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Based On C++Wireless Sensor Nodes’ Coverage Research

Posted on:2014-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:J K WangFull Text:PDF
GTID:2248330398994192Subject:Measuring and Testing Technology and Instruments
Abstract/Summary:PDF Full Text Request
Continued technology improvements have made it possible for wireless sensornetworksto be deployed in radio technologies, integrated circuitsetc[1]. But the sensors’selection and deployment are still non-settled problems. This paper addresses somebasic measures to these problems.Due to interference between sensors and coverage redundant, there is highlydesire to identify the sensors’ coverage. But the random distributed sensors’ coveragevaries largely in every simulation, therefore interfere area is hard to compute, thepaper initially addresses convex-hull algorithm change the coverage and interferenceproblems to the sensing range problems (radius), and it also a evaluate algorithmwhich is suitable for roughly computing of the coverage when in hostile. So as toselect minimum sensors to covering the target field, this paper proposed theameliorated greedy algorithm; it changes the select schemes by the dynamic ofdirector’s demands. These algorithms are suitable either inR~2space or inR~3space.By the chance, the sensors are able to move by the instruction. The paperproposed wreath model and honeycomb model which target on the coverage of thefield after the sensors’ movement、 the interference between sensors after the sensors’movement、the length of sensors have moved and the number of the sensors selected.The paper also extends these two models to the R~3space.At last, the paper shows object-program to get the superior sensors’ networks,and adopts genetic algorithm for the analysis of the computer’s learning capability.There is no doublt, with the development of wireless technologies, the computer willbe able to evaluate the most appropriate schemes to the sensors’ selection anddeployment problems.
Keywords/Search Tags:Convex-hull algorithm, Ameliorated greedy algorithm, Select ofsensor nodes, Movement of sensor nodes, Genetic algorith
PDF Full Text Request
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