Abstract
In the IoT era, the Software-Defined Wireless Sensor Networks play a crucial role. In these networks, many sensors were placed in hostile areas. Since the capabilities of the sensors has its own limits when it comes to computational and energy efficiency, it is hard to replace them once they run out of battery. So, there is an obvious need to develop an energy-efficient and Software-Defined routing system that enables us to handle wireless sensor networks with ease. This paper recommends the integration of Fork and Join Adaptive Particle Swarm Optimization (FJAPSO) along with data aggregation in the existing Software-Defined Wireless Sensor networks. This enhanced FJAPSO uses dual optimization techniques toward the optimal number of control nodes. The simulation results of enhanced FJAPSO produces a significant improvement compared to FJAPSO in optimizing the size of data to be transmitted which in turn increases the lifetime of sensor network.
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Lalitha, K., Poongodi, C., Anitha, S., Vijay Anand, D. (2021). An Energy-Efficient Routing with Particle Swarm Optimization and Aggregate Data for IOT-Enabled Software-Defined Networks. In: Udgata, S.K., Sethi, S., Srirama, S.N. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-33-6081-5_10
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DOI: https://doi.org/10.1007/978-981-33-6081-5_10
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