A model of route lifetime optimization with linguistic knowledge in wireless ad-hoc networks.

E. Natsheh; S. Khatun; A. Jantan

Mathware and Soft Computing (2006)

  • Volume: 13, Issue: 1, page 23-36
  • ISSN: 1134-5632

Abstract

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Ad-hoc On-Demand Distance Vector (AODV) routing protocol has been and continues to be a very active and fruitful research protocol since its introduction in the wireless ad-hoc networks. AODV uses a static value for its route lifetime parameter called Active Route Timeout (ART) which indicates the time that the route can stay active in the routing table. Route lifetime may be more accurately determined dynamically via measurement, instead of static value. To accomplish this, the fuzzy logic system is used to obtain adaptive values for ART depending on the situation of the transmitter and intermediate nodes. To study the effect of various parameters on ART, three design methods for fuzzy ART are proposed here, namely: fuzzy-SKP, fuzzy-Power, and fuzzy-Comb. Analysis shows that the proposed design methods are quite efficient and superior to the conventional design method with respect to routing overhead (25%) and average end-to-end delay (41%). Hence, the proposed fuzzy system is able to optimize ART efficiently.

How to cite

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Natsheh, E., Khatun, S., and Jantan, A.. "A model of route lifetime optimization with linguistic knowledge in wireless ad-hoc networks.." Mathware and Soft Computing 13.1 (2006): 23-36. <http://eudml.org/doc/40871>.

@article{Natsheh2006,
abstract = {Ad-hoc On-Demand Distance Vector (AODV) routing protocol has been and continues to be a very active and fruitful research protocol since its introduction in the wireless ad-hoc networks. AODV uses a static value for its route lifetime parameter called Active Route Timeout (ART) which indicates the time that the route can stay active in the routing table. Route lifetime may be more accurately determined dynamically via measurement, instead of static value. To accomplish this, the fuzzy logic system is used to obtain adaptive values for ART depending on the situation of the transmitter and intermediate nodes. To study the effect of various parameters on ART, three design methods for fuzzy ART are proposed here, namely: fuzzy-SKP, fuzzy-Power, and fuzzy-Comb. Analysis shows that the proposed design methods are quite efficient and superior to the conventional design method with respect to routing overhead (25%) and average end-to-end delay (41%). Hence, the proposed fuzzy system is able to optimize ART efficiently.},
author = {Natsheh, E., Khatun, S., Jantan, A.},
journal = {Mathware and Soft Computing},
keywords = {Redes inalámbricas; Encaminamiento de datos; Optimización; Lógica difusa; routing protocol},
language = {eng},
number = {1},
pages = {23-36},
title = {A model of route lifetime optimization with linguistic knowledge in wireless ad-hoc networks.},
url = {http://eudml.org/doc/40871},
volume = {13},
year = {2006},
}

TY - JOUR
AU - Natsheh, E.
AU - Khatun, S.
AU - Jantan, A.
TI - A model of route lifetime optimization with linguistic knowledge in wireless ad-hoc networks.
JO - Mathware and Soft Computing
PY - 2006
VL - 13
IS - 1
SP - 23
EP - 36
AB - Ad-hoc On-Demand Distance Vector (AODV) routing protocol has been and continues to be a very active and fruitful research protocol since its introduction in the wireless ad-hoc networks. AODV uses a static value for its route lifetime parameter called Active Route Timeout (ART) which indicates the time that the route can stay active in the routing table. Route lifetime may be more accurately determined dynamically via measurement, instead of static value. To accomplish this, the fuzzy logic system is used to obtain adaptive values for ART depending on the situation of the transmitter and intermediate nodes. To study the effect of various parameters on ART, three design methods for fuzzy ART are proposed here, namely: fuzzy-SKP, fuzzy-Power, and fuzzy-Comb. Analysis shows that the proposed design methods are quite efficient and superior to the conventional design method with respect to routing overhead (25%) and average end-to-end delay (41%). Hence, the proposed fuzzy system is able to optimize ART efficiently.
LA - eng
KW - Redes inalámbricas; Encaminamiento de datos; Optimización; Lógica difusa; routing protocol
UR - http://eudml.org/doc/40871
ER -

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