Abstract
Internet of Things (IoTs) network technologies are becoming popular in delay, integrity, and security sensitive applications such as healthcare, etc. In addition, pervasive IoT network applications face challenges like computing, energy, and network management. This paper presents a novel efficient and secure protocol for emerging IoT network applications (ESPINA), which can be seamlessly hosted on both IoTs and smart edge (SE) nodes and integrated with upcoming sixth generation (6G) wireless communication and embedded systems. The proposed ESPINA protocol consists of two stages: (1) IoT network setup, and (2) data transmission. First stage of ESPINA includes initialization (ESPINAi), path discovery (ESPINAs) and security (ESPINAg) subroutines for the IoT network. Second stage ensures data transmission scheduling for IoTs and SEs associated with the network. ESPINAiot–se and ESPINAse–bs subroutines govern IoTs and selected SE(s) scheduling respectively. When compared against state-of-the-art competitors, the proposed ESPINA protocol: (a) saves 0.5% to 3.5% residual energy consumption depending on the length of the path between a SE and a base station (BS), (b) reduces computational cost from linear [e.g., O(n), where n is the node count] to constant [e.g., O(1)), c] improves security for a longer data transmission time by using its keys-renewal strategy. Low energy, linear computational cost, and better security demonstrate that performance of the ESPINA is better than the compared state-of-the-art protocols. The ESPINA is envisioned as a better candidate protocol to match the standard and expectations set by the 6G wireless communications.
Similar content being viewed by others
Data availability
The present study is based on synthesized data generated randomly by the authors based on some parameters mentioned in the above text.
References
Ali, H.M., et al.: Optimising the power using firework-based evolutionary algorithms for emerging IoT applications. IET Netw. 8(1), 15–31 (2019)
Ali, H.M., et al.: Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods. J. Wirel. Commun. Netw. (2020). https://doi.org/10.1186/s13638-020-01798-y
Ali, H.M., et al.: Planning a secure and reliable IoT-enabled FOG-assisted computing infrastructure for healthcare. Clust. Comput. (2021). https://doi.org/10.1007/s10586-021-03389-y
Banimelhem, O., et al.: Genetic algorithm based node deployment in hybrid wireless sensor networks. Commun. Netw. 5(4), 273–279 (2013)
Bomgni, A.B., Jagho Mdemaya, G.B., et al.: A2CDC: Area Coverage, Connectivity and Data Collection in wireless sensor networks. Netw. Protoc. Algorithms 10(4), 20–34 (2018)
Boualem, A., et al.: Area coverage optimization in wireless sensor network by semi-random deployment. In: Proceedings of the 7th International Conference on Sensor Networks (SENSORNETS 2018), pp. 85–90 (2018)
Butun, I., et al.: Security of the Internet of Things: vulnerabilities, attacks, and countermeasures. IEEE Commun. Surv. Tutor. 22(1), 616–644 (2020). https://doi.org/10.1109/COMST.2019.2953364
Chang, V., Kuo, Y.-H., Ramachandran, M.: Cloud computing adoption framework: a security framework for business clouds. Future Gener. Comput. Syst. 57, 24–41 (2016)
Chen, B., et al.: Edge computing in IoT-based manufacturing. IEEE Commun. Mag. 56(9), 103–109 (2018)
Cheng, W., Li, M., Liu, K., Liu, Y., Li, X., Liao, X.: Sweep Coverage with Mobile Sensors, Mobile Computing IEEE Transactions (2011)
Dar, Z., et al.: A context-aware encryption protocol suite for edge computing-based IoT devices. J Supercomput. 76, 2548–2567 (2020). https://doi.org/10.1007/s11227-019-03021-2
Erdelj, M., et al.: Covering points of interest with mobile sensors. IEEE Trans. Parallel Distrib. Syst. 24(1), 32–43 (2013)
Erdelj, M., et al.: Multiple point of interest discovery and coverage with mobile wireless sensors. In: Computing Networking and Communications (2012)
Hajjej, F., et al.: An efficient deployment approach for improved coverage in wireless sensor networks based on flower pollination algorithm. In: Computer Science and Information Technology (CS & IT), pp. –129 (2016)
He, S., Chen, J., et al.: Cost-effective barrier coverage by mobile sensor network. In: IEEE INFOCOM (2012)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd IEEE Hawaii International Conference on Systems (2000)
Jamshidi, M., Ranjbari, M., Esnaashari, N., Qader, N.: Sybil node detection in mobile wireless sensor networks using observer nodes. JOIV Int. J. Inform. Vis. 2(3), 159–165 (2018)
Kim, Y.H., et al.: Regular sensor deployment patterns for p-coverage and q-connectivity in wireless sensor networks. In: ICOIN (2012)
Kong, L., et al.: ICP: instantaneous clustering protocol for wireless sensor networks. Comput. Netw. 101, 144–157 (2016)
Kong, L., et al.: Mobile barrier coverage for dynamic objects in wireless sensor networks. In: Mobile Adhoc and Sensor Systems MASS, Las Vegas, NV, USA (2012)
Li, J., et al.: A secured framework for SDN-based edge computing in IoT-enabled healthcare system. IEEE Access 8, 135479–135490 (2020)
Liu, Y., et al.: Intelligent edge computing for IoT-based energy management in smart cities. IEEE Netw. 33(2), 111–117 (2019)
Ngom, D., et al.: DSMAC: Constraints-Based Coverage and Connectivity for Optimizing the Network Lifetime in Wireless Sensor Networks (2017)
Ngom, D.: Optimisation de la durée de vie dans les réseaux de capteurs sans fil sous contraintes de couverture et de connectivité réseau. Réseaux et téléommunications [cs.NI]. Université de Haute Alsace - Mulhouse (2016)
Oliveira, L.B., Wong, H.C., Bern, M., Dahab, R., Loureiro, A.A.F.: SecLEACH—a random key distribution solution for securing clustered sensor networks. In: Network Computing and Applications (2006)
Pan, J., et al.: Future edge cloud and edge computing for Internet of Things applications. IEEE Internet Things J. 5(1), 439–449 (2018)
Rajavel, R., et al.: IoT-based smart healthcare video surveillance system using edge computing. J. Ambient Intell. Humaniz. Comput. (2021). https://doi.org/10.1007/s12652-021-03157-1
Song, H., et al.: Security and Privacy in Cyber-Physical Systems: Foundations, Principles and Applications, pp. 1–472. Wiley-IEEE Press, Chichester (2017). ISBN: 978-1-119-22604-8
Vaiyapuri, T., et al.: A novel hybrid optimization for cluster-based routing protocol in information-centric wireless sensor networks for IoT based mobile edge computing. Wirel. Pers. Commun. (2021). https://doi.org/10.1007/s11277-021-08088-w
Yu, W., et al.: A survey on the edge computing for the Internet of Things. IEEE Access 6, 6900–6919 (2018)
Zhu, S., Setia, S., Jajodia, S.: LEAP+: efficient security mechanisms for large-scale distributed sensor networks. ACM Trans. Sens. Netw. 2(4), 500–528 (2006)
Zhu, S., Setia, S., Jajodia, S.: LEAP: efficient security mechanisms for large-scale distributed sensor networks. In: Computer-Communication Networks (2004)
Author information
Authors and Affiliations
Contributions
This work was conceptualized and designed by ABB and GBJ. Experiment was designed by ABB, GBJ, HMA and DGZ. Initial draft was prepared by ABB and HMA. After initial draft, HMA, GBJ, ABB, and DGZ give input to improve quality and presentation. EGZ is PI of this work and edited first and subsequent draft of the manuscript. All the authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflict of interest.
Ethical approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bomgni, A.B., Mdemaya, G.B.J., Ali, H.M. et al. ESPINA: efficient and secured protocol for emerging IoT network applications. Cluster Comput 26, 85–98 (2023). https://doi.org/10.1007/s10586-021-03493-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10586-021-03493-z