A model of routine lifetime optimization with linguistic knowledge in wireless ad-hoc networks
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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.
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.
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Com citar
Natsheh, Essam et al. “A model of routine lifetime optimization with linguistic knowledge in wireless ad-hoc networks”. Mathware & soft computing, vol.VOL 13, no. 1, https://raco.cat/index.php/Mathware/article/view/84933.