Dynamic Optimization Algorithm Based On Irregular Partitioning Area Coverage

Wireless sensor networks have gained extensive attention in the fields of monitoring and transmission due to their advantages of convenient deployment,high precision,high reliability and high scalability.With the rapid development of sensor technology,wireless sensor networks have been widely used in all aspects of social life.Meanwhile,higher requirements are imposed on the wireless sensor network monitoring service standard.For example,the level of coverage is improved from 1 to K and specific single target coverage is enhanced to area coverage.This coverage activity in high standard is achieved by large-scale sensor node delivery.However,the delivery of too many nodes is not only easy to cause an imbalance in energy consumption but also a rapid increase in the number of overlap areas and blind areas of node sensing range.As a result,the implementation cost of wireless sensor networks will be significantly increased,and the monitoring service time will be seriously shortened.This paper studies the above issues in depth the minimum number of startup nodes required to meet the coverage requirements.The existing methods of regional regularization are reviewed,and the advantages and disadvantages of the regional division are fully analyzed.However,there are still many problems in these existing algorithm models.To address these problems,we propose an adaptive high-performance algorithm.In this paper,the comprehensive regional K-level coverage and partial regional K-level coverage are mainly discussed.The research contents and innovations of this paper are as follows:(1)The division pattern design for the irregular area.An irregular region partitioning method based on node distribution position is proposed.Specifically,the multi-intersection region between nodes is used as the basic segmentation unit,and then the scanning method is introduced,which improves the efficiency of all basic segmentation units in the calculation monitoring area,and lays a foundation for the subsequent research based on the basic segmentation unit.(2)The design for the basic segmentation unit and the node weight function.According to the different research objectives,different weight function expressions are set as an important basis for the algorithm implementation node startup order selection.The weight function design mainly refers to the coverage degree of the basic segmentation unit.In some K-level coverage,it is necessary to additionally consider the basic segmentation unit area.(3)A feasibility implementation algorithm is proposed.First,an irregular partition region coverage enhancement algorithm is proposed for comprehensive K-level coverage.Then,a distributed iterative startup algorithm is introduced for partial-region K-level coverage.The effectiveness and feasibility of the algorithm are verified by a series of simulation experiments.This paper introduces a new basic segmentation unit based on the irregular division of monitoring area.Firstly,the weight values of function for different nodes and basic segmentation units are selected according to different research objectives,and then nodes are selected sequentially to start the coverage monitoring area.In this way,the number of startup nodes is minimized.At the same time,the implementation cost of the wireless sensor network is reduced and the monitored service time is extended.