Research Output

Drizzle: Adaptive and Fair Route Maintenance Algorithm for Low-power and Lossy Networks in IoT

  Low-power and Lossy Networks (LLNs) have been a
key component in the Internet of Things (IoT) paradigm. Recently,
a standardized algorithm, namely Trickle algorithm, is adopted for
routing information maintenance in such networks. This algorithm
is originally designed for disseminating code updates through a
wireless sensor network. Thus, when it comes to routing maintenance
in LLNs, Trickle suffers from some issues related to power,
convergence time, network overhead and load-distribution. In this
paper, a new algorithm for maintaining the network topology in
LLNs is developed motivated by Trickle weaknesses, namely, Drizzle
algorithm. Unlike Trickle, Drizzle uses an adaptive suppression
mechanism that permits the nodes to have different transmission
probabilities consistent with their transmission history. Another
distinctive feature of Drizzle in comparison with Trickle, is the
absence of the listen-only period from Drizzle’s intervals, thus,
leading to faster convergence time. Furthermore, a new policy
for setting the redundancy counter has been used to mitigate
the negative effect of the short-listen problem presented when
removing the listen-only period and to further boost the fairness
in the network. Our extensive simulation experiments confirm the
superiority of the proposed algorithm over Trickle under different
operating conditions.

  • Date:

    27 January 2017

  • Publication Status:


  • Dewey Decimal Classification:

    004 Data processing & computer science


Ghaleb, B., Al-Dubai, A., Romdhani, I., Nasser, Y. & Boukerche, A. (in press). Drizzle: Adaptive and Fair Route Maintenance Algorithm for Low-power and Lossy Networks in IoT. In Proceedings of IEEE ICC 2017



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Internet of Things; Low-power and Lossy Networks; RPL; Trickle Algorithm

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