The Internet of Things（IoT） of fiber-optic sensing has the characteristics of measurement perception and data transmission. In order to realize the fast positioning of any node in the network

a fast node positioning technology is investigated

which uses the method of boundary box optimizing the Artificial Bee Colony（ABC） algorithm. Experiments are performed on multiple unknown nodes in fiber-optic sensor networks. The performances of the proposed algorithm

the unoptimized ABC algorithm and the traditional Particle Swarm Optimization（PSO） algorithm are compared. The results show that as the population increases

the positioning accuracy of the three algorithms improves. When the population is greater than 20

it will stabilize

and the positioning accuracy is 2.2

3.0 and 3.3 m

respectively. It can be known from the number of iterations and positioning accuracy interval that the convergence speed and positioning stability of this algorithm are better than the latter two algorithms. It can be seen that the positioning technology based on this algorithm is more suitable for node positioning applications of the optical fiber sensing IoT.