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An Efficient Multi-Mobile Agent Based Data Aggregation in Wireless Sensor Networks Based on HSSO Route Planning
Karthick M, Chandru Vignesh C, Alfred Daniel J and Sivaparthipan CB

In wireless sensor networks (WSNs), for rendering a supplementary solution for conventional data collection, a mobile agent (MA) was proposed recently. Normally, finding out an optimum itinerary for the MA is a vital research problem in any MA-centred sensor network. Thus to attain effectual data gathering as of multiple sensory data source nodes, an Efficient multi-MA-based Data Aggregation (DA) in WSN centered upon HSSO route planning (EDA-HSSO) is proposed. Primarily, the MK-Means clustering algorithm clusters the sensor nodes (SN). From this generated cluster, the Cluster Head (CH) is chosen by utilizing the Improved Crow Search Algorithm (ICSA). Subsequent to CH-selection, the system plans the route discovery for collecting data as of the CH of every cluster; in addition, here, the Hybrid Salp Swarm Optimization (HSSO) algorithm is employed for route planning (RP). Ultimately, by utilizing the route discovery, the MA migration along with DA processes are done. In an investigational assessment, the proposed EDA-HSSO system’s performance is contrasted with the existing one. The proposed EDA-HSSO rendered a better performance when weighted against top-notch methodologies.

Keywords: Efficient Data Aggregation based on HSSO (EDA-HSSO), Hybrid Salp Swarm Optimization (HSSO), Improved Crow Search Algorithm (ICSA) and Modified K-Means (MK-Means) algorithm

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