DV-hop localization for local distance estimation

Among various localization techniques, the Distance Vector-Hop (DV-Hop) algorithm is favored by many researchers for its simplicity. However, the DV-Hop algorithm relies solely on discrete hop counts to estimate distances between nodes, which often results in considerable localization errors. To address this limitation, this study proposes an enhanced algorithm named Localized Distance Estimation DV-Hop (LDEDV-Hop). The algorithm introduces a novel statistical method through which it estimates the actual distance of localized hop segments by calculating the number of common nodes within the range of neighboring 1-hop, 2-hop, and 3-hop nodes, and by constructing a model of consecutive hops. This approach transforms the localized hop counts of the initial 3-hop neighborhood into precise continuous values, thereby significantly reducing distance estimation inaccuracies. The experimental results confirm the outstanding performance of the LDEDV-Hop algorithm across various network structures, showcasing its superior localization accuracy.