本文選題：無線傳感器網(wǎng)絡(luò) + 數(shù)據(jù)融合�。� 參考：《蘭州交通大學(xué)》2017年碩士論文

【摘要】：隨著計(jì)算機(jī)技術(shù)、無線通信技術(shù)、傳感器技術(shù)以及嵌入式系統(tǒng)技術(shù)的跨越式發(fā)展,一些生產(chǎn)成本低、功耗低的微型傳感器應(yīng)運(yùn)而生;這些傳感器主要擁有對(duì)監(jiān)測(cè)目標(biāo)的感知能力、對(duì)信息數(shù)據(jù)的計(jì)算能力以及在傳感器設(shè)備之間的無線通信能力。無線傳感器網(wǎng)絡(luò)正是由這類微型傳感器節(jié)點(diǎn)以隨機(jī)或者人工的方式部署在指定的監(jiān)測(cè)區(qū)域,使用無線通信方式形成一個(gè)多跳自組織的分布式網(wǎng)絡(luò)。無線傳感器網(wǎng)絡(luò)具有大規(guī)模性、拓?fù)浣Y(jié)構(gòu)的動(dòng)態(tài)性、自組織性以及高度的應(yīng)用相關(guān)性,使得它在傳統(tǒng)的信息收集方式上帶來了一場(chǎng)根本性的變革。但是,傳感器節(jié)點(diǎn)在能量資源、設(shè)備存儲(chǔ)和計(jì)算能力等方面存在的局限性,尤其是來自能量資源約束,極大地阻礙了無線傳感網(wǎng)絡(luò)面向具有更大規(guī)模性、多樣性等應(yīng)用領(lǐng)域的發(fā)展。在初始階段,本文對(duì)基于傳統(tǒng)C/S計(jì)算模型的傳感器網(wǎng)絡(luò)隨著網(wǎng)絡(luò)規(guī)模增大時(shí)所產(chǎn)生的一系列問題進(jìn)行分析和討論;隨后,以基于Mobile Agent計(jì)算模型的無線傳感器網(wǎng)絡(luò)為研究方向展開理論分析和技術(shù)研究。本文的主要研究?jī)?nèi)容如下:首先,在基于Mobile Agent計(jì)算模型中,由于Mobile Agent對(duì)網(wǎng)絡(luò)傳感器節(jié)點(diǎn)的訪問路徑會(huì)直接影響網(wǎng)絡(luò)的能量開銷和數(shù)據(jù)融合的性能,所以本文對(duì)Mobile Agent訪問路徑的規(guī)劃方法進(jìn)行研究和改進(jìn)。在此基礎(chǔ)之上分別提出了兩種路徑規(guī)劃方法:(1)WSN中基于數(shù)據(jù)規(guī)模的Mobile Agent路徑規(guī)劃方法,該算法主要根據(jù)網(wǎng)絡(luò)各個(gè)簇的規(guī)模來確定網(wǎng)絡(luò)所需Mobile Agent的數(shù)量,進(jìn)而明確Mobile Agent對(duì)網(wǎng)絡(luò)節(jié)點(diǎn)的訪問規(guī)則。(2)WSN中基于迭代局部搜索的Mobile Agent路徑規(guī)劃方法,此算法主要針對(duì)多Agent的路徑規(guī)劃方法存在的一些問題,使用迭代局部搜索理論進(jìn)行優(yōu)化和改良。其次,Mobile Agent計(jì)算模型所使用的數(shù)據(jù)融合算法的效率對(duì)最終融合結(jié)果起著顯著作用。本文對(duì)常見的數(shù)據(jù)融合算法進(jìn)行分析和研究,在此基礎(chǔ)之上,提出一種基于數(shù)據(jù)抽樣的Mobile Agent數(shù)據(jù)融合算法;針對(duì)一些融合方法在融合效率以及精確性存在的缺陷,此算法主要從減少網(wǎng)絡(luò)數(shù)據(jù)的傳輸量、提高數(shù)據(jù)融合的精確性方面進(jìn)行完善。最后,通過在TinyOS仿真平臺(tái)TOSSIM下,對(duì)本文所提算法進(jìn)行仿真實(shí)驗(yàn)與測(cè)試;實(shí)驗(yàn)結(jié)果表明:本文算法在無線傳感器網(wǎng)絡(luò)的高效節(jié)能、均衡網(wǎng)絡(luò)負(fù)載、降低網(wǎng)絡(luò)延遲和網(wǎng)絡(luò)系統(tǒng)開銷、延長(zhǎng)網(wǎng)絡(luò)生命周期方面具有一定的合理性及有效性。
[Abstract]:With the development of computer technology, wireless communication technology, sensor technology and embedded system technology, some micro sensors with low production cost and low power consumption come into being. These sensors have the ability to perceive the target, compute the information data and wireless communication between sensor devices. Wireless sensor networks (WSN) are deployed randomly or manually in the designated monitoring area to form a multi-hop self-organized distributed network using wireless communication. Wireless sensor network (WSN) has the characteristics of large scale, dynamic topology, self-organization and high application correlation, which makes it bring a fundamental change in the traditional information collection method. However, the limitations of sensor nodes in energy resources, device storage and computing capabilities, especially due to energy resource constraints, greatly hinder the wireless sensor network facing to a larger scale. Development of applications such as diversity. In the initial stage, this paper analyzes and discusses a series of problems in sensor networks based on the traditional C / S computing model when the network size increases. The theoretical analysis and technical research of wireless sensor networks based on Mobile Agent computing model are carried out. The main contents of this paper are as follows: firstly, in the Mobile Agent computing model, the access path of Mobile Agent to sensor nodes directly affects the energy cost and data fusion performance of the network. Therefore, this paper studies and improves the planning method of Mobile Agent access path. On this basis, two kinds of path planning methods, Mobile Agent path planning method based on data scale, are proposed respectively. This algorithm mainly determines the number of Mobile Agent required by the network according to the size of each cluster in the network. Furthermore, it is clear that the Mobile Agent path planning method based on iterative local search in Mobile Agent's access rule to network nodes. This algorithm is mainly aimed at some problems existing in the path planning method of multiple Agent. The iterative local search theory is used for optimization and improvement. Secondly, the efficiency of the data fusion algorithm used in Mobile Agent model plays a significant role in the final fusion results. Based on the analysis and research of common data fusion algorithms, this paper proposes a Mobile Agent data fusion algorithm based on data sampling, aiming at the shortcomings of some fusion methods in fusion efficiency and accuracy. This algorithm is mainly improved by reducing the amount of network data transmission and improving the accuracy of data fusion. Finally, through the simulation experiments and tests on the TinyOS simulation platform TOSSIM, the experimental results show that the proposed algorithm can efficiently save energy, balance network load, reduce network delay and network system overhead in wireless sensor networks. It is reasonable and effective to extend the network life cycle.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP212.9;TN929.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 杜永文;馮珂;練云翔;;無線傳感器節(jié)點(diǎn)能量自主預(yù)測(cè)算法研究[J];微電子學(xué)與計(jì)算機(jī);2016年12期

2 屈應(yīng)照;胡曉輝;宗永勝;張榮光;;WSN中一種基于數(shù)據(jù)融合的Mobile Agent路徑規(guī)劃方法[J];傳感技術(shù)學(xué)報(bào);2016年07期

3 Zhi ZHANG;Jianxun LI;Liu LIU;;Distributed state estimation and data fusion in wireless sensor networks using multi-level quantized innovation[J];Science China(Information Sciences);2016年02期

4 張雅瓊;;基于K-Means的無線傳感網(wǎng)均勻分簇路由算法研究[J];控制工程;2015年06期

5 張美燕;蔡文郁;;融合K均值分簇MST路由的無線傳感網(wǎng)壓縮采樣技術(shù)[J];傳感技術(shù)學(xué)報(bào);2015年09期

6 李致遠(yuǎn);畢俊蕾;王汝傳;;基于移動(dòng)Agent的無線多媒體傳感器網(wǎng)絡(luò)QoS路由算法[J];傳感技術(shù)學(xué)報(bào);2013年07期

7 張亞明;史浩山;劉燕;姜飛;;WSNs中基于蟻群模擬退火算法的移動(dòng)Agent訪問路徑規(guī)劃[J];西北工業(yè)大學(xué)學(xué)報(bào);2012年05期

8 蔣暢江;石為人;唐賢倫;王平;向敏;;能量均衡的無線傳感器網(wǎng)絡(luò)非均勻分簇路由協(xié)議[J];軟件學(xué)報(bào);2012年05期

9 張海燕;劉虹;;基于K-means聚類的WSN能耗均衡路由算法[J];傳感技術(shù)學(xué)報(bào);2011年11期

10 楊庚;王安琪;陳正宇;許建;王海勇;;一種低耗能的數(shù)據(jù)融合隱私保護(hù)算法[J];計(jì)算機(jī)學(xué)報(bào);2011年05期

，

本文編號(hào)：1785352