A Heuristic Algorithm for Smart Edge Sensing Device Distribution Optimization for Industrial Park

There are many sensing nodes in the industrial park system, and the amount of data uploaded at the same time is huge, the concurrency requirements are high, and the sensing loss is large. Therefore, the cloud-edge collaborative multi-processing architecture is built, which includes decentralized data aggregation of edge sensing nodes, partition data processing, and cloud data comparison. In this paper, a cloud-edge collaborative multi-processing architecture of edge sensing node decentralized data aggregation, partition data processing and cloud data comparison is constructed, and a unified point distribution principle is designed. Under the typical area scale of the multi-processing architecture, combined with the requirements of obtaining the minimum sensing devices and the maximum characteristic information in the multi-processing architecture area, the optimization design of the layout scheme was carried out based on the constraint conditions of all sensing devices in the coverage area, and the physical relationship model of the transmitted power and coverage radius of the sensing devices was constructed. Considering the deployment scheme of field sensing nodes and the coupling relationship between different indicators, a two-stage sensor location strategy based on a variety of heuristic algorithms was designed, and a two-stage location optimization method with minimum power initial location + fitness correction was proposed, which effectively reduced the coverage overlap area of regional sensing collection equipment and constructed a location energy consumption model.