本文選題：無(wú)線傳感器-執(zhí)行器網(wǎng)絡(luò) + 能效優(yōu)化��； 參考：《中南大學(xué)》2014年博士論文

【摘要】：摘要：能效優(yōu)化是無(wú)線傳感器-執(zhí)行器網(wǎng)絡(luò)(Wireless Sensor and Actuator Network, WSAN)的核心問題之一。近年來(lái),以動(dòng)態(tài)拓?fù)淇刂坪凸?jié)點(diǎn)分布式協(xié)作為基本策略的協(xié)作數(shù)據(jù)匯聚是提升WSAN能量效率的重要研究方向。本文以重載橋梁和路基長(zhǎng)期安全狀態(tài)監(jiān)測(cè)的WSAN為研究背景,采用增強(qiáng)學(xué)習(xí)、協(xié)作通信和博弈論等理論和方法,研究執(zhí)行器路徑規(guī)劃、多執(zhí)行器負(fù)載平衡和節(jié)點(diǎn)干擾抑制等問題,提出WSAN中時(shí)延約束下的能效優(yōu)化機(jī)制。主要工作包括以下幾個(gè)方面： 論文從應(yīng)用于監(jiān)測(cè)重載橋梁和路基的WSAN實(shí)例出發(fā),分析了時(shí)延約束下多執(zhí)行器WSAN能效優(yōu)化的重點(diǎn)和難點(diǎn),提出了基于移動(dòng)數(shù)據(jù)匯聚和協(xié)作通信干擾抑制的WSAN系統(tǒng)架構(gòu),首先構(gòu)建具有能量感知的動(dòng)態(tài)拓?fù)?以此為基礎(chǔ)選擇輪詢點(diǎn),再規(guī)劃執(zhí)行器采集信息的路徑；然后針對(duì)多執(zhí)行器情況,采用在線模糊Q學(xué)習(xí)方法對(duì)網(wǎng)絡(luò)進(jìn)行自適應(yīng)分區(qū),保證多個(gè)執(zhí)行器間的通信負(fù)載和能耗均衡；針對(duì)執(zhí)行器采集信息過程中相鄰節(jié)點(diǎn)間存在的數(shù)據(jù)干擾,提出基于協(xié)作通信和博弈論的干擾抑制方法。為實(shí)現(xiàn)低數(shù)據(jù)匯聚時(shí)延、高能量效率、高可靠性的WSAN提供一套有效的解決方案。 提高網(wǎng)絡(luò)能效,優(yōu)化網(wǎng)絡(luò)生存時(shí)間是WSAN的核心目標(biāo)。論文針對(duì)多跳路由數(shù)據(jù)匯聚的負(fù)載均衡問題,選擇網(wǎng)絡(luò)數(shù)據(jù)匯聚輪詢點(diǎn)。首先根據(jù)傳感器節(jié)點(diǎn)的剩余能量構(gòu)造網(wǎng)絡(luò)動(dòng)態(tài)生成樹；在全局拓?fù)湫畔⒖傻玫膱?chǎng)景下提出基于入度優(yōu)先的輪詢點(diǎn)選擇算法,在只能獲得局部拓?fù)湫畔⒌膱?chǎng)景下提出基于節(jié)點(diǎn)通信負(fù)載的輪詢點(diǎn)選擇算法。選擇的輪詢點(diǎn)作為局部網(wǎng)絡(luò)數(shù)據(jù)的匯聚點(diǎn)以分散化、區(qū)域化的方式限制網(wǎng)絡(luò)的路由跳數(shù),均衡網(wǎng)絡(luò)能耗。 針對(duì)WSAN的實(shí)時(shí)性要求,本文提出時(shí)延約束下的移動(dòng)執(zhí)行器的賽道尋優(yōu)路徑規(guī)劃算法。以輪詢點(diǎn)為執(zhí)行器路徑規(guī)劃停留的參考位置,將執(zhí)行器的路徑規(guī)劃問題轉(zhuǎn)換為旅行商問題；考慮輪詢點(diǎn)通信半徑,采用基于賽道尋優(yōu)的最近鄰點(diǎn)啟發(fā)式算法,求解執(zhí)行器遍歷所有輪詢點(diǎn)的最優(yōu)移動(dòng)軌跡；同時(shí)將網(wǎng)絡(luò)數(shù)據(jù)匯聚的時(shí)延約束轉(zhuǎn)換成執(zhí)行器的移動(dòng)距離約束,作為算法的迭代收斂條件,保證網(wǎng)絡(luò)數(shù)據(jù)匯聚實(shí)時(shí)性,并通過建立和求解空間域最優(yōu)規(guī)劃模型提供算法性能評(píng)估。 對(duì)多執(zhí)行器場(chǎng)景,論文提出一種在線模糊Q學(xué)習(xí)的能耗均衡自適應(yīng)分區(qū)算法。將每個(gè)執(zhí)行器作為具有學(xué)習(xí)和決策能力的智能體,實(shí)時(shí)獲取網(wǎng)絡(luò)中傳感器節(jié)點(diǎn)的能量和分布狀態(tài)信息；再使用模糊推理機(jī)制離散化位置和能量分布狀態(tài),構(gòu)建Q學(xué)習(xí)的狀態(tài)空間和Q函數(shù)；根據(jù)當(dāng)前的網(wǎng)絡(luò)能量分布狀態(tài)選擇具有最大回報(bào)值的分區(qū)中心位置,并產(chǎn)生對(duì)應(yīng)的Voronoi劃分,實(shí)現(xiàn)能耗均衡的分區(qū)自適應(yīng)調(diào)整。 WSAN中突發(fā)數(shù)據(jù)導(dǎo)致的相鄰節(jié)點(diǎn)間的數(shù)據(jù)發(fā)送干擾是影響數(shù)據(jù)傳輸效率的重要問題。本文提出了一種基于協(xié)作數(shù)據(jù)匯聚的干擾抑制機(jī)制。首先將協(xié)作通信技術(shù)引入WSAN,通過協(xié)作中繼轉(zhuǎn)發(fā)和協(xié)作干擾轉(zhuǎn)發(fā)的方式提升節(jié)點(diǎn)的抗干擾能力；然后考慮到節(jié)點(diǎn)自私特性,引入頻譜共享機(jī)制激勵(lì)中繼節(jié)點(diǎn)參與協(xié)作干擾抑制；采用斯坦伯格博弈方法對(duì)協(xié)作干擾抑制過程進(jìn)行分析；再通過求解博弈均衡來(lái)選擇最優(yōu)的策略進(jìn)行協(xié)作信息傳輸,得到一種干擾情況下的協(xié)作數(shù)據(jù)傳輸方法。該方法可抑制節(jié)點(diǎn)間的干擾影響,確保數(shù)據(jù)公平、合理的協(xié)作傳輸。仿真實(shí)驗(yàn)驗(yàn)證了算法的有效性。
[Abstract]:Abstract : Energy efficiency optimization is one of the core problems of Wireless Sensor and Network ( WSAN ) . In recent years , collaborative data convergence based on dynamic topology control and node distributed collaboration is an important research direction to improve the energy efficiency of WSAN .

Based on the example of WSAN applied to monitoring heavy - load bridge and subgrade , the emphasis and difficulty of energy efficiency optimization of multi - actuator WSAN under time delay constraint is analyzed . Based on the mobile data convergence and cooperative communication interference suppression WSAN system architecture , a dynamic topology with energy perception is first constructed , which can be used as the base to select the polling point and then plan the path of the actuator acquisition information .
then aiming at the multi - actuator situation , an online fuzzy Q learning method is adopted to adaptively partition the network , so that communication load and energy consumption balance among the plurality of actuators are ensured ;
In order to realize low data convergence time delay , high energy efficiency and high reliability , a set of effective solutions for WSAN with low data convergence time delay , high energy efficiency and high reliability is proposed .

In order to improve the energy efficiency of the network , optimize the network survival time is the core goal of WSAN . In this paper , the network data convergence polling point is selected according to the load balance problem of multi - hop routing data convergence . Firstly , the tree is generated according to the residual energy of the sensor node .
A polling point selection algorithm based on input priority is proposed in the context of global topological information , and a polling point selection algorithm based on the node communication load can be presented in a scenario where only local topological information can be obtained .

Aiming at the real - time requirements of WSAN , this paper proposes a path planning algorithm for the track optimization of a mobile actuator under the delay constraint . The path planning problem of the actuator is converted into a traveling salesman problem by taking the polling point as the reference position of the actuator path planning and staying .
considering the polling point communication radius , a nearest neighbor heuristic algorithm based on the track optimization is adopted to solve the optimal moving track of the executor through all polling points ;
At the same time , the delay constraint of the convergence of the network data is converted into the moving distance constraint of the actuator . As the iterative convergence condition of the algorithm , the real - time performance of the network data is guaranteed , and the algorithm performance evaluation is provided by establishing and solving the spatial domain optimal planning model .

In this paper , an adaptive partitioning algorithm for energy consumption in online fuzzy Q learning is presented in this paper . Each actuator is used as an intelligent body with learning and decision - making ability , and the energy and distribution state information of sensor nodes in the network are obtained in real time .
then the state space and the Q function of the Q learning are constructed by using the discrete positions and the energy distribution states of the fuzzy inference mechanism ;
according to the current network energy distribution state , and generating the corresponding voracious division so as to realize the partition self - adaptation adjustment of energy consumption equalization .

The data transmission interference between adjacent nodes caused by burst data in WSAN is an important problem which affects the efficiency of data transmission . In this paper , a kind of interference suppression mechanism based on cooperative data convergence is put forward . Firstly , the cooperative communication technology is introduced into WSAN , and the anti - interference ability of the node is improved by cooperative relay forwarding and cooperative interference forwarding .
then taking into account the self - private characteristic of the node , introducing a spectrum sharing mechanism to excite the relay node to participate in the cooperative interference suppression ;
The cooperative interference suppression process is analyzed by Steinberg game method .
The method can suppress the interference effect between nodes , ensure the fairness of data and reasonable cooperative transmission , and the simulation experiment verifies the effectiveness of the algorithm .

【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5;TP212.9

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