A cooperative sequential adsorption model for wireless gossiping

T.M.M. Meyfroyt

doi:10.1145/2667522.2667535

A cooperative sequential adsorption model for wireless gossiping

T.M.M. Meyfroyt

Stochastische Besliskunde - BETA

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

1 Citaat (Scopus)

1 Downloads (Pure)

Samenvatting

Wireless sensor networks require communication protocols for efficiently maintaining data in a distributed fashion. The Trickle algorithm is a popular protocol serving as the basis for many of the current standard communication protocols. In this paper we develop a mathematical model describing how Trickle maintains data, establish a relationship with a class of spatial stochastic models known as Cooperative Sequential Adsorption (CSA). We derive asymptotic results for the coverage ratio for a specific class of CSA models and investigate the scalability of the Trickle algorithm.

Originele taal-2	Engels
Titel	32nd International Symposium on Computer Performance, Modeling, Measurement, and Evaluation (IFIP WG 7.3 Performance 2014, Torino, Italy, October 7-9, 2014)
Pagina's	40-42
DOI's	https://doi.org/10.1145/2667522.2667535
Status	Gepubliceerd - 2014

Publicatie series

Naam	ACM SIGMETRICS Performance Evaluation Review
Volume	42
ISSN van geprinte versie	0163-5999

Toegang tot document

10.1145/2667522.2667535

Vingerafdruk Duik in de onderzoeksthema's van 'A cooperative sequential adsorption model for wireless gossiping'. Samen vormen ze een unieke vingerafdruk.

Citeer dit

@inproceedings{bd14c074d4704c63ba80b00c90310f56,

title = "A cooperative sequential adsorption model for wireless gossiping",

abstract = "Wireless sensor networks require communication protocols for efficiently maintaining data in a distributed fashion. The Trickle algorithm is a popular protocol serving as the basis for many of the current standard communication protocols. In this paper we develop a mathematical model describing how Trickle maintains data, establish a relationship with a class of spatial stochastic models known as Cooperative Sequential Adsorption (CSA). We derive asymptotic results for the coverage ratio for a specific class of CSA models and investigate the scalability of the Trickle algorithm.",

author = "T.M.M. Meyfroyt",

year = "2014",

doi = "10.1145/2667522.2667535",

language = "English",

series = "ACM SIGMETRICS Performance Evaluation Review",

pages = "40--42",

booktitle = "32nd International Symposium on Computer Performance, Modeling, Measurement, and Evaluation (IFIP WG 7.3 Performance 2014, Torino, Italy, October 7-9, 2014)",

}

A cooperative sequential adsorption model for wireless gossiping. / Meyfroyt, T.M.M.

32nd International Symposium on Computer Performance, Modeling, Measurement, and Evaluation (IFIP WG 7.3 Performance 2014, Torino, Italy, October 7-9, 2014). 2014. blz. 40-42 (ACM SIGMETRICS Performance Evaluation Review; Vol. 42).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - A cooperative sequential adsorption model for wireless gossiping

AU - Meyfroyt, T.M.M.

PY - 2014

Y1 - 2014

N2 - Wireless sensor networks require communication protocols for efficiently maintaining data in a distributed fashion. The Trickle algorithm is a popular protocol serving as the basis for many of the current standard communication protocols. In this paper we develop a mathematical model describing how Trickle maintains data, establish a relationship with a class of spatial stochastic models known as Cooperative Sequential Adsorption (CSA). We derive asymptotic results for the coverage ratio for a specific class of CSA models and investigate the scalability of the Trickle algorithm.

AB - Wireless sensor networks require communication protocols for efficiently maintaining data in a distributed fashion. The Trickle algorithm is a popular protocol serving as the basis for many of the current standard communication protocols. In this paper we develop a mathematical model describing how Trickle maintains data, establish a relationship with a class of spatial stochastic models known as Cooperative Sequential Adsorption (CSA). We derive asymptotic results for the coverage ratio for a specific class of CSA models and investigate the scalability of the Trickle algorithm.

U2 - 10.1145/2667522.2667535

DO - 10.1145/2667522.2667535

M3 - Conference contribution

T3 - ACM SIGMETRICS Performance Evaluation Review

SP - 40

EP - 42

BT - 32nd International Symposium on Computer Performance, Modeling, Measurement, and Evaluation (IFIP WG 7.3 Performance 2014, Torino, Italy, October 7-9, 2014)

ER -