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Scheduling Based Data Aggregation with Hybrid Artificial Bee Colony and Monarchy Butterfly Optimization Algorithm
A. Asha, S. Gopikrishnan, Abolfazl Mehbodniya, Anita Venaik and L. Shakkeera
The principal challenges of data aggregation techniques in Wireless Sensor Networks (WSN) include energy balance, packet loss, and latency reduction. Time slots are usually assigned in existing data aggregation scheduling algorithms depending on data sensing interval and data transmission rate without taking into account the latency and packet loss. The SBDA (Scheduling Based Data Aggregation) Strategy with Hybrid Artificial Bee Colony and Monarchy Butterfly Optimization Algorithm (HABC-MBOA) for Latency as well as Packet Loss Reduction in WSN being suggested in this proposed research. Construction of the aggregation tree and the Slot Scheduling Algorithm are the two phases of the suggested methodology. The cluster head performs compressive aggregation to the data received through its own members in the first phase. The sink then constructs the aggregation tree utilizing Minimum Spanning Tree (MST). The latency as well as packet loss rate are considered in the second phase when prioritising and timeslots are assigned towards node consisting of aggregated data. This approach minimises the use of needless retransmissions and waiting, resulting in improved performance network in WSN. The proposed technique analyse the overhead reduction, latency, packet delivery ratio and residual energy, thus preserving the privacy. Simulation outcome reveal that the latency of the proposed SBDA is 19% shorter than the existing methods.
Keywords: data aggregation, scheduling algorithm, HABC-MBOA, aggregation tree