Dynamic Technique for Data Optimization using Artificial Bee Colonies (ABC) in Wireless Communications

Abstract

The artificial bee colony algorithm may be an effective optimization method for the acquisition
model of bees where Clustering is a good approach to provide a better route that doesn't cause
any problems when transmitting data. Also, clusters have a high degree of resemblance within
themselves but a low degree of similarity between them. For processing large dimensional data,
the usual optimization approach is ineffective. Hence, this paper introduces a novel dynamic
technique with an ABC algorithm to generate an initial population of pathways connecting the
source and destination node. Consequently, to pick a food source Employee bees linked with
explicit food sources, onlooker bees watching the movement of employee bees inside the hive
to pick a food source, and scout bees looking for food sources randomly make up the condition
of artificial bees in the ABC algorithm. Due to specific factors like network lifetime, energy
consumption, and so on, the capacity to send data over the network via a better route must be
the key aspect of Wireless Sensor Networks (WSN). Thus, the proposed framework lowers the
network energy consumption, extends the network lifetime, and improves the network
throughput.