Title :
A clustering routing protocol for wireless sensor networks based on type-2 fuzzy logic and ACO
Author :
Qi-Ye Zhang ; Ze-Ming Sun ; Feng Zhang
Author_Institution :
Sch. of Math. & Syst. Sci., Beihang Univ., Beijing, China
Abstract :
Aiming at the problem of load balancing and lifetime prolonging for wireless sensor networks (WSNs), and considering complex uncertainties existed in WSNs, this paper proposes a clustering routing protocol CRT2FLACO for WSN based on type-2 fuzzy logic and ant colony optimization (ACO). Specifically, in the cluster set-up phase, a type-2 Mamdnai fuzzy logic system (T2MFLS) is built to handle rule uncertainty better and balance the network load, in which three important factors - residual energy, the number of neighbor nodes and the distance to the base station (BS) of a node - are considered as inputs, and the probability of the node to be a candidate cluster head (CH) and the CH competition radius as outputs of our T2MFLS, to select the final CHs; in the steady-state phase, in order to reduce the transmission consumption, all the CHs are linked into a chain using ACO algorithm, then each CH send its data packet to the leader along link, which is a CH eventually transmitting packets to the BS. The simulation results show that the proposed routing protocol can effectively balance network load and reduce the transmission energy consumption of CHs, thus greatly prolong the lifetime of WSN.
Keywords :
ant colony optimisation; energy consumption; fuzzy logic; pattern clustering; routing protocols; telecommunication power management; wireless sensor networks; ACO algorithm; BS; CH competition; T2MFLS; WSN; ant colony optimization; base station; cluster head; cluster set-up phase; clustering routing protocol CRT2FLACO; data packet; network load balancing; transmission energy consumption reduction; type-2 Mamdnai fuzzy logic system; wireless sensor networks; Clustering algorithms; Fuzzy logic; Routing; Routing protocols; Uncertainty; Wireless sensor networks; Wireless sensor network; ant colony optimization; clustering algorithm; type-2 fuzzy logic; unequal competition radius;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-2073-0
DOI :
10.1109/FUZZ-IEEE.2014.6891584