本文關(guān)鍵詞： 無線傳感器網(wǎng)絡(luò) 覆蓋優(yōu)化 可變步長果蠅算法 傳感器節(jié)點　出處：《安徽大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：無線傳感器網(wǎng)絡(luò)是一種分布式傳感網(wǎng)絡(luò),是由大量固定或移動的無線傳感器節(jié)點以自組織和多跳傳輸?shù)姆绞浇M成。傳感器節(jié)點采集的監(jiān)測數(shù)據(jù),可以通過逐跳的方式在多個節(jié)點之間進(jìn)行傳輸。無線傳感器網(wǎng)絡(luò)具有網(wǎng)絡(luò)設(shè)置靈活、網(wǎng)絡(luò)服務(wù)質(zhì)量高等優(yōu)點,因此廣泛應(yīng)用于軍事、智能交通、環(huán)境監(jiān)控、醫(yī)療衛(wèi)生等多個領(lǐng)域。在傳統(tǒng)的無線傳感器網(wǎng)絡(luò)中,網(wǎng)絡(luò)覆蓋和節(jié)點部署等技術(shù)已經(jīng)獲得很多的研究成果,但隨著網(wǎng)絡(luò)通信技術(shù)的快速發(fā)展,人們對于無線傳感器網(wǎng)絡(luò)的需求變得更大。傳統(tǒng)的節(jié)點部署策略就會出現(xiàn)部署速度慢,覆蓋范圍小,服務(wù)質(zhì)量差等問題。無線傳感器網(wǎng)絡(luò)節(jié)點部署主要分為可移動傳感器節(jié)點的網(wǎng)絡(luò)覆蓋和固定位置傳感器節(jié)點的網(wǎng)絡(luò)覆蓋,這兩種節(jié)點部署方式都存在一些相同的問題。例如:有些區(qū)域的節(jié)點過于密集,造成網(wǎng)絡(luò)信號覆蓋的亢余,而有的區(qū)域節(jié)點過于稀疏,造成該區(qū)域信號強(qiáng)度不夠,成為網(wǎng)絡(luò)盲區(qū)。于是,為了提高網(wǎng)絡(luò)覆蓋率和網(wǎng)絡(luò)服務(wù)質(zhì)量,通常就會通過增加節(jié)點數(shù)量的方式來實現(xiàn),結(jié)果造成一些節(jié)點冗余,資源的利用率降低,網(wǎng)絡(luò)結(jié)構(gòu)變復(fù)雜,系統(tǒng)能耗變大等問題。本論文針對這兩種節(jié)點部署方式,運用一種改進(jìn)的果蠅算法,實現(xiàn)對無線傳感器網(wǎng)絡(luò)覆蓋的優(yōu)化。目前已有多種智能算法運用在無線傳感器網(wǎng)絡(luò)的覆蓋優(yōu)化問題上,例如粒子群算法、魚群算法、遺傳算法等。但是這些算法在無線傳感器網(wǎng)絡(luò)問題上,或算法復(fù)雜度高,導(dǎo)致計算速度太慢,或算法性能差,導(dǎo)致計算結(jié)果精度太低,或算法參數(shù)太多,導(dǎo)致網(wǎng)絡(luò)模型復(fù)雜。針對這些問題,本文將改進(jìn)的果蠅算法與無線傳感器網(wǎng)絡(luò)的兩種覆蓋模型結(jié)合,通過對比試驗,驗證在無線傳感器網(wǎng)絡(luò)覆蓋優(yōu)化問題上,本文的解決方案優(yōu)于以往的解決方案,實現(xiàn)對網(wǎng)絡(luò)覆蓋的進(jìn)一步優(yōu)化。本文主要的工作集中于以下幾點:1、提出一種改進(jìn)的果蠅算法:可變步長果蠅算法。算法將整個搜索過程分為若干個周期,這樣做可以增加搜索過程的多樣性,大大減小局部收斂的可能性。其次算法在每個周期內(nèi)采用Sin(x)函數(shù),使步長在單位周期T內(nèi)可以跌宕變化。這樣既能保證算法有很強(qiáng)的全局搜索能力,可以實現(xiàn)快速收斂,又能使算法可以在小范圍內(nèi)完成高精度的搜索,結(jié)果具有更好的收斂效果。2、使用多個經(jīng)典測試函數(shù)對可變步長果蠅算法的性能進(jìn)行檢測,體現(xiàn)算法在尋優(yōu)問題上的有效性和優(yōu)越性。通過實驗結(jié)果的展示與分析,驗證了相對于其它幾種智能算法,可變步長果蠅算法具有更好的搜索性能和更高的穩(wěn)定性。3、針對可移動傳感器節(jié)點的網(wǎng)-絡(luò)覆蓋,首先建立網(wǎng)絡(luò)模型,然后結(jié)合可變步長果蠅算法提出優(yōu)化流程,在仿真環(huán)境下進(jìn)行模擬實驗,體現(xiàn)優(yōu)化方法的有效性和優(yōu)越性。通過一系列的對比試驗和數(shù)據(jù)展示,驗證了相對于其它智能算法,可變步長果蠅算法能更有效的結(jié)合可移動節(jié)點網(wǎng)絡(luò)覆蓋模型,進(jìn)一步提高網(wǎng)絡(luò)的覆蓋率,實現(xiàn)對網(wǎng)絡(luò)覆蓋的優(yōu)化。4、針對固定位置傳感器節(jié)點的網(wǎng)絡(luò)覆蓋,首先建立網(wǎng)絡(luò)模型,然后結(jié)合可變步長果蠅算法提出優(yōu)化流程,在仿真環(huán)境下進(jìn)行模擬實驗,體現(xiàn)優(yōu)化方法的有效性和優(yōu)越性。通過一系列的對比試驗和數(shù)據(jù)展示,驗證了相對于其它智能算法,可變步長果蠅算法能更有效的結(jié)合固定位置節(jié)點網(wǎng)絡(luò)覆蓋模型,進(jìn)一步提高網(wǎng)絡(luò)覆蓋率并降低網(wǎng)絡(luò)能耗,實現(xiàn)對網(wǎng)絡(luò)覆蓋的優(yōu)化。
[Abstract]:Wireless sensor network is a distributed sensor network is composed of a large number of fixed or mobile wireless sensor nodes in a self-organized and multi hop transmission mode. The monitoring data collected by sensor nodes, can be transmitted between a plurality of nodes through hop by hop. Wireless sensor network has set up a flexible network, higher quality of network service the advantages, it is widely applied to the military, intelligent transportation, environmental monitoring, medical and health fields. In traditional wireless sensor networks, network coverage and node deployment technology has obtained research results very much, but with the rapid development of network communication technology, the wireless sensor network needs to get bigger. The traditional node deployment strategy will be deployed to slow, the coverage is small and the problem of poor quality of service. The wireless sensor network node deployment is divided into Can the network coverage of mobile sensor nodes and the fixed position of the sensor node network coverage, the two nodes are some of the same questions. For example: nodes in some areas is too dense, resulting in more network coverage, and some regional nodes is too sparse, the signal intensity is not enough, the network become blind. So, in order to improve the efficiency and quality of network service overlay network, usually achieved by increasing the number of nodes, resulting in some redundant nodes, the utilization rate of resources is reduced, the network structure is complicated, the energy consumption of the system change and other issues. This thesis focuses on the two kinds of node deployment, using an improved algorithm of Drosophila and optimize coverage of wireless sensor networks. There are many intelligent algorithms used in the coverage problem of wireless sensor networks, such as particle swarm optimization Method, fish swarm algorithm, genetic algorithm and so on. But these algorithms in wireless sensor networks, or the complexity of the algorithm is high, so the calculation speed is too slow, or the algorithm performance is poor, which results in low precision, too much or cause the algorithm parameters, the models of complex networks. According to these problems, this paper will cover two the improved algorithm and the Drosophila model combined with the wireless sensor network, through the contrast test, verify the coverage problem in wireless sensor networks, the solution is better than the previous solutions, to further optimize the network coverage. This paper mainly focuses on the following points: 1, this paper proposes an improved algorithm: Drosophila a variable step algorithm. The algorithm will search the entire Drosophila process is divided into several periods, this can increase the diversity of the searching process, greatly reduce the possibility of local convergence. The second algorithm in each The Sin cycle (x) function, can make step ups and changes during the period T units. This can ensure the algorithm has strong global search ability, can achieve fast convergence, and can make the algorithm can achieve precision search in a small range,.2 has better convergence effect, the use of multiple the classic test functions on the performance of variable step algorithm for detection of Drosophila, reflect the efficiency and superiority of the algorithms in the optimization problem. And through the analysis of experimental results, verified compared with other several intelligent algorithms, a variable step search algorithm has better performance in Drosophila and higher stability of.3 for mobile sensor nodes the network coverage, first establish the network model, and then combined with the variable step algorithm is proposed to optimize the process of Drosophila melanogaster, a simulation experiment was carried out in the simulation environment, reflect the effectiveness and superiority of the optimization method. Through a series of experiments and data display, verified compared with other intelligent algorithms, a variable step algorithm with Drosophila more effective mobile node network coverage model, further improve the network coverage, to realize the optimization of.4 network coverage, according to the fixed position of the sensor node network coverage, network model is firstly established, then combined with the variable step algorithm is proposed to optimize the process of Drosophila melanogaster, a simulation experiment was carried out in the simulation environment, reflect the effectiveness and superiority of the optimization method. Through a series of experiments and data display, verified compared with other intelligent algorithms, a variable step algorithm with fixed position of Drosophila node network coverage model more effectively, further improve the network the coverage rate and reduce the energy consumption of the network, to realize the optimization of network coverage.

【學(xué)位授予單位】：安徽大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP212.9;TN929.5

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