Abstract
The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements.
Highlights
Wireless sensor networks (WSNs) are a form of network formed by freely organizing and combining tens of thousands of sensor nodes through wireless communication technology
The each node is deployed at the intersection of gridlines and differentiated according to the proportion of parameters useddeviation, in the DEIDV-Hop experiment are shown
DEIDV-Hop proposed in this and 33 algorithms nodes are higher than the thealgorithm localization error
Summary
Wireless sensor networks (WSNs) are a form of network formed by freely organizing and combining tens of thousands of sensor nodes through wireless communication technology. On the basis of the abovementioned discussions, a wireless sensor node localization algorithm based on the improved DV-Hop and differential evolution (DE) algorithms is proposed in this paper, namely DEIDV-Hop. On the basis of the abovementioned discussions, a wireless sensor node localization algorithm based on the improved DV-Hop and differential evolution (DE) algorithms is proposed in this paper, namely DEIDV-Hop It can effectively reduce the localization error of nodes without increasing network traffic and hardware, and consists of three steps: the first two steps estimate the distance between unknown nodes and anchor nodes throughout information such as the average distance per hop and hop-count value, and the third step uses DE to determine the location of unknown nodes.
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