本文選題：無線傳感器網絡 + 傳感器調度　； 參考：《吉林大學》2017年碩士論文

【摘要】：近年來,無線傳感器因其具有體積小和價格低廉等優(yōu)點被廣泛地應用于國防軍事、醫(yī)療健康和環(huán)境監(jiān)測等領域。但無線傳感器由電池供電,較小的體積限制其只能攜帶有限的電量,并且電池更換難度大,因此無線傳感器網絡的能耗問題一直被人們所關注,越來越多的學者投入到提高網絡能效的研究中。通過對有向傳感器網絡特點分析,提出迭代優(yōu)化休眠調度算法來解決有向傳感器網絡中的目標覆蓋問題。使用二維數組表示候選解,并隨機初始化指定數量的候選解添加到候選解集合中。重組函數根據當前候選解集合產生新的候選解,有利于豐富候選解集合的多樣性。算法先后調用調整函數和休眠函數作用于候選解集合,調整函數嘗試調整候選解中傳感器節(jié)點的感知方向來減少傳感器使用數量,從而節(jié)省能量;休眠函數是在調整函數結束后嘗試去除候選解中過多的冗余覆蓋,減少能量浪費。算法對初始候選解集合施加多輪計算、重組、調整和休眠等操作后獲取較優(yōu)問題解。通過實驗驗證,與領域內另外兩種算法對比,提出的算法能夠獲取更長的網絡生存周期。針對全向傳感器網絡的目標覆蓋問題提出多階段貪心覆蓋算法。算法主要分為三個階段,一是通過適應度函數選擇合理的傳感器節(jié)點構建覆蓋集合,適應度函數綜合考慮傳感器節(jié)點的覆蓋貢獻率、對其它目標點的覆蓋影響度、能量標準差等因素;二是針對第一步所構建的覆蓋集合進行無用覆蓋優(yōu)化,在保證完成覆蓋任務的前提下,進行半徑優(yōu)化調整來減少網絡中的無用覆蓋;三是冗余覆蓋優(yōu)化階段,在無用覆蓋優(yōu)化基礎上通過調整節(jié)點的感知半徑大小或者調整節(jié)點的工作狀態(tài)來進一步節(jié)省能量。實驗結果表明,與解決相同問題的算法相比,提出的多階段貪心覆蓋算法能獲取更長的網絡生存周期。另外,基于迭代優(yōu)化休眠調度算法和多階段貪心覆蓋算法進行了覆蓋優(yōu)化系統的設計與實現,對系統進行了需求分析及功能設計,系統大體上分為交互模塊、數據處理模塊和系統控制模塊。數據處理模塊負責對輸入的數據進行校驗和轉換等操作,便于其他模塊使用,系統控制模塊作為系統的核心,根據輸入的網絡信息進行復雜的計算。系統可以對不同場景進行快速高效的覆蓋方案計算。
[Abstract]:In recent years, wireless sensors have been widely used in military defense, medical health and environmental monitoring due to their small size and low cost. However, the wireless sensor is powered by battery, the small volume limits it can only carry a limited amount of electricity, and the battery replacement is difficult, so the problem of energy consumption in wireless sensor network has been concerned by people all the time. More and more scholars put into the research of improving network energy efficiency. By analyzing the characteristics of directed sensor networks, an iterative optimal sleep scheduling algorithm is proposed to solve the target coverage problem in directed sensor networks. A two-dimensional array is used to represent the candidate solution and a random number of candidate solutions are initialized to the candidate solution set. The recombination function generates new candidate solutions according to the current candidate solution sets, which is helpful to enrich the diversity of candidate solution sets. The algorithm successively calls the adjustment function and the sleep function to act on the candidate solution set. The adjustment function tries to adjust the sensing direction of the sensor node in the candidate solution to reduce the number of sensors used, thus saving energy. The dormant function tries to eliminate the redundant cover in the candidate solution after the end of the adjustment function and reduces the energy waste. The algorithm applies multiple rounds of computation, recombination, adjustment and hibernation to the initial set of candidate solutions to obtain the optimal solution. Compared with the other two algorithms in the domain, the proposed algorithm can obtain longer network lifetime. A multistage greedy coverage algorithm is proposed for target coverage in omnidirectional sensor networks. The algorithm is mainly divided into three stages. Firstly, the suitable sensor nodes are selected by fitness function to construct coverage set. The fitness function considers the coverage contribution rate of sensor nodes and the coverage impact on other target points. Secondly, the useless coverage is optimized according to the cover set constructed in the first step, and the radius is adjusted to reduce the useless coverage in the network on the premise of completing the coverage task. The third is redundancy coverage optimization stage, which can save energy further by adjusting the perceived radius of nodes or adjusting the working state of nodes on the basis of useless coverage optimization. Experimental results show that the proposed multi-stage greedy cover algorithm can obtain longer lifetime than the algorithm to solve the same problem. In addition, based on the iterative optimal sleep scheduling algorithm and the multi-stage greedy coverage algorithm, the design and implementation of the coverage optimization system are carried out, and the requirements and functions of the system are analyzed. The system is divided into interactive modules. Data processing module and system control module. The data processing module is responsible for the operation of checking and converting the input data, which is convenient for other modules to use. The system control module is the core of the system, and the complex calculation is carried out according to the input network information. The system can calculate the coverage scheme of different scenarios quickly and efficiently.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP212.9;TN929.5

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