Greedy Forwarding Routing Schemes using an Improved K-Means Approach for Wireless Sensor Networks

Reducing energy consumption in wireless sensor networks (WSNs) is one of the main ways to extend network lifetime since, in most cases, sensor nodes are battery-powered and are not rechargeable. One way to achieve this goal is to reduce the amount of redundant data sent to the base station (BS) through an aggregation operation carried out by the coordinating nodes. The clustering approach is considered as one of the most energy-efficient approaches for routing data in WSNs because in this approach the cluster-heads are responsible for the aggregation of the data packets, which reduces the amount of data sent to the BS. In this paper, we propose an approach based on an improved version of the K-Means method. This approach allows to find the appropriate number of clusters and generate clusters based on the radio communication of the nodes (RC). Moreover, to send data to the BS, we propose three greedy forwarding schemes. The first is a pure greedy forwarding (DKM-GF), the second is based on the distance and the residual energy of the relay nodes (DKM-GFE) and the third on the distance, the residual energy of the relay nodes and the energy dissipated to send data from a node to the forwarding node (DKM-GF2E). The proposed routing schemes have been implemented over MATLAB simulator. The results obtained show that our proposals bring significant improvements in terms of energy consumption, network lifetime and the number of packets sent to the base station compared to other protocols.

Automated summary

Reducing energy consumption in wireless sensor networks is critical, and using a clustering approach based on an improved K-Means method with greedy forwarding schemes can effectively reduce redundant data transmissions and optimize clusters. Research results show that these schemes bring significant improvements in energy consumption, network lifetime, and the number of packets compared to other protocols.