Research On Traversing Algorithm In Wireless Sensor Networks Environment

With the development of wireless sensor technology, wireless sensor networks as amonitoring tool are gradually applied to the military field. The study on anti-monitoringtechnology is also becoming increasingly important. Traversing the enemy’s monitoringarea is an important application of anti-monitoring technology. That is, when intelligencetarget travels the enemy’s sensor area, it will calculate a traversing path according toglobal or local nodes distribution information mastered in order to avoid detection andreach the destination ultimately. Because traversing and monitoring is a kind ofrelationship between ourselves and the enemy, the traversing study of how to avoid thesurveillance of the wireless network and reach destination safely is urgent and significant,and it’s also a important counter-surveillance reseach.Firstly, the reseach status about the connectivity coverage, location and routingprotocol of wireless sensor networks is summarized based on the study of a lot of relatedliteratures. Then the reseach status of anti-monitoring is generalized and some typicalanti-monitoring algorithms are close analysedSecondly, putting forward the concept of safety traversing circle by combinating thegeneration process of voronoi diagram solved the problem how to search for the nextlocation points. Then, A Path Search Algorithm Based On Safety Traversing Circle isproposed.Thirdly, the traversing model is established with a triple. And aiming at some pathedges which have high exposure, the dangerous path edges are constrainted, based ontraversing paths with voronoi subdivision in the wireless sensor area. Then the paths aresearched with A* algorithm, and then Heuristic Traversing Algorithm With ConstraintedVoronoi Division is proposed.Finally, The SASTC algorithm and HTACV algorithm are tested by simulations.Using experimental results by adjusting the experimental assessment indicators of thetraversing algorithm evaluates performance of the algorithm, and analyzes the effect fromthe degree of exposure and the length of the path for traversing behavioral And through comparison of the FDP algorithm and HTACV algorithm in exposure and the total lengthof the path, the proposed algorithm of the article has been verified.