Skip to main content
Log in

C3P-RPL: A collaborative and proactive approach for optimal peer to peer path selection and sustenance

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Internet of Things is evolving from information gathering platforms into collaborative systems wherein, smart devices actively interact with each other in a seamless manner. For instance, Internet of Robotic Things is envisioned to provide augmented solutions through collaboration of varied smart devices and robots. These visions revolve around the ability of smart devices to directly communicate and cooperate with each other in real time. In this context, this paper is an attempt to study RPL’s (Routing Protocol for Low-power Lossy Networks) point to point routing that creates multi-hop paths between peer nodes. This standard routing protocol is known for robust and failsafe upward paths but its peer to peer (P2P) routes are reported to be suboptimal. This work assesses P2P performance of RPL’s storing mode in a network of new generation devices having higher memory. Further, a Collaborative and Proactive Peer to Peer (C3P) path selection and sustenance approach is proposed where, root node collates incremental topology from collaborative nodes and disseminates optimal single source shortest path trees SPT(n). A progressive node betweenness centrality score ensures spread out paths. Minor topology changes are accommodated through incremental node and edge updates to targeted SPT(n) locally. Storing SPTs in intermediate nodes reduces storage and packet size. Through simulations and testbed experiments, it is proven that C3P-RPL improves simultaneous peer to peer communication between all the nodes. Specifically, the path length is reduced by 30% and subsequently the network latency drops by 65% in an experimental testbed of 47 nodes, making it suitable for collaborations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Availability of data and material

The datasets are available with the authors and can be taken if required for the review process. The data would be published along with the the publication of the paper.

References

  1. Adegbija T, Rogacs A, Patel C, Gordon-Ross A (2018) Microprocessor optimizations for the internet of things: a survey. IEEE Trans Comput Aided Des Integr Circuits Syst 37(1):7–20. https://doi.org/10.1109/TCAD.2017.2717782

  2. Neelakandan S, Berlin MA, Tripathi S et al (2021) IoT-based traffic prediction and traffic signal control system for smart city. Soft Computing 25:12241–12248. https://doi.org/10.1007/s00500-021-05896-x

    Article  Google Scholar 

  3. Xu H, Yu W, Griffith D, Golmie N (2018) A survey on industrial internet of things: a cyber-physical systems perspective. IEEE Access 6:78238–78259. https://doi.org/10.1109/ACCESS.2018.2884906

    Article  Google Scholar 

  4. Wang Y, Yan H, Wan J (2016) Electronic commerce platform of manufacturing industry under industrial internet of things. In: Wan J, Humar I, Zhang D (eds) Industrial IoT Technologies and Applications. Industrial IoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-44350-8_14

  5. Winter T et al (2012) RFC 6550 - RPL: IPv6 routing protocol for low-power and lossy networks. Internet Eng. Task Force, Fremont, CA, USA. https://doi.org/10.17487/RFC6550

  6. Sobin CC (2020) A survey on architecture, protocols and challenges in IoT. Wireless Personal Comm. 112:1383–1429. https://doi.org/10.1007/s11277-020-07108-5

    Article  Google Scholar 

  7. Porcu G, Buron J, Brandt A (2010) Home automation routing requirements in low-power and lossy networks. RFC 5826, Internet Eng. Task Force. https://doi.org/10.17487/RFC5826

  8. Pister K, Phinney T, Thubert P, Pister SD, Thubert P (eds) (2009) Industrial routing requirements in low-power and lossy networks. RFC 5673, Internet Eng. Task Force. https://doi.org/10.17487/RFC5673

  9. Watteyne T, Winter T, Barthel D, Dohler M (eds) (2009) Routing requirements for urban low-power and lossy networks. RFC 5548. https://doi.org/10.17487/RFC5548

  10. Gupta M, Conta A (eds) (2006) Internet Control Message Protocol (ICMPv6) for the Internet Protocol Version 6 (IPv6) Specification. RFC 4443. https://doi.org/10.17487/RFC4443

  11. Levis P, Clausen T, Hui J, Gnawali O, Ko J (2011) The trickle algorithm. Internet Eng. Task Force, RFC 6206. https://doi.org/10.17487/RFC6206

  12. Peres B, Santos BP, de O. Souza OA, Goussevskaia O, Vieira MAM, Vieira LFM, Loureiro AAF (2018) Matrix: multihop address allocation and dynamic any-to-any routing for 6LoWPAN. Commun Netw 140:28–40. https://doi.org/10.1016/j.comnet.2018.04.017

  13. Clausen T, Herberg U, Philipp M (2011) A critical evaluation of the IPv6 routing protocol for low power and lossy networks (RPL). In: Proc IEEE Int Conf Wireless Mobile Comput Netw Commun. (WiMob), Wuhan, China. 365–372. https://doi.org/10.1109/WiMOB.2011.6085374

  14. Kim H, Ko J, Culler DE, Paek J (2017) Challenging the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL): a survey. IEEE Comm. Surveys & Tutorials 19(4):2502–2525. https://doi.org/10.1109/COMST.2017.2751617

    Article  Google Scholar 

  15. Goyal M, Baccelli E, Philipp M, Brandt A, Martocci J (2013) Reactive discovery of pointtopoint routes in low-power and lossy networks. RFC 6997. https://doi.org/10.17487/RFC6997

  16. Kim Y, Paek J (2020) NG-RPL for efficient P2P routing in low-power multi-hop wireless networks. IEEE Access 8:182591–182599

    Article  Google Scholar 

  17. Mahyoub M, Mahmoud ASH, Abu-Amara M, Sheltami TR (2021) An efficient RPL-based mechanism for node-to-node communications in IoT. IEEE Internet Things J 8(9):7152–7169. https://doi.org/10.1109/JIOT.2020.3038696

  18. Ghaleb B, Al-Dubai AY, Ekonomou E, Alsarhan A, Nasse Y, Mackenzie LM, Boukerche A (2019) A survey of limitations and enhancements of the IPv6 routing protocol for low-power and lossy networks: a focus on core operation. IEEE Commun Surv Tutorials 21(2):1605–1635. https://doi.org/10.1109/COMST.2018.2874356

    Article  Google Scholar 

  19. Kamgueu PO, Nataf E, Ndie TD (2018) Survey on RPL enhancements: a focus on topology, security and mobility. Comput Commun 120:10–21. https://doi.org/10.1016/j.comcom.2018.02.011

    Article  Google Scholar 

  20. Zhao M, Kumar A, Ristaniemi T, Chong PHJ (2017) Machine-to-machine communication and research challenges: a survey. Wireless Pers Commun 97:3569–3585. https://doi.org/10.1007/s11277-017-4686-1

  21. Wang Z, Zhang L, Zheng Z, Wang J (2018) Energy balancing RPL protocol with multipath for wireless sensor networks. Peer-to-Peer Netw Appl 11:1085–1100. https://doi.org/10.1007/s12083-017-0585-1

    Article  Google Scholar 

  22. Nesary Moghadam M, Taheri H, Karrari M (2014) Minimum cost load balanced multipath routing protocol for low power and lossy networks. Wirel Netw 20:2469–2479. https://doi.org/10.1007/s11276-014-0753-7

  23. Pushpa Mettilsha J, Sandhya MK, Murugan K (2021) RPR: reliable path routing protocol to mitigate congestion in critical IoT applications. Wirel Netw 27:5229–5243. https://doi.org/10.1007/s11276-021-02805-w

    Article  Google Scholar 

  24. Kim H, Paek J, Bahk S (2015) QU-RPL: queue utilization based RPL for load balancing in large scale industrial applications. 2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), pp 265–273. https://doi.org/10.1109/SAHCN.2015.7338325

  25. Gan W, Shi Z, Zhang C, Sun L, Ionescu D (2013) MERPL: a more memory-efficient storing mode in RPL. 2013 19th IEEE International Conference on Networks (ICON). pp 1–5. https://doi.org/10.1109/ICON.2013.6781985

  26. Ko J, Jeong J, Park J, Jun JA, Paek J (2015) DualMOP-RPL: supporting multiple modes of downward routing in a single RPL Network. ACM Trans Sens Netw 11(2):1–20. https://doi.org/10.1145/2700261

  27. Farooq MO, Pesch D (2018) ERPL: an enhanced peer-to-peer routing mechanism for low-power and lossy networks. 11th IFIP Wireless and Mobile Networking Conference (WMNC). pp. 1–8. https://doi.org/10.23919/WMNC.2018.8480918

  28. Kiraly C, Istomin T, Iova O, Picco GP (2015) D-RPL: overcoming memory limitations in RPL point-to-multipoint routing. 2015 IEEE 40th Conference on Local Computer Networks (LCN). pp. 157–160. https://doi.org/10.1109/LCN.2015.7366295

  29. Zhong X, Liang Y (2019) Scalable downward routing for wireless sensor networks actuation. IEEE Sensors J 19(20):9552–9560. https://doi.org/10.1109/JSEN.2019.2924153

    Article  Google Scholar 

  30. Rojas E, Hosseini H, Gomez C, Carrascal D, Cotrim JR (2021) Outperforming RPL with scalable routing based on meaningful MAC addressing. Ad Hoc Netw 114:1570–8705. https://doi.org/10.1016/j.adhoc.2021.102433

    Article  Google Scholar 

  31. Zhao M, Ho IW, Chong PHJ (2016) An energy-efficient region-based RPL Routing Protocol for Low-Power and Lossy networks. IEEE Internet Things J 3(6):1319–1333. https://doi.org/10.1109/JIOT.2016.2593438

    Article  Google Scholar 

  32. Baccelli E, Philipp M, Goyal M (2011) The P2P-RPL routing protocol for IPv6 sensor networks: testbed experiments. In: Proceedings of the International Conference on Software, Telecommunications and Computer Networks (SoftCOM), Split, Croatia. pp. 1–6

  33. Zhao M, Kumar A, Joo Chong PH et al (2017) A comprehensive study of RPL and P2P-RPL routing protocols: implementation, challenges and opportunities. Peer-to-Peer Netw Appl 10:1232–1256. https://doi.org/10.1007/s12083-016-0475-y

    Article  Google Scholar 

  34. Perkins CE, Anand SVR, Anamalamudi S, Liu BR (2022) Supporting asymmetric links in low power networks: AODV-RPL. https://datatracker.ietf.org/doc/draft-ietf-roll-aodv-rpl/14/

  35. Djamaa B, Senouci MR, Bessas H, Dahmane B, Mellouk A (2021) Efficient and stateless P2P routing mechanisms for the internet of things. IEEE Internet Things J 8(14):11400–11414. https://doi.org/10.1109/JIOT.2021.3053339

  36. Sharifian Z, Barekatain B, Quintana AA, Beheshti Z, Esfahani FS (2022) LOADng-AT: a novel practical implementation of hybrid HP-TOPSIS algorithm in reactive routing protocol for intelligent IoT-based networks. J Supercomput 78:9521–9569. https://doi.org/10.1007/s11227-021-04256-8

    Article  Google Scholar 

  37. Zrelli A (2022) Hardware, software platforms, operating systems and routing protocols for internet of things applications. Wirel Pers Commun 122:3889–3912. https://doi.org/10.1007/s11277-021-09116-5

    Article  Google Scholar 

  38. Skiena S (2010) The algorithm design manual, 2nd edn. Springer-Verlag. https://doi.org/10.1007/978-1-84800-070-4

  39. Ramalingam G, Reps TW (1996) On the computational complexity of dynamic graph problems. Theor Comput Sci 158(1 and 2):233–277 

  40. Slobbe A, Bergamini E, Meyerhenke H (2016) Faster incremental all-pairs shortest paths. https://doi.org/10.13140/RG.2.1.3692.2005

  41. Adjih C, Baccelli E, Fleury E, Harter G, Mitton N, Noel T, Pissard-Gibollet R, Saint-Marcel F, Schreiner G, Vandaele J, Watteyne T (2015) FIT IoT-LAB: a large scale open experimental IoT testbed. IEEE World Forum on Internet of Things (IEEE WF-IoT). pp. 459–464. https://doi.org/10.1109/WF-IoT.2015.7389098

  42. Texas Instruments (2022) MSP430F5 series mixed-signal micro controllers. https://www.ti.com/lit/gpn/msp430f5437. Accessed 1 Mar 2022. Between the Conclusions and Reference

  43. Texas Instruments (2022) CC2520 2.5 GHZ IEEE 802.15.4 RF Transceiver. https://www.ti.com/lit/gpn/cc2520. Accessed 01 March 2022

  44. Contiki Operating System (2022) https://github.com/contiki-os/contiki. Accessed 1 Mar 2022

  45. AT86RF231, a low power 2.4 GHz transceiver designed for industrial and consumer IEEE 802.15.4, ZigBee, RF4CE, SP100, WirelessHART™, ISM, and high data rate applications. https://www.microchip.com/en-us/product/AT86RF231. Accessed 1 Mar 2022

  46. Arm Cortex-M3 MCU with 512 Kbytes of Flash memory, 72 MHz CPU, motor control, USB and CAN. https://www.st.com/en/microcontrollers-microprocessors/stm32f103re.html. Accessed 1 Mar 2022

  47. Dunkels A (2011) The ContikiMAC radio duty cycling protocol. SICS Technical Report, T2011:13, ISSN: 1100-3154

Download references

Acknowledgements

We would like offer our sincere gratitude to FIT IoT-LAB for their excellent testbed infrastructure and in-house tools for making it very convenient to use. We thank the team for the access and also for the prompt response to queries.

Author information

Authors and Affiliations

Authors

Contributions

T.Anusha: Conceptualization, Methodology, Software, Visualization, Validation and Writing manuscript. M.Pushpalatha: Methodology, Formal Analysis, Validation, Critical review and Supervision.

Corresponding author

Correspondence to T. Anusha.

Ethics declarations

Ethical approval and consent to participate

This research work does not involve any human participants and / or animals.

Consent for publication

All authors agree with the content and both of them has given their explicit consent to submit.

Human and animal ethics

This research work does not involve any human participants and/or animals.

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Anusha, T., Pushpalatha, M. C3P-RPL: A collaborative and proactive approach for optimal peer to peer path selection and sustenance. Peer-to-Peer Netw. Appl. 16, 914–931 (2023). https://doi.org/10.1007/s12083-023-01447-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-023-01447-3

Keywords

Navigation