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能量感知的無(wú)線傳感器網(wǎng)絡(luò)路由算法研究

發(fā)布時(shí)間:2019-02-20 20:53
【摘要】:無(wú)線傳感器網(wǎng)絡(luò)采用自組織的方式將數(shù)量眾多的造價(jià)低廉、運(yùn)行能耗較低的微型傳感器節(jié)點(diǎn)構(gòu)建成網(wǎng)絡(luò),實(shí)現(xiàn)對(duì)目標(biāo)檢測(cè)區(qū)域各種信息的實(shí)時(shí)感知、監(jiān)測(cè)和采集,并對(duì)采集到的數(shù)據(jù)進(jìn)行處理分析。無(wú)線傳感器節(jié)點(diǎn)具有使用方便靈活、穩(wěn)定性強(qiáng)、擴(kuò)展方便、經(jīng)濟(jì)性好、安全可靠等特點(diǎn),在軍事監(jiān)控、系統(tǒng)控制、醫(yī)療衛(wèi)生和環(huán)境監(jiān)測(cè)以及其他行業(yè)都得到了廣泛的推廣,受到各行各業(yè)研究開(kāi)發(fā)人員的高度重視。在實(shí)際開(kāi)發(fā)應(yīng)用中還存在著許多影響網(wǎng)絡(luò)進(jìn)行大規(guī)模推廣的障礙。例如:在網(wǎng)絡(luò)的使用過(guò)程中,需要進(jìn)行部署的傳感器節(jié)點(diǎn)數(shù)量眾多,且位置隨機(jī)、監(jiān)測(cè)環(huán)境復(fù)雜,這使得部分節(jié)點(diǎn)在運(yùn)行過(guò)程中能量消耗劇烈,會(huì)造成能量很快消耗殆盡,節(jié)點(diǎn)停止工作;網(wǎng)絡(luò)進(jìn)行大范圍監(jiān)測(cè)時(shí),要使用大量的節(jié)點(diǎn)進(jìn)行部署,造成整體成本較高,影響網(wǎng)絡(luò)的推廣與普及;在實(shí)際部署中,傳感器節(jié)點(diǎn)往往使用電池為節(jié)點(diǎn)進(jìn)行供電,節(jié)點(diǎn)的微型化發(fā)展使得電池容量受到限制,而且節(jié)點(diǎn)數(shù)量的巨大會(huì)造成對(duì)節(jié)點(diǎn)進(jìn)行電池更換十分不便。通過(guò)采用能量模型優(yōu)化策略對(duì)網(wǎng)絡(luò)進(jìn)行研究,從網(wǎng)絡(luò)路由拓?fù)涑霭l(fā),為建立高效、節(jié)能的網(wǎng)絡(luò)提供新的思路。針對(duì)網(wǎng)絡(luò)能耗不均衡問(wèn)題,根據(jù)不同類型的應(yīng)用特點(diǎn),綜合節(jié)點(diǎn)能耗模型和多路徑路由技術(shù),對(duì)節(jié)點(diǎn)剩余時(shí)間預(yù)測(cè)、網(wǎng)絡(luò)拓?fù)、時(shí)間同步進(jìn)行研究。(1)能量模型方面,將組成CC2530傳感器節(jié)點(diǎn)的各個(gè)模塊能量消耗特點(diǎn)和節(jié)點(diǎn)電池放電規(guī)律進(jìn)行統(tǒng)合研究,構(gòu)建能量模型實(shí)現(xiàn)對(duì)節(jié)點(diǎn)運(yùn)行過(guò)程中各模塊消耗情況的統(tǒng)計(jì),以及對(duì)節(jié)點(diǎn)工作時(shí)間和剩余能量的統(tǒng)計(jì),并根據(jù)節(jié)點(diǎn)工作能耗情況對(duì)剩余工作時(shí)間進(jìn)行預(yù)測(cè)。針對(duì)TinyOS2.x的仿真工具無(wú)法實(shí)現(xiàn)節(jié)點(diǎn)能量檢測(cè)的不足,設(shè)計(jì)計(jì)算節(jié)點(diǎn)剩余能量的TinyOS2.x能量組件,實(shí)現(xiàn)能量監(jiān)測(cè),有利于對(duì)網(wǎng)絡(luò)能量進(jìn)行研究。(2)路由協(xié)議方面,由于節(jié)點(diǎn)使用的電池容量受限,運(yùn)行過(guò)程中網(wǎng)絡(luò)拓?fù)鋾?huì)不斷發(fā)生變化,路由要隨應(yīng)用的變化而變化。采用非均勻分簇方法進(jìn)行簇首選擇;通過(guò)節(jié)點(diǎn)競(jìng)爭(zhēng)力和節(jié)點(diǎn)能量管理機(jī)制相互協(xié)作決定最優(yōu)簇首節(jié)點(diǎn);根據(jù)傳輸能耗、剩余能量和傳輸距離等影響因素采用簇間連通算法進(jìn)行簇間多跳路徑選擇,實(shí)現(xiàn)負(fù)載的均衡分配。(3)時(shí)間同步方面,針對(duì)傳感器節(jié)點(diǎn)數(shù)據(jù)時(shí)間不一致,提出時(shí)間同步算法。使用網(wǎng)絡(luò)分層策略減少同步通信開(kāi)銷;采用同步誤差補(bǔ)償機(jī)制降低同步誤差的影響,利用時(shí)鐘補(bǔ)償機(jī)制減少運(yùn)行的累積誤差。在保證時(shí)間精度前提下,降低同步次數(shù)減少同步開(kāi)銷。
[Abstract]:Wireless sensor networks (WSNs) use self-organization to construct a network of small sensor nodes with low cost and low energy consumption, which can realize real-time sensing, monitoring and collecting of various information in target detection area. The collected data are processed and analyzed. Wireless sensor nodes have been widely used in military monitoring, system control, health care, environmental monitoring and other industries, with the advantages of convenient use, strong stability, easy expansion, good economy, safety and reliability, etc. By a variety of industry research and development personnel attached great importance. There are still many obstacles in the development and application of network. For example, in the process of using the network, the number of sensor nodes that need to be deployed is large, the location is random, and the monitoring environment is complex. The node stops working; When the network is monitored on a large scale, a large number of nodes should be deployed, which results in high overall cost and affects the popularization and popularization of the network. In actual deployment, the sensor nodes often use batteries to power the nodes, the development of the node miniaturization limits the battery capacity, and the huge number of nodes will cause the node battery replacement is very inconvenient. By using the energy model optimization strategy to study the network, starting from the network routing topology, this paper provides a new way of thinking for the establishment of efficient and energy-saving network. Aiming at the imbalance of network energy consumption, according to the characteristics of different types of applications, combined with node energy consumption model and multipath routing technology, the residual time prediction, network topology and time synchronization of nodes are studied. (1) Energy model. The characteristics of energy consumption of each module of CC2530 sensor node and the discharge law of node battery are studied, and the energy model is constructed to realize the statistics of the consumption of each module during the operation of the node. The working time and residual energy of the node are counted, and the remaining working time is predicted according to the working energy consumption of the node. Because the simulation tool of TinyOS2.x can not realize the energy detection of nodes, the design of TinyOS2.x energy component to calculate the residual energy of nodes is beneficial to the research of network energy. (2) in the aspect of routing protocol, the design of TinyOS2.x energy component to calculate the residual energy of nodes is beneficial to the research of network energy. Due to the limited battery capacity used by the nodes, the network topology will change continuously during operation, and the routing will change with the application. The non-uniform clustering method is used to select the cluster heads, and the optimal cluster heads are determined by the cooperation of the node competitiveness and the energy management mechanism of the nodes. According to the influence factors such as transmission energy consumption, residual energy and transmission distance, inter-cluster connectivity algorithm is used to select multi-hop paths between clusters to achieve load balancing. (3) in the aspect of time synchronization, the data time of sensor nodes is inconsistent. A time synchronization algorithm is proposed. The network delamination strategy is used to reduce the synchronous communication overhead, the synchronization error compensation mechanism is adopted to reduce the influence of synchronization error, and the clock compensation mechanism is used to reduce the cumulative error. On the premise of ensuring time precision, the synchronization times are reduced and the synchronization overhead is reduced.
【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

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