Improving the performance of heterogeneous IoT networks through multi-stage and parallel computing systems

Document Type : Article

Authors

Department of Electronics and Computer Science, Koneru Lakshmaiah Education Foundation University, Vaddeswaram, Guntur District, Andhra Pradesh, India 522502

Abstract

Multiple networking layers existing in the IoT network involve heterogeneity that must be addressed to facilitate proper communication such that the performance of an IoT network does not suffers. The performance of the IoT networks depends on networking topologies used in different layers, clustering algorithms, protocols used for handling heterogeneity communication speeds, and data packet sizes. In this Research, the performance of IoT networks is improved by adding device clustering via a multi-Stage network and using an efficient SOJK clustering algorithm in the device layer, which minimizes power depletion and increases the quantity of data and data packets; transmitted at zero power. A mechanism to handle heterogeneity that exists due to Wi-Fi, CDMA, and USB communication protocols is also presented while optimizing the communication speeds and data transmission size. It has also been shown that the use of 170Mbps cellular speed and the data size of 468 bytes gives the optimum response time of an IoT network. The time taken to transport information from the device to the storage layer is reduced by 57% compared to the time taken to transport the data using the prototype network.

Keywords

References

References:
1. Rahimi, P. and Chrysostomou, C. "Improving the network lifetime and performance of wireless sensor networks for IoT applications based on fuzzy logic", 15th International Conference on Distributed Computing in Sensor Systems (DCOSS), Santorini, Greece, pp. 667-674 (2019).
2. Behzad, M., Abdullah, M., Hassan, M.T., et al. "Performance optimization in IoT-based next-generation wireless sensor networks", Transactions on Computational Collective Intelligence XXXIII. Lecture Notes in Computer Science, 11610, Springer, Berlin, Heidelberg, pp. 1-31 (2019).
3. Khan, Imran., Haque, Md.Ershad, Asikuzzaman, Md and Shah, Syed Bilal. "Comparative study of IoTbased topology maintenance protocol in a wireless sensor network for structural health monitoring", Remote Sensing, 12(15), p. 2358 (2020).
4. Ogudo, A., Kingsley Muwawa, Dahj and Jean Nestor, Dahj Khalaf, Osamah Daei Kasmaei, H. "A deviceperformance and data  analytics concept for smartphones' IoT services and machine-type communication in cellular networks", Symmetry, 11(4), p. 593 (2019).
5. Metongnon, L., Ezin, E.C., and Sadre, R. "Efficient probing of heterogeneous IoT networks", IFIP/IEEE Symposium on Integrated Network and Service Management (IM)., Lisbon, Portugal, pp. 1052-1058 (2017).
6. Sowmya, K.V. and Sastry, J.K.R. "Performance evaluation of IoT systems - basic issues", Int. J. Eng. Technol, 7(2-7), pp. 131-137 (2018).
7. Geetha, V. Kallapur, P.V., and Tellajeera, S. "Clustering in wireless sensor networks: Performance comparison of LEACH and LEACH-C Protocols Using NS2", Procedia Technol, 4, pp. 163-170 (2012).
8. Vijitha Ananthi, J., Chinnalagi, V., Murugeshwari, R., et al. "An effective performance of smart sensor network using IOT", International Journal of Advance Research, Ideas and Innovations in Technology, 3(2), pp. 638-646 (2017).
9. Bhandari, S., Sharma, S.K., and Wang, X. "Cloudassisted device clustering for lifetime prolongation in wireless IoT networks", Can. Conf. Electr. Comput. Eng., Windsor, ON, Canada, pp. 8-11 (2017).
10. Ashwini, M. and Rakesh, N. "Enhancement and performance analysis of the LEACH algorithm in IoT", Proc. Int. Conf. Inven. Syst. Control. ICISC., Coimbatore, India, pp. 1-5 (2017).
11. Choi, D.K., Jung, J.H., Kang, H.W., et al. "Clusterbased CoAP for message queueing in Internet-of- Things networks", Int. Conf. Adv. Commun. Technol. ICACT., PyeongChang, Korea (South), pp. 584-588 (2017).
12. Khedira, S.E.L., Nasri, N.A., Wei, A., et al. "A new approach for clustering in wireless sensors networks based on LEACH", Procedia Comput. Sci., 32, pp. 1180-1185 (2014).
13. Choi, D.K., Jung, J.H., and Koh, S.J. "Enhanced cluster-based CoAP in Internet-of-Things networks", Int. Conf. Inf. Netw., Chiang Mai., Thailand, pp. 652- 656 (2018).
14. Liu, Y. and Zhou, Y. "Development of distributed cache strategy for the analytic cluster in an Internet of Things system", ICNSC 2018 - 15th IEEE Int. Conf. Networking, Sens. Control., Zhuhai, China, pp. 1-6 (2018).
15. Behera, T.M., Samal, U.C., and Mohapatra, S.K. "Energy-efficient modified LEACH protocol for IoT application", IET Wirel. Sens. Syst, 8(6), pp. 223-228 (2018).
16. 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., 6(3), pp. 5132-5139 (2019).
17. Sowmya, K.V. and Sastry, J.K.R. "Performance optimization within the device layer of IoT networks", Journal of Engineering and Technology, 13(6), pp. 1338-1346 (2020).
18. Sowmya, K.V., Chandu, A., Nagasai, A., et al. "Smart home system using clustering based on internet of things", J. Comput. Theor. Nanosci, 17(5), pp. 1-6 (2020).
19. Ju, Q. and Zhang, Y. "Adaptive clustering for the Internet of Battery-less Things", IEEE Wirel. Commun. Netw. Conf. WCNC., San Francisco, CA, USA, pp. 1-5 (2017).
20. Kumar, P. "Data stream clustering in the Internet of Things", SSRG Int. J. Comput. Sci. Eng., 3, pp. 14-19 (2016).
21. Zhao, S., Yu, L., Cheng, B., et al. "IoT service clustering for dynamic service matchmaking", Sensors (Switzerland), 17(8), pp. 1-17 (2017).
22. Puschmann, D. Barnaghi, P., and Tafazolli, R. "Adaptive clustering for dynamic IoT data streams", IEEE Internet Things J., 4(1), pp. 64-74 (2017).
23. Tao, X. and Ji, C. "Clustering massive, small data for IoT", 2nd Int. Conf. Syst. Informatics, (ICSAI 2014). Shanghai, China, pp. 974-978 (2015).
24. Kwon, M. and Park, H. "The cluster formation strategies for approximate decoding in IoT networks", Int. Conf. Inf. Netw., Kota Kinabalu, Malaysia, pp. 366- 368 (2016).
25. Geethika Reddy, A., Upendra, Y., Sastry, J.K.R., et al. "An approach to compute fault tolerance of an IoT network having clustered devices using crossbar networks", Int. J. Emerg. Trends Eng. Res., 8(4), pp. 987-1004 (2020).
26. Sai Rama Krishna, J.S.B.M. and Sastry, J.K.R. "Building fault tolerance within wireless sensor networks: A butter y model", Res. J. Appl. Sci., 12(2), pp. 139-147 (2017).
27. Rajasekhar, J. and Sastry, J. "Building composite embedded systems based networks through hybridization and bridging i2c and can", J. Eng. Sci. Technol, 15(2), pp. 858-881 (2020).
28. Rajasekhar, J. and Sastry, J. "On developing highspeed heterogeneous and composite ES network through multi-master interface", International Journal of Advanced Computer Science and Applications, 11(12), pp. 320-333 (2020).
29. Sastry, J., Ramya, G.S., Niharika, V.M., et al. "Performance optimization of IoT networks within gateway layer", Recent Adv. Comput. Sci. Commun, 13(6), pp. 1338-1346 (2019).
30. Sasi Bhanu, J., Sastry, JKR., Venkata Sunil Kumar, P., et al. "Enhancing performance of IoT networks through high-performance computing", International Journal of Advanced Trends in Computer Science, 8(3), pp. 432-442 (2019).
31. Vishnu Priya, B. and Sastry, J.K.R. "A comparative analysis of the methods used to build information/content-centric networks over softwarede fined networks", J. Eng. Technol, 7(2), pp. 997-1003 (2018).
32. Pavithra, T. and Sastry, J.K.R. "Strategies to handle heterogeneity prevalent within an IOT based network", Int. J. Eng. Technol, 7(2-7), pp. 77-83 (2018).
33. Sastry, J.K.R., Naga Sai Tejasvi, T., and Aparna, J. "Dynamic scheduling of message  flow within a distributed embedded system connected through an RS485 network", ARPN J. Eng. Appl. Sci, 12(9), pp. 2809-2817 (2017).
Scientia Iranica
Volume 30, Issue 5
Transactions on Computer Science & Engineering and Electrical Engineering (D)
September and October 2023
Pages 1714-1730

Files

History

  • Receive Date: 30 March 2021
  • Revise Date: 26 October 2021
  • Accept Date: 18 April 2022

Share

How to cite

Statistics