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Adjusted and Robust Routing Update Algorithms for Internet of Things

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In this paper, two enhanced Trickle-based route update and maintenance algorithms for Low-Power and Lossy Networks (LLNs), called Adaptive and Robust Trickle and Adjusted-Trickle algorithms (AR-Trickle and Trickle-A) are proposed. The purpose is to tackle the main limitations of the standardized route update Trickle algorithm in this type of networks, in addition to the load-balancing problem of the IPv6 Routing Protocol for LLNs (RPL). In the proposed algorithms, new approaches for dynamically choosing the values of the redundancy coefficient (k) and the minimum interval size (Imin) are introduced. In addition, new mechanisms for skipping intervals to double the current interval size (I) are introduced. Moreover, new probabilistic approaches for transmitting and suppressing scheduled transmissions are introduced. In addition, new techniques for selecting the listen-only period and transmission window are introduced. Moreover, in order to evaluate the proposed algorithms, extensive simulation experiments have been conducted under different conditions and scenarios. The experiments results have showed that Trickle-A outperforms the standard Trickle and achieves better efficiency, with high stability, reliability, and scalability for different applications. Thanks to the stepwise approach, this algorithm follows in dealing with network variations by gradually increasing and decreasing parameters and variables values. On the other hand, AR-Trickle outperforms both Trickle-A and the standard Trickle and has achieved strong performance, by effectively reducing control-plane overhead, convergence time, and power consumption by up to 68%, 47%, and 18% respectively, while maintaining nearly the same level of reliability in term of Packet Delivery Ratio (PDR).
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IoT; Low-Power and Lossy Networks; RPL; Trickle Algorithm; Load Balancing

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J. H. Nord, A. Koohang, and J. Paliszkiewicz, The Internet of Things: Review and theoretical framework, Expert Systems with Applications, Volume 133, 2019, Pages 97-108.

S. Li, L. Da Xu, and S. Zhao, 5G Internet of Things: A survey, Journal of Industrial Information Integration, Volume 10, 2018, Pages 1-9.

M. S. Mahdavinejad, M. Rezvan, M. Barekatain, P. Adibi, P. Barnaghi, and A. P. Sheth, Machine learning for Internet of Things data analysis: A survey, Digital Communications and Networks, Volume 4, (Issue 3), 2018, Pages 161-175.

A. Nauman, Y. A. Qadri, M. Amjad, Y. B. Zikria, M. K. Afzal, and S. W. Kim, Multimedia Internet of Things: A comprehensive survey, IEEE Access, Volume 8, 2020, Pages 8202-8250.

T. Winter et al., RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks, rfc, Volume 6550, 2012, Pages 1-157.

P. Levis, T. Clausen, J. Hui, O. Gnawali, and J. Ko, The trickle algorithm, Internet Engineering Task Force, RFC6206, 2011.

P. Levis, N. Patel, D. Culler, and S. Shenker, Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks, Proc. of the 1st USENIX/ACM Symp. on Networked Systems Design and Implementation, 2004.

B. Djamaa and M. Richardson, Optimizing the trickle algorithm, IEEE Communications Letters, Volume 19, (Issue 5), 2015, pages 819-822.

C. Vallati and E. Mingozzi, Trickle-F: Fair broadcast suppression to improve energy-efficient route formation with the RPL routing protocol, Sustainable Internet and ICT for Sustainability (SustainIT), pp. 1-9, 2013.

T. M. M. Meyfroyt, M. Stolikj, and J. J. Lukkien, Adaptive broadcast suppression for Trickle-based protocols, IEEE 16th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1-9, 2015.

T. Coladon, M. Vučinić, and B. Tourancheau, Multiple redundancy constants with trickle, IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1951-1956, 2015.

B. Ghaleb, A. Y. Al-Dubai, E. Ekonomou, I. Romdhani, Y. Nasser, and A. Boukerche, A novel adaptive and efficient routing update scheme for low-power lossy networks in IoT, IEEE Internet of Things Journal, Volume 5, (Issue 6), 2018, pages 5177-5189.

M. Vučinić, M. Król, B. Jonglez, T. Coladon, and B. Tourancheau, Trickle-D: High fairness and low transmission load with dynamic redundancy, IEEE Internet of Things Journal, Volume 4, (Issue 5), 2017, pages 1477-1488.

B. Djamaa, M. R. Senouci, and A. Mellouk, Trickle++: A context-aware trickle algorithm, IEEE Global Communications Conference, pp. 1-6, 2017.

A. Musaddiq, Y. B. Zikria, and S. W. Kim, Energy-aware adaptive trickle timer algorithm for RPL-based routing in the internet of things, 28th International Telecommunication Networks and Applications Conference (ITNAC), pp. 1-6, 2018.

G. Jeong, M. Park, and J. Paek, A²-Trickle: Adaptive & Aligned Trickle for Rapid and Reliable Dissemination in Low-Power Wireless Networks, IEEE Access, Volume 8, 2020, pages 214374-214382.

A. Kumar and N. Hariharan, DCRL-RPL: Dual context-based routing and load balancing in RPL for IoT networks, IET Communications, Volume 14, (Issue 12), 2020, pages 1869-1882.

B. Bannour and A. Lapitre, Heuristic-aided symbolic simulation for trickle-based wireless sensors networks configuration, Proceedings of the Conference on Rapid Simulation and Performance Evaluation: Methods and Tools, pp. 1-7, 2020.

B. Ghaleb et al., 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, Volume 21, (Issue 2), 2018, pages 1607-1635.

S. Stoyanov, B. Ghaleb, and S. M. Ghaleb, A Comparative Performance Evaluation of A load-balancing Algorithm using Contiki:"RPL vs QU-RPL", International Journal of Advanced Trends in Computer Science and Engineering , Volume 9, (Issue 4), 2020.

H.-S. Kim, J. Paek, and S. Bahk, QU-RPL: Queue utilization based RPL for load balancing in large scale industrial applications, 12th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pp. 265-273, 2015.

A. Dunkels, B. Gronvall, and T. Voigt, Contiki-a lightweight and flexible operating system for tiny networked sensors, 29th annual IEEE international conference on local computer networks, pp. 455-462, 2004.

Bani Yassein, M., Khwaileh, E., Al Zoubi, O., An Optimized Dynamic Trickle Algorithm for Media Technology, (2020) International Journal on Communications Antenna and Propagation (IRECAP), 10 (4), pp. 277-285.

Bani Yassein, M., Bani Younes, M., Low Power Trickle (LP-Trickle) Timer Algorithm: an Improved Solution for Low Power and Lossy Network in Media Technology Context, (2020) International Journal on Communications Antenna and Propagation (IRECAP), 10 (6), pp. 393-398.

Bani Baker, Q., Bani Yassein, M., Shehadeh, H., Adaptive and Fair Route Update Algorithm for Low Power and Lossy Networks in the Internet of Things, (2020) International Journal on Communications Antenna and Propagation (IRECAP), 10 (1), pp. 58-67.


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