Top

Wireless Personal Communications

Published in:

22-04-2021

Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks

Authors: J. Ramkumar, R. Vadivel

Published in: Wireless Personal Communications | Issue 2/2021

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Internet of Things (IoT) based applications are being evolved in multiple fields to provide enhanced service to the world. IoT is a recent computing concept interconnecting the wired and wireless networks through the internet. Most mobile devices function only in an ad-hoc manner. Infrastructureless networks are called ad-hoc networks. IoT is an effective technology to utilize in Cognitive Radio Mobile Ad-hoc Network (CRMANET) instantaneously. The protocols that are developed for common ad-hoc networks will never suit for IoT-based-CRMANET because the delay they face is inversely proportional with real-time applications. Hence, there exists a need for designing and developing a better routing protocol that suits IoT-based ad-hoc networks. Multi adaptive route indicates the optimum cum efficient path which is selected when the priority of the node gets changed or failed, it may be due to problems that arise in nodes or network components. Multi-adaptive routes make sure the connectivity of the network and its operations before sending the data packet. This paper focuses on developing a Multi-Adaptive Routing Protocol (MARP) inspired by natural characteristics of fish for IoT-based ad-hoc networks to minimize the delay and the energy consumption to extend a network lifetime. NS3 simulation results indicate that MARP gives its best performance than other routing protocols in terms of Throughput, Packet Delivery Ratio, Packet Drop Ratio, Delay and Energy Consumption.

next article A Novel Baseband Generation Method for Modeling RF Power Amplifiers for Bit Error Rate Computations

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Singh, V. K., Mukhopadhyay, S., Xhafa, F., & Sharma, A. (2020). A budget feasible peer graded mechanism for iot-based crowdsourcing. Journal of Ambient Intelligence and Humanized Computing, 11(4), 1531–1551. https://doi.org/10.1007/s12652-019-01219-z.CrossRef

Yohan, A., & Lo, N. W. (2020). FOTB: A secure blockchain-based firmware update framework for IoT environment. International Journal of Information Security 19, 257–278. Springer. https://doi.org/10.1007/s10207-019-00467-6.

Mukherjee, A., Deb, P., De, D., & Buyya, R. (2019). IoT-F2N: An energy-efficient architectural model for IoT using Femtolet-based fog network. Journal of Supercomputing, 75(11), 7125–7146. https://doi.org/10.1007/s11227-019-02928-0.CrossRef

Hwang, J., Aziz, A., Sung, N., Ahmad, A., Le Gall, F., & Song, J. (2020). AUTOCON-IoT: Automated and Scalable Online Conformance Testing for IoT Applications. IEEE Access, 8, 43111–43121. https://doi.org/10.1109/ACCESS.2020.2976718.CrossRef

Chowdhury, A., & Raut, S. (2019). Scheduling Correlated IoT Application Requests Within IoT Eco-System: An Incremental Cloud Oriented Approach. Wireless Personal Communications, 108(2), 1275–1310. https://doi.org/10.1007/s11277-019-06469-w.CrossRef

Neshenko, N., Bou-Harb, E., Crichigno, J., Kaddoum, G., & Ghani, N. (2019). Demystifying IoT Security: An Exhaustive Survey on IoT Vulnerabilities and a First Empirical Look on Internet-Scale IoT Exploitations. IEEE Communications Surveys and Tutorials, 21(3), 2702–2733. https://doi.org/10.1109/COMST.2019.2910750.CrossRef

Condry, M. W., & Nelson, C. B. (2016). Using Smart Edge IoT Devices for Safer, Rapid Response with Industry IoT Control Operations. Proceedings of the IEEE, 104(5), 938–946. https://doi.org/10.1109/JPROC.2015.2513672.CrossRef

Ramkumar, J., & Vadivel, R. (2020). Improved wolf prey inspired protocol for routing in cognitive radio ad hoc networks. International Journal of Computer Networks and Applications, 7(5), 126–136. https://doi.org/10.22247/ijcna/2020/202977.

Vivekanand, C. V., & Bagan, K. B. (2020). Secure Distance Based Improved Leach Routing to Prevent Puea in Cognitive Radio Network. Wireless Personal Communications, 113(4), 1823–1837. https://doi.org/10.1007/s11277-020-07294-2.CrossRef

10.

Singh, K., & Verma, A. K. (2020). TBCS: A Trust Based Clustering Scheme for Secure Communication in Flying Ad-Hoc Networks. Wireless Personal Communications, 114(4), 3173–3196. https://doi.org/10.1007/s11277-020-07523-8.CrossRef

11.

Ramkumar, J., & Vadivel, R. (2020). Intelligent fish swarm inspired protocol (IFSIP) for dynamic ideal routing in cognitive radio ad-hoc networks. International Journal of Computing and Digital Systems, 10, 2–11. https://journal.uob.edu.bh/handle/123456789/3961?show=full.

12.

Li, C., & Dai, H. (2014). Throughput Scaling of Primary and Secondary Ad Hoc Networks With Same-Order Dimensions. IEEE Transactions on Vehicular Technology, 63(8), 3957–3966. https://doi.org/10.1109/TVT.2014.2310424.CrossRef

13.

Wang, C., Tang, S., Li, X., & Jiang, C. (2012). Multicast Capacity Scaling Laws for Multihop Cognitive Networks. IEEE Transactions on Mobile Computing, 11(11), 1627–1639. https://doi.org/10.1109/TMC.2011.212.CrossRef

14.

Musavi, M., Yau, K.-L. A., Syed, A. R., Mohamad, H., & Ramli, N. (2018). Route selection over clustered cognitive radio networks: An experimental evaluation. Computer Communications, 129, 138–151. https://doi.org/10.1016/j.comcom.2018.07.035.

15.

Vadivel, R., & Ramkumar, J. (2019). QoS-Enabled improved cuckoo search-inspired protocol (ICSIP) for IoT-based healthcare applications, 109–121. https://doi.org/10.4018/978-1-7998-1090-2.ch006.

16.

Dakulagi, V., & Alagirisamy, M. (2020). Adaptive Beamformers for High-Speed Mobile Communication. Wireless Personal Communications, 113(4), 1691–1707. https://doi.org/10.1007/s11277-020-07287-1.CrossRef

17.

To, M. A. (2016). A Proactive Approach for Strip Interoperability in Wireless Ad hoc Routing Protocols. IEEE Latin America Transactions, 14(6), 2543–2549. https://doi.org/10.1109/TLA.2016.7555216.CrossRef

18.

Ochola, E. O., Mejaele, L. F., Eloff, M. M., & Poll, J. A. van der. (2017). Manet reactive routing protocols node mobility variation effect in analysing the impact of black hole attack. SAIEE Africa Research Journal, 108(2), 80–92. https://doi.org/10.23919/SAIEE.2017.8531629.

19.

Ramkumar, J., & Vadivel, R. (2020). Bee inspired secured protocol for routing in cognitive radio ad hoc networks. Indian Journal of Science and Technology, 13(30), 3059–3069. https://doi.org/10.17485/IJST/v13i30.1152.

20.

Singh, K., & Moh, S. (2016). Routing protocols in cognitive radio ad hoc networks: A comprehensive review. Journal of Network and Computer Applications, 72, 28–37. https://doi.org/10.1016/j.jnca.2016.07.006.

21.

Ramkumar, J., & Vadivel, R. (2017). CSIP- cuckoo search inspired protocol for routing in cognitive radio ad hoc networks. In Advances in Intelligent Systems and Computing 556, 145–153. Springer. https://doi.org/10.1007/978-981-10-3874-7_14.

22.

Zarca, A. M., Bernabe, J. B., Skarmeta, A., & Alcaraz Calero, J. M. (2020). Virtual IoT HoneyNets to mitigate cyberattacks in SDN/NFV-Enabled IoT networks. IEEE Journal on Selected Areas in Communications, 38(6), 1262–1277. https://doi.org/10.1109/JSAC.2020.2986621.CrossRef

23.

Frustaci, M., Pace, P., Aloi, G., & Fortino, G. (2018). Evaluating critical security issues of the IoT world: Present and future challenges. IEEE Internet of Things Journal, 5(4), 2483–2495. https://doi.org/10.1109/JIOT.2017.2767291.CrossRef

24.

Said, O., Al-Makhadmeh, Z., & Tolba, A. (2020). EMS: An Energy Management Scheme for Green IoT Environments. IEEE Access, 8, 44983–44998. https://doi.org/10.1109/ACCESS.2020.2976641.CrossRef

25.

Airehrour, D., Gutierrez, J. A., & Ray, S. K. (2019). SecTrust-RPL: A secure trust-aware RPL routing protocol for Internet of Things. Future Generation Computer Systems, 93, 860–876. https://doi.org/10.1016/j.future.2018.03.021.CrossRef

26.

Jin, Y., Gormus, S., Kulkarni, P., & Sooriyabandara, M. (2016). Content centric routing in IoT networks and its integration in RPL. Computer Communications, 89–90, 87–104. https://doi.org/10.1016/j.comcom.2016.03.005.CrossRef

27.

Li, J., Silva, B. N., Diyan, M., Cao, Z., & Han, K. (2018). A clustering based routing algorithm in IoT aware wireless mesh networks. Sustainable Cities and Society, 40, 657–666. https://doi.org/10.1016/j.scs.2018.02.017.CrossRef

28.

Pan, M. S., & Yang, S. W. (2017). A lightweight and distributed geographic multicast routing protocol for IoT applications. Computer Networks, 112, 95–107. https://doi.org/10.1016/j.comnet.2016.11.006.CrossRef

29.

Vashishth, V., Chhabra, A., & Sharma, D. K. (2019). GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks. Computer Communications, 134, 138–148. https://doi.org/10.1016/j.comcom.2018.12.001.CrossRef

30.

Dhurandher, S. K., Borah, S. J., Woungang, I., Bansal, A., & Gupta, A. (2018). A location Prediction-based routing scheme for opportunistic networks in an IoT scenario. Journal of Parallel and Distributed Computing, 118, 369–378. https://doi.org/10.1016/j.jpdc.2017.08.008.CrossRef

31.

Anamalamudi, S., Sangi, A. R., Alkatheiri, M., & Ahmed, A. M. (2018). AODV routing protocol for Cognitive radio access based Internet of Things (IoT). Future Generation Computer Systems, 83, 228–238. https://doi.org/10.1016/j.future.2017.12.060.

32.

Al-Turjman, F. (2019). Cognitive routing protocol for disaster-inspired Internet of Things. Future Generation Computer Systems, 92, 1103–1115. https://doi.org/10.1016/j.future.2017.03.014.CrossRef

33.

Chemodanov, D., Esposito, F., Sukhov, A., Calyam, P., Trinh, H., & Oraibi, Z. (2019). AGRA: AI-augmented geographic routing approach for IoT-based incident-supporting applications. Future Generation Computer Systems, 92, 1051–1065. https://doi.org/10.1016/j.future.2017.08.009.CrossRef

34.

AlZubi, A. A., Al-Maitah, M., & Alarifi, A. (2019). A best-fit routing algorithm for non-redundant communication in large-scale IoT based network. Computer Networks, 152, 106–113. https://doi.org/10.1016/j.comnet.2019.01.030.CrossRef

35.

Borah, S. J., Dhurandher, S. K., Woungang, I., & Kumar, V. (2017). A game theoretic context-based routing protocol for opportunistic networks in an IoT scenario. Computer Networks, 129, 572–584. https://doi.org/10.1016/j.comnet.2017.07.005.CrossRef

36.

Sadek, R. A. (2018). Hybrid energy aware clustered protocol for IoT heterogeneous network. Future Computing and Informatics Journal, 3(2), 166–177. https://doi.org/10.1016/j.fcij.2018.02.003.MathSciNetCrossRef

37.

Qiu, T., Lv, Y., Xia, F., Chen, N., Wan, J., & Tolba, A. (2016). ERGID: An efficient routing protocol for emergency response Internet of Things. Journal of Network and Computer Applications, 72, 104–112. https://doi.org/10.1016/j.jnca.2016.06.009.CrossRef

38.

Debroy, S., Samanta, P., Bashir, A., & Chatterjee, M. (2019). SpEED-IoT: Spectrum aware energy efficient routing for device-to-device IoT communication. Future Generation Computer Systems, 93, 833–848. https://doi.org/10.1016/j.future.2018.01.002.CrossRef

39.

Cacciapuoti, A. S., Caleffi, M., & Paura, L. (2012). Reactive routing for mobile cognitive radio ad hoc networks. Ad Hoc Networks, 10(5), 803–815. https://doi.org/10.1016/j.adhoc.2011.04.004.

40.

Liu, L., Ma, Z., & Meng, W. (2019). Detection of multiple-mix-attack malicious nodes using perceptron-based trust in IoT networks. Future Generation Computer Systems, 101, 865–879. https://doi.org/10.1016/j.future.2019.07.021.CrossRef

41.

Gill, S. S., Garraghan, P., & Buyya, R. (2019, August 1). ROUTER: Fog enabled cloud based intelligent resource management approach for smart home IoT devices. Journal of Systems and Software. Elsevier Inc. https://doi.org/10.1016/j.jss.2019.04.058.

42.

Meddeb, M., Dhraief, A., Belghith, A., Monteil, T., Drira, K., & Gannouni, S. (2018). AFIRM: Adaptive forwarding based link recovery for mobility support in NDN/IoT networks. Future Generation Computer Systems, 87, 351–363. https://doi.org/10.1016/j.future.2018.04.087.CrossRef

43.

Shah, S. B., Chen, Z., Yin, F., Khan, I. U., & Ahmad, N. (2018). Energy and interoperable aware routing for throughput optimization in clustered IoT-wireless sensor networks. Future Generation Computer Systems, 81, 372–381. https://doi.org/10.1016/j.future.2017.09.043.CrossRef

44.

Safaei, B., Mohammad Salehi, A. A., Hosseini Monazzah, A. M., & Ejlali, A. (2019). Effects of RPL objective functions on the primitive characteristics of mobile and static IoT infrastructures. Microprocessors and Microsystems, 69, 79–91. https://doi.org/10.1016/j.micpro.2019.05.010.CrossRef

45.

Elappila, M., Chinara, S., & Parhi, D. R. (2018). Survivable Path Routing in WSN for IoT applications. Pervasive and Mobile Computing, 43, 49–63. https://doi.org/10.1016/j.pmcj.2017.11.004.CrossRef

46.

Wang, H., Han, G., Zhou, L., Ansere, J. A., & Zhang, W. (2019). A source location privacy protection scheme based on ring-loop routing for the IoT. Computer Networks, 148, 142–150. https://doi.org/10.1016/j.comnet.2018.11.005.CrossRef

47.

Jin, X., Zhang, R., Sun, J., & Zhang, Y. (2014). TIGHT: A geographic routing protocol for cognitive radio mobile Ad Hoc networks. IEEE Transactions on Wireless Communications, 13(8), 4670–4681. https://doi.org/10.1109/TWC.2014.2320950.CrossRef

48.

Ramkumar, J., & Vadivel, R. (2018). Improved frog leap inspired protocol (IFLIP) – for routing in cognitive radio ad hoc networks (CRAHN). World Journal of Engineering, 15(2). https://doi.org/10.1108/WJE-08-2017-0260.

49.

Shao, B., & Leeson, M. S. (2019). PaFiR: Particle Filter Routing – A predictive relaying scheme for UAV-assisted IoT communications in future innovated networks. Internet of Things. https://doi.org/10.1016/j.iot.2019.100077.CrossRef

50.

Thangaramya, K., Kulothungan, K., Logambigai, R., Selvi, M., Ganapathy, S., & Kannan, A. (2019). Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Computer Networks, 151, 211–223. https://doi.org/10.1016/j.comnet.2019.01.024.CrossRef

51.

Kabilan, K., Bhalaji, N., Selvaraj, C., Kumaar, B., & M., & P T R, K. . (2018). Performance analysis of IoT protocol under different mobility models. Computers and Electrical Engineering, 72, 154–168. https://doi.org/10.1016/j.compeleceng.2018.09.007.CrossRef

52.

Ramkumar, J., & Vadivel, R. (2019). Performance modeling of bio-inspired routing protocols in cognitive radio ad hoc network to reduce end-to-end delay. International Journal of Intelligent Engineering and Systems, 12(1), 221–231. https://doi.org/10.22266/ijies2019.0228.22.

Title: Multi-Adaptive Routing Protocol for Internet of Things based Ad-hoc Networks
Authors: J. Ramkumar
R. Vadivel
Publication date: 22-04-2021
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 2/2021
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-021-08495-z

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 2/2021

Wireless COVID-19 Telehealth: Leukocytes Encryption Guided by Amino Acid Matrix

A Biometric based Remote User Authentication Technique Using Smart Card in Multi-Server Environment

A Proficient Fair Resource Allocation in the Channel of Multiuser Orthogonal Frequency Division Multiplexing using a Novel Hybrid Bat-Krill Herd Optimization

MTLBP: A Novel Framework to Assess Multi-Tenant Load Balance in Cloud Computing for Cost-Effective Resource Allocation

A New Secure Quantum Signature Masked Authentication Scheme

Hardware Implementation of Contention Resolution in a Torus Network with Binary Optimized Routing Algorithm