A survey of limitations and enhancements of the ipv6 routing protocol for low-power and lossy networks: A focus on core operations
Open accessAbstract
Driven by the special requirements of the low-power and lossy networks (LLNs), the IPv6 routing protocol for LLNs (RPL) was standardized by the IETF some six years ago to tackle the routing issue in such networks. Since its introduction, however, numerous studies have pointed out that, in its current form, RPL suffers from issues that limit its efficiency and domain of applicability. Thus, several solutions have been proposed in the literature in an attempt to overcome these identified limitations. In this survey, we aim mainly to provide a comprehensive review of these research proposals assessing whether such proposals have succeeded in overcoming the standard reported limitations related to its core operations. Although some of RPL's weaknesses have been addressed successfully, the study found that the proposed solutions remain deficient in overcoming several others. Hence, the study investigates where such proposals still fall short, the challenges and pitfalls to avoid, thus would help researchers formulate a clear foundation for the development of further successful extensions in future allowing the protocol to be applied more widely.
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MQTT and WebSocket are more suitable for timely anomaly alerts due to low latency.
“MQTT and WebSocket, with their low latency, are more suitable for timely anomaly alerts.”
From Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework (2024) · cites this paper as [45]
The LLNs Routing Requirements section (p. 7) says alert traffic is highly sensitive to delay, supporting the need for timely delivery. It does not discuss MQTT or WebSocket, their latency, or whether they are more suitable for anomaly alerts; searches for both protocol names found no matching passage. (LLM, conf=0.84)
Experimental — accuracy not yet measuredCoAP is lightweight and efficient, ideal for low-latency operations but struggles with scalability in larger deployments.
“CoAP, being lightweight and efficient, is ideal for low-latency operations but struggles with scalability in larger deployments [45].”
From Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework (2024) · cites this paper as [45]
The passages on downward traffic (p. 25) and RPL deployments (p. 26) discuss scalability problems with RPL, not CoAP. Searches for CoAP, Constrained Application Protocol, and the claimed latency and scalability characteristics found no passage addressing those claims about CoAP. (LLM, conf=0.76)
Experimental — accuracy not yet measuredMQTT's reduced reliability in high-traffic scenarios may result in dropped messages.
“However, MQTT’s reduced reliability in high-traffic scenarios may result in dropped messages.”
From Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework (2024) · cites this paper as [45]
The copy discusses packet loss in RPL multipath routing (OF Enhancements Based on Multi-path Routing, p. 21), not MQTT. Searches for “MQTT” and “MQTT high traffic dropped messages” found no passage addressing MQTT reliability or dropped messages under high traffic. (LLM, conf=0.75)
Experimental — accuracy not yet measuredHTTP introduces higher latency due to inherent overhead, which can delay real-time detection.
“Protocols such as HTTP introduce higher latency due to their inherent overhead, which can delay real-time detection.”
From Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework (2024) · cites this paper as [45]
The LLNs Routing Requirements section (p. 7) says alert traffic is sensitive to delay, while the Listen Interval Oriented Enhancements section (p. 23) discusses latency caused by Trickle’s listen-only period. Searches for HTTP and protocol overhead found no passage linking HTTP’s overhead to higher latency or delayed real-time detection. (LLM, conf=0.75)
Experimental — accuracy not yet measured
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Simpson, S. (2016) · International Journal of Digital Television · doi:10.1386/jdtv.7.3.331_1 · Cited by 15 · see citing works
A Comprehensive Survey on Intrusion Detection based Machine Learning for IoT Networks
Mliki, H., Kaceam, A. H., & Fourati, L. C. (2021) · ICST Transactions on Security and Safety · doi:10.4108/eai.6-10-2021.171246 · Cited by 15 · see citing works
- Authors
- Ghaleb, B., Al-Dubai, A. Y., Ekonomou, E., Alsarhan, A., Nasser, Y., Mackenzie, L. M., & Boukerche, A.
- Affiliations
- Edinburgh Napier University (GB)
- Hashemite University (JO)
- American University of Beirut (LB)
- University of Glasgow (GB)
- University of Ottawa (CA)
- ORCID
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2019
- Volume
- 21
- Issue
- 2
- Pages
- 1607-1635
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2890378792
- Cited by
- 333
- References
- 114
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 17 · 2023: 24 · 2022: 25 · 2021: 42 · 2020: 28 · 2019: 19 · 2018: 20 · 2017: 16 · 2016: 31 · 2015: 24 · 2014: 20 · 2013: 4 · 2012: 5
- FWCI
- 16.88
- Type
- journal article
- Language
- en
- Open access
- green
- eprints.gla.ac.uk
- Licence
- Locations
- IEEE Communications Surveys & Tutorials (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- arXiv (Cornell University) (submittedVersion)
- Edinburgh Napier Research Repository (Edinburgh Napier University) (submittedVersion, cc-by)
- Research Output (Edinburgh Napier University) (submittedVersion, cc-by)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Energy Efficient Wireless Sensor Networks
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IPv6, Mobility, Handover, Networks, Security
- Physical Sciences › Computer Science › Computer Networks and Communications › Opportunistic and Delay-Tolerant Networks
- Keywords
- recurrent pregnancy loss, low-power and lossy networks, routing protocol enhancement, routing protocol extensions, energy-efficient routing, constrained networks
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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