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Publication Details for Inproceedings "On Modeling Low-Power Wireless Protocols Based on Synchronous Packet Transmissions"

 

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Authors: Marco Zimmerling, Federico Ferrari, Luca Mottola, Lothar Thiele
Group: Computer Engineering
Type: Inproceedings
Title: On Modeling Low-Power Wireless Protocols Based on Synchronous Packet Transmissions
Year: 2013
Month: August
Pub-Key: ZFMT2013
Book Titel: Proceedings of the 21st IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)
Keywords: SN, synchronous transmissions, protocol modeling, Glossy, Low-Power Wireless Bus, network flooding
Publisher: IEEE
Abstract: Mathematical models play a pivotal role in understanding and designing advanced low-power wireless systems. However, the distributed and uncoordinated operation of traditional multi-hop low-power wireless protocols greatly complicates their accurate modeling. This is mainly because these protocols build and maintain substantial network state to cope with the dynamics of low-power wireless links. Recent protocols depart from this design by leveraging synchronous transmissions (ST), whereby multiple nodes simultaneously transmit towards the same receiver, as opposed to pairwise link-based transmissions (LT). ST improve the one-hop packet reliability to an extent that efficient multi-hop protocols with little network state are feasible. This paper studies whether ST also enable simple yet accurate modeling of these protocols. Our contribution to this end is twofold. First, we show, through experiments on a 139-node testbed, that characterizing packet receptions and losses as a sequence of independent and identically distributed (i.i.d.) Bernoulli trials---a common assumption in protocol modeling but often illegitimate for LT---is largely valid for ST. We then show how this finding simplifies the modeling of a recent ST-based protocol, by deriving (i) sufficient conditions for probabilistic guarantees on the end-to-end packet reliability, and (ii) a Markovian model to estimate the long-term energy consumption. Validation using testbed experiments confirms that our simple models are also highly accurate; for example, the model error in energy against real measurements is 0.25%, a figure never reported before in the related literature.
Location: San Francisco, CA, USA
Resources: [BibTeX] [ External LINK ]

 

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