Affiliations: [a] Computer Science Center of Technology and Urban Planning, University of State of Piaui, Teresina, PI, Brazil | [b] Applied Computer Sciences Department, University of Fortaleza, Fortaleza, Brazil | [c] Unified Teaching Center of Teresina, Teresina, PI, Brazil
Correspondence:
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Corresponding author: Ricardo A.L. Rabelo, Computer Science Center of Technology and Urban Planning, University of State of Piaui, Brazil. E-mail: [email protected]
Abstract: Wireless sensor networks (WSNs) consist of a set of sensor nodes in order to detect and transmit environmental characteristics, such as, temperature, humidity or lightness. These sensor nodes, after capturing an event, should communicate with a special node, named sink node. However, the use of a single sink node implies a bottleneck in the sensor network, specially for real time applications. To overcome this problem, researches are focusing on studies for the selection of routes in sensor networks with multiple sink nodes. The approach proposed by this paper presents the application of Genetic Fuzzy Systems (GFSs) to estimate the quality of routes in WSNs, in order to ensure communication between multiple sensor nodes and multiple sink nodes. A Mamdani Fuzzy Inference System is used to select the best sink node for communication at a given moment, based on network features such as the available energy of the route and the number of hops to reaches the sink node. Genetic Algorithms (GAs) are used to obtain the optimal setting of design parameters of the Mamdani fuzzy inference system. The proposed route classification was implemented by computer simulations to demonstrate its feasibility and the results showed a sensor network with longer lifetime, based on the appropriate selection of the sink and the route used to send packets through the network.
