@inproceedings{Clausen2013b,
title = {Performance analysis of Trickle as a flooding mechanism},
author = {Thomas Clausen and Axel Colin de Verdiere and Jiazi Yi},
url = {http://jiaziyi.com/wp-content/uploads/2016/08/Performance-analysis-of-Trickle-as-a-flooding-mechanism.pdf
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6820439},
doi = {10.1109/ICCT.2013.6820439},
year = {2013},
date = {2013-11-01},
publisher = {IEEE 15th International Conference on Communication Technology},
abstract = {“The Trickle Algorithm” is conceived as an adaptive mechanism for allowing efficient and reliable information sharing among nodes, communicating across a lossy and shared medium. Its basic principle is, for each node, to monitor transmissions from its neighbours, compare what it receives with its cur- rent state, and schedule future transmissions accordingly: if an inconsistency of information is detected, or if few or no neighbours have transmitted consistent information “recently”, the next transmission is scheduled “soon” – and, in case consistent information from a sufficient number of neighbours is received, the next transmission is scheduled to be “later”. Developed originally as a means of distributing firmware updates among sensor devices, this algorithm has found use also for distribution of routing information in the routing protocol RPL, standardised within the IETF for maintaining a routing topology for low-power and lossy networks (LLNs). Its use is also proposed in a protocol for multicast in LLNs, denoted “Multicast Forwarding Using Trickle”. This paper studies the performance of the Trickle algorithm, as it is used in that multicast protocol.},
keywords = {Constrained Networks, lln, Performance Evaluation, rpl, Sensor Networks, Trickle},
pubstate = {published},
tppubtype = {inproceedings}
}
“The Trickle Algorithm” is conceived as an adaptive mechanism for allowing efficient and reliable information sharing among nodes, communicating across a lossy and shared medium. Its basic principle is, for each node, to monitor transmissions from its neighbours, compare what it receives with its cur- rent state, and schedule future transmissions accordingly: if an inconsistency of information is detected, or if few or no neighbours have transmitted consistent information “recently”, the next transmission is scheduled “soon” – and, in case consistent information from a sufficient number of neighbours is received, the next transmission is scheduled to be “later”. Developed originally as a means of distributing firmware updates among sensor devices, this algorithm has found use also for distribution of routing information in the routing protocol RPL, standardised within the IETF for maintaining a routing topology for low-power and lossy networks (LLNs). Its use is also proposed in a protocol for multicast in LLNs, denoted “Multicast Forwarding Using Trickle”. This paper studies the performance of the Trickle algorithm, as it is used in that multicast protocol.
