本文選題：無線傳感器網(wǎng)絡(luò) + 節(jié)能路由協(xié)議��； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless sensor networks,WSNs)是由分布在其中的傳感器節(jié)點通過自組織過程形成的網(wǎng)絡(luò),節(jié)點通過相互之間的通信共同完成對網(wǎng)絡(luò)中監(jiān)測對象的相關(guān)數(shù)據(jù)信息的采集和處理,并將采集處理后信息傳送給觀察者。自對無線傳感器網(wǎng)絡(luò)的研究開始,這一課題就引起了各界極大的關(guān)注。由于傳感器節(jié)點體較小、構(gòu)造簡單,無法保證充足的電池能量,加上傳感器網(wǎng)絡(luò)常用于一些特殊的場景中,環(huán)境惡劣甚至人跡罕至,電池能量無法得到及時補(bǔ)充或更換,因此如何最大程度上減少能耗是無線傳感器網(wǎng)絡(luò)重點關(guān)注的問題之一。元胞自動機(jī)(Cellular automata,CA)是一種時間和空間均離散的系統(tǒng),且每個元胞都有有限個離散狀態(tài),元胞下一時刻的狀態(tài)由當(dāng)前時刻自身以及鄰居元胞的狀態(tài)共同決定,所有元胞遵守同一個狀態(tài)轉(zhuǎn)換規(guī)則,元胞自動機(jī)能夠以簡單的規(guī)則實現(xiàn)復(fù)雜的整體特性。將元胞自動機(jī)和無線傳感器網(wǎng)絡(luò)相比擬,傳感器節(jié)點類似于元胞,節(jié)點根據(jù)與鄰近節(jié)點通信獲得的局部信息決定自身下一時刻的行為,實現(xiàn)網(wǎng)絡(luò)的整體特性。在節(jié)能方面,WSN網(wǎng)絡(luò)同元胞自動機(jī)模型同樣具有相似之處,節(jié)點通過執(zhí)行特定的協(xié)議控制自身的工作狀態(tài),延長睡眠時間,減少能量消耗。因此,利用元胞自動機(jī)模型來解決傳感器網(wǎng)絡(luò)的能耗問題是十分有效的方法。本文研究了基于元胞自動機(jī)模型的WSN節(jié)能路由協(xié)議,設(shè)計了基于元胞自動機(jī)模型的節(jié)能路由協(xié)議AODV-ECA和GAF-CA。傳統(tǒng)的基于元胞自動機(jī)模型的AODV路由協(xié)議中節(jié)點分布不夠靈活,以“生命游戲”作為狀態(tài)轉(zhuǎn)換規(guī)則,未考慮節(jié)點能量狀態(tài),會導(dǎo)致個別處于低能狀態(tài)的節(jié)點過度工作致能量耗盡,形成網(wǎng)絡(luò)分割。AODV-ECA協(xié)議針對此問題引入不規(guī)則元胞自動機(jī)模型,使節(jié)點能夠隨機(jī)分布在網(wǎng)絡(luò)中,并在制定狀態(tài)轉(zhuǎn)換規(guī)則時考慮節(jié)點的剩余能量,提高了能量均衡性。GAF-CA協(xié)議針對GAF協(xié)議中簇頭選舉方法存在的問題進(jìn)行了改進(jìn),節(jié)點無需掌握復(fù)雜的全局信息,避免發(fā)送大量測試信息,自發(fā)完成簇頭選舉,降低了網(wǎng)絡(luò)開銷。對改進(jìn)后的協(xié)議在NS2網(wǎng)絡(luò)仿真工具下進(jìn)行仿真分析,與改進(jìn)前的協(xié)議進(jìn)行性能比較,通過對節(jié)點剩余能量、網(wǎng)絡(luò)總能量消耗以及網(wǎng)絡(luò)生存時間等方面性能指標(biāo)的比較,驗證本文提出的新協(xié)議的有效性和優(yōu)越性。
[Abstract]:Wireless sensor Networks (WSNs) is a network formed by the sensor nodes distributed among them through self-organizing process. The nodes work together to complete the collection and processing of the relevant data information of the monitoring objects in the network through the communication between the nodes. The collected and processed information is transmitted to the observer. Since the beginning of the research on wireless sensor networks, this subject has attracted great attention from all walks of life. Because the sensor node is small and simple, it can not guarantee sufficient battery energy. Besides, sensor network is often used in some special scenarios, the environment is bad or even people are not available, so the battery energy can not be replenished or replaced in time. Therefore, how to minimize energy consumption is one of the most important issues in wireless sensor networks. Cellular automata (CA) is a system with discrete time and space, and each cell has a finite number of discrete states. The state of the next moment of the cell is determined by the state of the current moment and that of the neighbor cell. All cells follow the same state transition rule, and cellular automata can achieve complex global properties with simple rules. Comparing cellular automata with wireless sensor networks, sensor nodes are similar to cellular nodes. Nodes decide their own behavior at the next moment according to the local information obtained from communication with neighboring nodes, and realize the overall characteristics of the network. In the aspect of energy saving, the cellular automata model of WSN network is similar. Nodes control their working state by executing specific protocols, prolong sleep time and reduce energy consumption. Therefore, using cellular automata model to solve the problem of sensor network energy consumption is a very effective method. In this paper, WSN energy-saving routing protocol based on cellular automata model is studied, and AODV-ECA and GAF-CA-based energy-saving routing protocols based on cellular automata model are designed. The traditional AODV routing protocol based on cellular automata model is not flexible enough to distribute nodes, and takes "game of life" as the rule of state transition, and does not consider the state of node energy. It will lead to excessive work of individual nodes in low energy state and lead to energy depletion. AODV-ECA protocol introduces irregular cellular automata model to solve this problem, which enables nodes to be randomly distributed in the network. Considering the residual energy of the node, the GAF-CA protocol improves the energy balance and improves the problem of cluster head selection method in GAF protocol. The node does not need to master complex global information. Avoiding sending a large amount of test information and spontaneously completing cluster head election, the network overhead is reduced. The improved protocol is simulated and analyzed under the NS2 network simulation tool. The performance of the improved protocol is compared with that of the improved protocol. The performance indexes of the node residual energy, the total energy consumption of the network and the network lifetime are compared. The validity and superiority of the proposed new protocol are verified.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN929.5;TP212.9

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本文編號：1948120