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A hybrid fuzzy logic based ant colony routing optimization system for wireless communications

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Abstract

The development of information technology, wireless communications have become prevalent in every other field we can imagine. Sensor nodes are the fundamental element of wireless communication networks. When they are deployed, they gather environmental data from the surrounding area and send it to the base station for further analysis. This paper focused on creating a routing technique that improved wireless communication energy conservation through the use of fuzzy logic and ant colony optimisation in order to extend battery life. Ant colony optimisation algorithm (HFACO) and hybrid fuzzy logic were used in the construction of the routing protocol. Numerous derived techniques have been adapted to dynamic problems in real variables, stochastic problems, multi-targets, and parallel implementations. Ant colony optimisation algorithms have been applied to a wide range of combinatorial optimisation problems, from quadratic assignment to protein folding or routing vehicles. Several techniques that are based on how ant colonies forage have been used recently to solve challenging discrete optimisation problems.By taking into account the node’s energy and traffic load, fuzzy logic was utilised to determine the total node cost to the gateway. Ant colony optimisation (ACO) was used to find the shortest path between the source and destination sensor nodes, and the path’s value was determined by measuring its shortest distance. When compared to the ACO’s performance in the same conditions, the Matlab simulation’s results showed superior energy conservation performance. This improved routing technique can be applied to Wi-Fi sensor networks in industrial environments.

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Authors and Affiliations

  1. Department of Information Science and Engineering, BMS College of Engineering, Bangalore, Karnataka, India

    K. R. Radhika & S. V. Sheela

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  1. K. R. Radhika
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  2. S. V. Sheela
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Contributions

RKR—Conceptualization; Methodology; Software; Formal analysis; Writing - Original Draft. SSV—Investigation; Supervision, Project administration; Writing—Final Draft.

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Correspondence to K. R. Radhika.

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Radhika, K.R., Sheela, S.V. A hybrid fuzzy logic based ant colony routing optimization system for wireless communications. Opt Quant Electron 56, 569 (2024). https://doi.org/10.1007/s11082-023-05971-7

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