Intelligent Water Drops Algorithm-Based Aggregation in Heterogeneous Wireless Sensor Network

This paper provides a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). When the aggregating node is utilized to transmit the data to the base station, the research attempts to show that the traffic situations of WSN may be modified appropriately by parameter tuning and algorithm modification. IWD is used to generate an optimum data aggregation tree in WSN as one of its applications. IWD assumes that all nodes in the environment are identical, resulting in identical parameter updates for all nodes. In practical scenarios, however, diverse nodes with variable beginning energy, communication range, and sensing range characteristics are deployed. In order to replicate the influence of heterogeneity in the environment, improved IID (IIWD) is offered as an enhancement to the original IID. The suggested enhancement is appropriate for scenarios in which the aggregation node is utilized to transmit data to the base station in heterogeneous configurations. In terms of residual energy, dead nodes, payload, and network lifespan, a series of simulation results demonstrates that the proposed IIWD significantly improves the accuracy and effectiveness of the IWD method in comparison.

Automated summary

This paper introduces a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). The research demonstrates that by tuning parameters and modifying algorithms, the traffic situations of WSN can be appropriately modified when the aggregating node transmits data to the base station. The proposed improvement, IIWD, takes into consideration the heterogeneity of nodes in practical scenarios, resulting in better accuracy and effectiveness compared to traditional methods in terms of residual energy, dead nodes, payload, and network lifespan.