A Review on Enhanced Routing Solutions in RPL Protocol

doi:10.23940/ijpe.21.11.p4.938945

Abstract

Abstract: Internet of Things is drawing the attention of researchers due to its wide range of applications in emerging areas. To support interoperability in IoT, IETF has proposed 6LoWPAN. Due to the hardware limitations of IoT devices, it is presenting a lot of challenges mainly related to the routing. To address the issues in routing, IETF has proposed the Routing Protocol for Low-power and Lossy Networks (RPL). In the RPL protocol, an acyclic graph is constructed to exchange the data in between nodes. The RPL protocol is widely used in different applications. Even though the RPL protocol is used in various applications, there are several drawbacks and limitations that have been exposed by recent studies. Researchers have proposed several new solutions to address these issues. This paper discusses the limitations of the RPL protocol in routing the data and solutions proposed by different researchers as well as drawbacks of the proposed methodologies by various researchers.

Key words: RPL, IoT, DODAG, rank attack, routing, DIO, DAO, DIS, DAO-ACK

Bandarupalli Rakesh and H. Parveen Sultana. A Review on Enhanced Routing Solutions in RPL Protocol [J]. Int J Performability Eng, 2021, 17(11): 938-945.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

1. Atzori L., Iera A., andMorabito G,The Internet of Things: A Survey. Computer networks, vol. 54, no. 15, pp. 2787-2805, 2010.
2. Council N.Disruptive Civil Technologies: Six Technologies with Potential Impacts on Us Interests Out to 2025; Conference Report CR; SRI Consulting Business Intelligence: Menlo Park, CA, USA, 2008.
3. Yuan L., Cheng H., andWangshun C,Building Energy Consumption Data Index Method in Cloud Computing Environment. International Journal of Performability Engineering, vol. 16, no. 5, pp. 747-756, 2020.
4. Winter T., Thubert P., Brandt A., Hui J.W., Kelsey R., Levis P., Pister K., Struik R., Vasseur J.P., andAlexander R.K,RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks. rfc, vol. 6550, pp. 1-157, 2012.
5. Iova O., Theoleyre F., andNoel T.Using Multiparent Routing in RPL to increase the Stability and the Lifetime of the Network. Ad Hoc Networks, vol. 29, pp. 45-62, 2015
6. Levis P., Clausen T., Hui J., Gnawali O., andKo J,The Trickle Algorithm (RFC 6206). InProc. Internet Engineering Task Force (IETF), pp. 1-13, March 2011.
7. Mohamed, B. and Mohamed, F.QoS Routing RPL for Low Power and Lossy Networks. International Journal of Distributed Sensor Networks, vol. 11, no. 11, pp. 971545. 2015.
8. Gara F., Saad L.B., Ayed R.B., andTourancheau B,RPL Protocol Adapted for Healthcare and Medical Applications. In 2015 International wireless communications and mobile computing conference (IWCMC). IEEE, pp. 690-695, August 2015.
9. Vasseur J.P., Kim M., Pister K., Dejean N., andBarthel D,Routing Metrics used for Path Calculation in Low-power and Lossy networks. InRFC 6551. IETF, pp. 1-30, 2012.
10. Goyal M., Baccelli E., Philipp M., Brandt A., andMartocci J.Reactive Discovery of Point-to-point Routes in Low Power and Lossy Networks.IETF Request For Comments RFC, 6997, 2013.
11. Barriquello C.H., Denardin G.W., andCampos A.A Geographic Routing Approach for IPv6 in Large-Scale Low-power and Lossy Networks. Computers & Electrical Engineering, vol. 45, pp. 182-191, 2015.
12. Zhao, M., Ho, I.W.H., and Chong, P.H.J. An Energy-efficient Region-based RPL Routing Protocol for Low-power and Lossy Networks. IEEE Internet of Things Journal, vol. 3, no. 6, pp. 1319-1333, 2016.
13. Anamalamudi S., Zhang M., Sangi A.R., Perkins C.E., andAnand S., BL Asymmetric AODV-P2P-RPL in Low-Power and Lossy Networks (LLNs). Internet-Draft draft-ietf-roll-aodv-rpl-03; Work in Progress.
14. Kelsey, R.,Hui, J.Multicast Protocol for Low-power and Lossy Networks (MPL).IETF, RFC 7731. 2016
15. Oikonomou G., Phillips I., andTryfonas T.IPv6 Multicast Forwarding in RPL-based Wireless Sensor Networks. Wireless personal communications, vol. 73, no. 3, pp.1089-1116, 2013.
16. Abdel Fadeel, K.Q., and El Sayed, K, ESMRF: Enhanced Stateless Multicast RPL Forwarding for IPv6-based Low-power and Lossy Networks. InProceedings of the 2015 Workshop on IoT challenges in Mobile and Industrial Systems, pp. 19-24, May 2015.
17. Lorente G.G., Lemmens B., Carlier M., Braeken A., andSteenhaut K,BMRF: Bidirectional Multicast RPL Forwarding. Ad Hoc Networks, vol. 54, pp. 69-84, 2017.
18. Gaddour O., Koubäa A., Rangarajan R., Cheikhrouhou O., Tovar E., andAbid M,Co-RPL: RPL Routing for Mobile Low Power Wireless Sensor Networks using Corona Mechanism. In Proceedings of the 9th IEEE international symposium on industrial embedded systems (SIES 2014), IEEE, pp. 200-209, June 2014.
19. Gaddour O., Koubâa A., andAbid M.Quality-of-service Aware Routing for Static and Mobile IPv6-based Low-power and Lossy Sensor Networks using RPL. Ad Hoc Networks, vol. 33, pp. 233-256, 2015.
20. Fotouhi H., Moreira D., andAlves, M. mRPL: Boosting Mobility in the Internet of Things.Ad Hoc Networks, vol. 26, pp. 17-35, 2015.
21. Bouaziz M., Rachedi A., andBelghith A.EKF-MRPL: Advanced Mobility Support Routing Protocol for Internet of Mobile Things: Movement Prediction Approach. Future Generation Computer Systems, vol. 93, pp. 822-832, 2019.
22. Bouaziz M., Rachedi A., Belghith A., Berbineau M., andAl-Ahmadi, S, EMA-RPL: Energy and Mobility aware Routing for the Internet of Mobile Things.Future Generation Computer Systems, vol. 97, pp. 247-258, 2019.
23. Ko, J. Jeong, J. Park, J. Jun, J.A.; Gnawali, O.Paek, J,x DualMOP-RPL: Supporting Multiple Modes of Downward Routing in a Single RPL Network. ACM Trans. Sens. Netw. (TOSN), 2015.
24. Kim H.S., Cho H., Kim H., andBahk S,DT-RPL: Diverse Bidirectional Traffic Delivery through RPL Routing Protocol in Low Power and Lossy Networks. Computer Networks, vol. 126, pp. 150-161, 2017.
25. Taghizadeh S., Bobarshad H., andElbiaze H,CLRPL: Context-aware and Load Balancing RPL for IoT Networks under Heavy and Highly Dynamic Load. IEEE Access, vol. 6, pp. 23277-23291, 2018.
26. Ancillotti E., Bruno R., andConti M.Reliable Data Delivery with the IETF Routing Protocol for Low-power and Lossy Networks. IEEE Transactions on Industrial Informatics, vol. 10, no. 3, pp.1864-1877, 2014.
27. Mohamed, B. and Mohamed, F, QoS Routing RPL for Low Power and Lossy Networks. International Journal of Distributed Sensor Networks, vol. 11, no. 11, pp. 971545, 2015.
28. Iova O., Theoleyre F., andNoel T.Using Multiparent Routing in RPL to increase the Stability and the Lifetime of the Network. Ad Hoc Networks, vol. 29, pp.45-62, 2015.
29. Abreu, C., Ricardo, M,Mendes, P.M, Energy-aware Routing for Biomedical Wireless Sensor Networks. Journal of Network and Computer Applications, vol. 40, pp. 270-278, 2014.
30. Capone S., Brama R., Accettura N., Striccoli D., andBoggia G,An Energy Efficient and Reliable Composite Metric for RPL Organized Networks. In 2014 12th IEEE International Conference on Embedded and Ubiquitous Computing. IEEE, pp. 178-184, August 2015.
31. Gaddour O., Koubâa A., Baccour N., andAbid M,OF-FL: QoS-aware Fuzzy Logic Objective Function for the RPL Routing Protocol. In 2014 12th International symposium on modeling and optimization in mobile, ad hoc, and wireless networks (WiOpt). IEEE. pp. 365-372. May 2014.
32. Gaddour O., Koubâa A., andAbid M.Quality-of-service Aware Routing for Static and Mobile IPv6-based Low-power and Lossy Sensor Networks using RPL. Ad Hoc Networks, vol. 33, pp. 233-256, 2015.
33. Kamgueu P.O., Nataf E., andDjotio T.N.On Design and Deployment of Fuzzy-based Metric for Routing in Low-power and Lossy Networks. In 2015 IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops). IEEE, pp. 789-795, October 2015.
34. Araujo H.D.S., Rodrigues, J.J., Rabelo, R.D.A., Sousa, N.D.C., and Sobral, J.V, A Proposal for IoT Dynamic Routes Selection based on Contextual Information. Sensors, vol. 18, no. 2, pp. 353, 2018.
35. Chen Y., Chanet J.P., Hou K.M., Shi H., andDe Sousa, G, A Scalable Context-aware Objective Function (SCAOF) of Routing Protocol for Agricultural Low-power and Lossy Networks (RPAL). Sensors, vol. 15, no. 8, pp.19507-19540, 2015.
36. Gozuacik, N. and Oktug, S, Parent-aware Routing for Iot Networks. In Internet of things, smart spaces, and next generation networks and systems. Springer, Cham, pp. 23-33, 2015.
37. Airehrour D., Gutierrez J.A., andRay S.K,SecTrust-RPL: A Secure Trust-aware RPL routing Protocol for Internet of Things. Future Generation Computer Systems, vol. 93, pp. 860-876, 2019.
38. Mehta, R. and Parmar, M.M, Trust based Mechanism for Securing Iot Routing Protocol rpl Against Wormhole &Grayhole Attacks. In 2018 3rd International Conference for Convergence in Technology (I2CT), IEEE, pp. 1-6, April 2018.
39. Shafique U., Khan A., Rehman A., Bashir F., andAlam M,Detection of Rank Attack in Routing Protocol for Low Power and Lossy Networks. Annals of Telecommunications, vol. 73, no. 7, pp. 429-438, 2018.

[1]	Surbhi Gupta, H.D. Aroraa, Anjali Naithania, Anil Chandrab. Reliability Assessment of the Planning and Perception Software Competencies of Self-Driving Cars [J]. Int J Performability Eng, 2021, 17(9): 779-786.
[2]	Harinee S and Anand Mahendran. Secure ECG Signal Transmission for Smart Healthcare [J]. Int J Performability Eng, 2021, 17(8): 711-721.
[3]	Azhagiri.M, Shubhanjay Mishra, Shubham Joshi, and Amritash Srivastava. An Integrated System for Initial Prediction of Autism Spectrum Disorder [J]. Int J Performability Eng, 2021, 17(6): 504-510.
[4]	Ngangbam Phalguni Singh, Sabbisetty Akhil, Ratakonda Vishnu, K. Kirit Redddy, B. Bhanu Prakash, and Shruti Suman. Investigation of Growth Management and Field Optimization on IOT-based Technology for Chilli Cultivation: Hybrid Chilli (F1 Golden Parrot) in Pallavolu, Nellore [J]. Int J Performability Eng, 2021, 17(6): 559-568.
[5]	Wen-Hsuan Liang, Dun-Wei Cheng, Chih-Wei Hsu, Chia-Wei Lee, Chih-Heng Keand, Albert Y. Zomaya, and Sun-Yuan Hsieh. Dynamic Flow Scheduling Technique for Load Balancing in Fat-Tree Data Center Networks [J]. Int J Performability Eng, 2021, 17(6): 491-503.
[6]	Vibhuti, Deepika Bhalla, and Genius Walia. Transient Finite Element Method for Computing and Analyzing the Effect of Harmonics on Hysteresis and Eddy Current Loss of Distribution Transformer [J]. Int J Performability Eng, 2021, 17(5): 451-463.
[7]	Redondin Maxime, Bouillaut Laurent, and Daucher Dimitri. EM Approach for Weibull Analysis in a Strongly Censored Data Context - Application to Road Markings [J]. Int J Performability Eng, 2021, 17(4): 333-342.
[8]	Yang Tae-Jin. Comparative Study on the Performance Attributes of NHPP Software Reliability Model based on Weibull Family Distribution [J]. Int J Performability Eng, 2021, 17(4): 343-353.
[9]	Anil Kumar Gulivindala, M.V.A. Raju Bahubalendruni, S.S.V. Prasad Varupala, and Chandrasekar Ravi. Exponential Moving Average Modelled Particle Swarm Optimization Algorithm for Efficient Disassembly Sequence Planning towards Practical Feasibility [J]. Int J Performability Eng, 2021, 17(3): 289-298.
[10]	Vuppala Swathi and Sandeep Chitreddy. Polynomial Curve Fitting-based Early Room Reflection Analysis using B-Format Room Impulse Response Measurements for Ambient Sound Reproduction [J]. Int J Performability Eng, 2021, 17(3): 307-313.
[11]	Anita Agárdi, László Kovács, and Tamás Bányai. Neutrality of Vehicle Routing Problem [J]. Int J Performability Eng, 2021, 17(10): 848-857.
[12]	Latika Kakkar, Deepali Gupta, and Sarvesh Tanwar. A Novel Certificateless Secured Signature Scheme for IoT Data in Healthcare System [J]. Int J Performability Eng, 2021, 17(10): 873-879.
[13]	Anita Agárdi, László Kovács, and Tamás Bányai. Using Time Series and Classification in Vehicle Routing Problem [J]. Int J Performability Eng, 2021, 17(1): 14-25.
[14]	Jingyuan Liu, Xu Yang, Jingang Guo, Da Wang, and Hai Zhao. Monitoring Technology of Energy Storage Power Stations based on Discharge Control Scheduling Algorithm [J]. Int J Performability Eng, 2021, 17(1): 95-102.
[15]	Wei Feng and Yuqin Wu. DDoS Attack Real-Time Defense Mechanism using Deep Q-Learning Network [J]. Int J Performability Eng, 2020, 16(9): 1362-1373.