Modelling and Simulating the Trickle Algorithm

Becker, Markus; Kuladinithi, Koojana; Görg, Carmelita

doi:10.1007/978-3-642-30422-4_10

Cited by 18 publications

(14 citation statements)

References 2 publications

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“…Due to its wide-spread use, the Trickle algorithm has been subject to many studies [8], [9], [10], [11], [12], [13], [14]. Becker et al [8] develop a model to study the propagation time of new information in a network using Laplace transforms.…”

Section: Related Workmentioning

confidence: 99%

“…A common point on published Trickle models [8], [11], [9] (and deployments) is that they all consider a unique, fixed redundancy constant among nodes. The unique redundancy constant leads to unfairness as nodes with less neighbors have less incoming packets and thus a higher probability to transmit, and will therefore deplete their available energy source sooner.…”

Section: Related Workmentioning

confidence: 99%

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Multiple redundancy constants with trickle

Coladon

Vučinić

Tourancheau

2015

2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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Wireless sensor network protocols very often use the Trickle algorithm to govern information dissemination. For example, the widely used IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) uses Trickle to emit control packets. We derive an analytical model of Trickle to take into account multiple redundancy constants and the common lack of synchronization among nodes. Moreover, we demonstrate message count unfairness when Trickle uses a unique global redundancy constant because nodes with less neighbors transmit more often. Consequently, we propose a heuristic algorithm that calculates a redundancy constant for each node as a function of its number of neighbors. Our calculated redundancy constants reduce unfairness among nodes by distributing more equally the number of transmitted messages in the network. Our analytical model is validated by emulations of constrained devices running the Contiki Operating System and its IPv6 networking stack. Furthermore, results very well corroborate the heuristic algorithm improvements.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Multiple redundancy constants with trickle

Coladon

Vučinić

Tourancheau

2015

2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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“…In [45], the authors have analysed the Trickle algorithm of the RPL routing protocol in WSNs by means of simulations and analytical models. From the obtained results, design decisions of the network size, the number of supported nodes and trade-offs for the Trickle parameters can be found.…”

Section: Communication Protocolsmentioning

confidence: 99%

Communication techniques and challenges for wireless food quality monitoring

Jedermann

Pötsch

Lloyd

2014

Phil. Trans. R. Soc. A.

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Remote measurement of product core temperature is an important prerequisite to improve the cool chain of food products and reduce losses. This paper examines and shows possible solutions to technical challenges that still hinder practical applications of wireless sensor networks in the field of food transport supervision. The high signal attenuation by water-containing products limits the communication range to less than 0.5 m for the commonly used 2.4 GHz radio chips. By theoretical analysis of the dependency of signal attenuation on the operating frequency, we show that the signal attenuation can be largely reduced by the use of 433 MHz or 866 MHz devices, but forwarding of messages over multiple hops inside a sensor network is mostly unavoidable to guarantee full coverage of a packed container. Communication protocols have to provide compatibility with widely accepted standards for integration into the global Internet, which has been achieved by programming an implementation of the constrained application protocol for wireless sensor nodes and integrating into IPv6-based networks. The sensor's battery lifetime can be extended by optimizing communication protocols and by in-network pre-processing of the sensor data. The feasibility of remote freight supervision was demonstrated by our full-scale ‘Intelligent Container’ prototype.

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“…Some analytical results are obtained in [2,11,14,15]. First, in [14], qualitative results are provided for the scalability of the Trickle algorithm, but a complete analysis is not given.…”

Section: Introductionmentioning

confidence: 99%

On the scalability and message count of Trickle-based broadcasting schemes

et al. 2015

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As the use of wireless sensor networks increases, the need for efficient and reliable broadcasting algorithms grows. Ideally, a broadcasting algorithm should have the ability to quickly disseminate data, while keeping the number of transmissions low.In this paper, we analyze the popular Trickle algorithm, which has been proposed as a suitable communication protocol for code maintenance and propagation in wireless sensor networks. We show that the broadcasting process of a network using Trickle can be modeled by a Markov chain and that this chain falls under a class of Markov chains, closely related to residual lifetime distributions. It is then shown that this class of Markov chains admits a stationary distribution of a special form. These results are used to analyze the Trickle algorithm and its message count. Our results prove conjectures made in the literature concerning the effect of a listen-only period. Besides providing a mathematical analysis of the algorithm, we propose a generalized version of Trickle, with an additional parameter defining the length of a listen-only period.

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Modelling and Simulating the Trickle Algorithm

Cited by 18 publications

References 2 publications

Multiple redundancy constants with trickle

Multiple redundancy constants with trickle

Communication techniques and challenges for wireless food quality monitoring

On the scalability and message count of Trickle-based broadcasting schemes

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