalable Blockchain for IoT security and anonymity. Journal of Parallel and Distributed Computing, 134, 180–197.

    Article  Google Scholar 

  70. Sharma, S., & Verma, V. K. (2020). Security explorations for routing attacks in low power networks on internet of things. Journal of Supercomputing. https://doi.org/10.1007/s11227-020-03471-z

    Article  Google Scholar 

  71. Ibrar, M., Wang, L., Muntean, G. M., Shah, N., Akbar, A., & Qureshi, K. I. (2021). SOSW: scalable and optimal nearsighted location selection for fog node deployment and routing in SDN-based wireless networks for IoT systems. Annals of Telecommunications, 76, 331–341.

    Article  Google Scholar 

  72. Mubeen, S., Nikolaidis, P., Didic, A., Breivold, H. P., Sandstrom, K., & Behnam, M. (2017). Delay mitigation in offloaded cloud controllers in industrial IoT. IEEE Access, 5, 4418–4430.

    Article  Google Scholar 

  73. Yousefpour, A., Ishigaki, G., Gour, R., & Jue, J. P. (2018). On reducing IoT service delay via fog offloading. IEEE Internet of Things Journal, 5(2), 998–1010.

    Article  Google Scholar 

  74. Motlagh, N. H., Bagaa, M., & Taleb, T. (2019). Energy and delay aware task assignment mechanism for UAV-based IoT platform. IEEE Internet of Things Journal, 6(4), 6523–6536.

    Article  Google Scholar 

  75. Shahryari, O. K., Pedram, H., Khajehvand, V., & TakhtFooladi, M. D. (2020). Energy-Efficient and delay-guaranteed computation offloading for fog-based IoT networks. Computer Networks, 182, 107511.

    Article  Google Scholar 

  76. Althoubi, A., Alshahrani, R., & Peyravi, H. (2021). Delay analysis in IoT sensor networks. Sensors, 21, 3876. https://doi.org/10.3390/s21113876

    Article  Google Scholar 

  77. Verma, V. K. (2017). Pheromone and path length factor-based trustworthiness estimations in heterogeneous wireless sensor networks. IEEE Sensors Journal, 17, 215–220.

    Article  Google Scholar 

  78. Verma, V. K., Singh, S., & Pathak, N. P. (2015). Optimized battery models estimation for static, distance vector and on-demand based routing protocols over 802.11 enabled wireless sensor networks. Wireless Personal Communications: An International Journal, 81(2), 503–517. ISSN: 0929-6212 (Print) 1572-834X (Online).

  79. Verma, V.K., Singh, S., Pathak, N. P. (2014). Comprehensive event based estimation of sensor node distribution strategies using classical flooding routing protocol in wireless sensor networks. Wireless Networks: The Journal of Mobile Communication, Computation and Information, 20(8), 2349–2357. ISSN: 1022-0038 (Print) 1572-8196 (Online).

  80. Verma, V. K., Singh, S., Pathak, N. P. (2014). Collusion based realization of trust and reputation models in extreme fraudulent environment over static and dynamic wireless sensor networks. International Journal of Distributed Sensor Networks, 2014, Article ID 672968, 1–9.

  81. Verma, V. K., Singh, S., & Pathak, N. P. (2016). Impact of malicious servers over trust and reputation models in wireless sensor networks. International Journal of Electronics, 103(3), 530–540. Print ISSN: 0020-7217 Online ISSN: 1362-3060.

  82. Verma, V. K., Singh, S., & Pathak, N. P. (2014). Analysis of scalability for AODV routing protocol in wireless sensor networks. Optik - International Journal for Light and Electron Optics, 125(2), 748–750. ISSN: 0030-4026.

  83. Verma, V. K., Singh, S., & Pathak, N. P. (2017). Towards comparative evaluation of trust and reputation models over static, dynamic and oscillating wireless sensor networks. Wireless Networks, 23, 335–343.

    Article  Google Scholar 

  84. Johnson, M. O., Siddiqui, A., & Karami, A. (2017). A wormhole attack detection and prevention technique in wireless sensor networks. International Journal of Computer Applications, 174, 1–8.

    Article  Google Scholar 

  85. Jarrah, O. Y. A., Hammdi, Y. A., Yoo, P. D., Muhaidat, S., & Qutayri, M. A. (2017). Semi-supervised multi-layered clustering model for intrusion detection. Digital Communications and Networks, 109, 1–12.

    Google Scholar 

  86. Diro, A. A., & Chilamkurti, N. (2018). Distributed attack detection scheme using deep learning approach for Internet of Things. Future Generation Computer Systems, 82, 761–768.

    Article  Google Scholar 

  87. Airehrour, D., Gutierrez, J. A., & Ray, S. K. (2018). SecTrust-RPL: A secure trust-aware RPL routing protocol for Internet of Things. Future Generation Computer Systems, 4033, 1–29.

    Google Scholar 

  88. Jyothisree, M. V. R., & Sreekanth, S. (2019). Attacks in RPL and detection technique used for Internet of Things. International Journal of Recent Technology and Engineering (IJRTE), 1876–1879. ISSN: 2277-3878.

  89. Anitha, A. A. & Arockiam, L. (2019). ANNIDS: Artificial neural network based intrusion detection system for Internet of Things. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(11), 2583–2588. ISSN: 2278–3075.

  90. Sharma, M., Elmiligi, H., Gebali, F., & Verma, A. (2019). Simulating attacks for RPL and generating multi-class dataset for supervised machine learning. In: IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON-2019), pp. 20–26.

  91. Qureshi, K. N., Rana, S. S., Ahmed, A., & Jeon, G. (2020). A novel and secure attacks detection framework for Smart Cities Industrial Internet of Things. Sustainable Cities and Society, 102343, 1–33.

    Google Scholar 

  92. Ahutu, O. R., & El-Ocla, H. (2020). Centralized routing protocol for detecting wormhole attacks in wireless sensor networks. IEEE Access, 8, 63270–63282.

    Article  Google Scholar 

  93. Sahay, R., Geethakumari, G., Mitra, B., & Sahoo, I. (2020). Efficient framework for detection of version number attack in Internet of Things. In A. Abraham, A. Cherukuri, P. Melin, & N. Gandhi (Eds.), Intelligent Systems Design and Applications (ISDA 2018). Advances in Intelligent Systems and Computing (AISC 941) (pp. 480–492). Springer.

    Google Scholar 

  94. Pu, C. (2020). Sybil attack in RPL-based Internet of Things: analysis and defenses. IEEE Internet of Things Journal, 7, 4937–4949.

    Article  Google Scholar 

  95. Sharma, S., & Verma, V. K. (2021). AIEMLA: Artificial intelligence enabled machine learning approach for routing attacks on internet of things. The Journal of Supercomputing, 77, 13757–13787.

    Article  Google Scholar 

  96. Rambabu, K., & Venkatram, N. (2021). Ensemble classification using traffic flow metrics to predict distributed denial of service scope in the Internet of Things (IoT) networks. Computers and Electrical Engineering, 96, 107444.

    Article  Google Scholar 

  97. Guo, L., Dong, M., Ota, K., Li, Q., Ye, T., Wu, J., & Li, J. (2017). A secure mechanism for big data collection in large scale Internet of vehicle. IEEE Internet of Things Journal, 4(2), 601–610.

    Article  Google Scholar 

  98. Jindal, A., Dua, A., Kumar, N., Das, A. K., Vasilakos, A. V., & Rodrigues, J. J. P. C. (2018). Providing healthcare-as-a-service using fuzzy rule based big data analytics in cloud computing. IEEE Journal of Biomedical And Health Informatics, 22(5), 1605–1618.

    Article  Google Scholar 

  99. Mehmood, I., Ullah, A., Muhammad, K., Deng, D. J., Meng, W., Turjman, F. A., Sajjad, M., & Albuquerque, V. H. C. D. (2019). Efficient image recognition and retrieval on IoT-assisted energy-constrained platforms from big data repositories. IEEE Internet of Things Journal, 6(6), 9246–9255.

    Article  Google Scholar 

  100. Li, F., Xie, R., Wang, Z., Guo, L., Ye, J., Ma, P., & Song, W. (2020). Online distributed IoT security monitoring with multidimensional streaming big data. IEEE Internet of Things Journal, 7(5), 4387–4394.

    Article  Google Scholar 

  101. Wan, S., Lu, J., Fan, P., & Lataief, K. B. (2020). Toward big data processing in IoT: Path planning and resource management of UAV base stations in mobile-edge computing system. IEEE Internet of Things Journal, 7(7), 5995–6009.

    Article  Google Scholar 

  102. Lv, Z., Lou, R., Li, J., Singh, A. K., & Song, H. (2021). Big data analytics for 6G-enabled massive Internet of Things. IEEE Internet of Things Journal, 8(7), 5350–5359.

    Article  Google Scholar 

  103. Yu, W., Liu, Y., Dillon, T., Rahayu, W., & Mostafa, F. (2021). An integrated framework for health state monitoring in a smart factory employing IoT and big data techniques. IEEE Internet of Things Journal, X(X), 1–12.

    Google Scholar 

Download references

Funding

No funding available.

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, India

    Saurabh Sharma & Vinod Kumar Verma

Authors
  1. Saurabh Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vinod Kumar Verma
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Optional: All the authors have contributed for this manuscript.

Corresponding author

Correspondence to Vinod Kumar Verma.

Ethics declarations

Conflict of interest

Authors declare that they have no conflict of interest regarding publication of the manuscript.

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

Sharma, S., Verma, V.K. An Integrated Exploration on Internet of Things and Wireless Sensor Networks. Wireless Pers Commun 124, 2735–2770 (2022). https://doi.org/10.1007/s11277-022-09487-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-022-09487-3

Keywords

Search

Navigation