Improved Internet of Vehicles node heuristic K-means clustering method

The invention provides an improved Internet of Vehicles node heuristic K-means clustering method, and belongs to the technical field of Internet of Vehicles. The technical problem that an existing K-means clustering algorithm is low in operation efficiency under the conditions of numerous vehicle nodes and high-speed motion in an Internet of Vehicles system is solved. According to the technical scheme, the method comprises the following steps that S1, an edge server receives node information reported by vehicles in a nearby area; s2, immediately dividing the vehicle nodes into K initial clusters; s3, taking the vehicle closest to the central point as a cluster head node of the cluster; s4, each cluster member node creates an exclusive candidate cluster head number list; s5, stopping clustering when the sum error of the current and later iteration similarities converges to an error threshold value; s6, confirming to form a final cluster; the beneficial effects of the invention are that the method can improve t