【摘要】：隨著當(dāng)代信息科技的不斷發(fā)展,無(wú)線傳感器網(wǎng)絡(luò)在人們的日常生活中越來(lái)越受到重視,其應(yīng)用范圍現(xiàn)已涉及軍事、醫(yī)療、環(huán)境等諸多領(lǐng)域。無(wú)線傳感器網(wǎng)絡(luò)的三大主要功能包括數(shù)據(jù)采集,數(shù)據(jù)處理以及數(shù)據(jù)傳輸,它是由眾多靜止的傳感器節(jié)點(diǎn)以自行組織和多跳的方式構(gòu)成的網(wǎng)絡(luò)。其核心技術(shù)是如何選取一條合理并且高效的通信路由,這也是決定網(wǎng)絡(luò)整體性能的重要依據(jù)。近年來(lái),低功耗自適應(yīng)集簇分層型協(xié)議、能量有效的閾值敏感路由協(xié)議、定向擴(kuò)散協(xié)議、洪泛法,以及以數(shù)據(jù)為中心的自適應(yīng)通信路由協(xié)議等傳統(tǒng)的路由協(xié)議往往無(wú)法滿足無(wú)線傳感器網(wǎng)絡(luò)的實(shí)際需求,因此文章提出了基于改進(jìn)后的蟻群算法的無(wú)線傳感器網(wǎng)絡(luò)路由協(xié)議。本文的核心工作如下 1、文章介紹了基本蟻群算法的原理和適用范圍,總結(jié)出了基本蟻群算法在求解最優(yōu)路徑問(wèn)題時(shí),雖然具有很強(qiáng)的發(fā)現(xiàn)較優(yōu)解的能力,但是存在容易陷入局部最優(yōu)解和收斂時(shí)間過(guò)長(zhǎng)等問(wèn)題�？紤]到基本蟻群算法在無(wú)線傳感器網(wǎng)絡(luò)路由上應(yīng)用的不足,文章提出了一種改進(jìn)后的蟻群算法,并將其應(yīng)用到傳感器網(wǎng)絡(luò)路由中。該算法不僅在狀態(tài)轉(zhuǎn)移概率公式中引入罰函數(shù)以及動(dòng)態(tài)權(quán)重因子,而且采用局部信息素更新和全局信息素更新結(jié)合的方式更新路徑信息,可以更加高效、全面地進(jìn)行尋優(yōu)。防止基本蟻群算法較早的陷入局部最優(yōu)解。 2、該算法模型充分考慮到傳感器節(jié)點(diǎn)與節(jié)點(diǎn)間的傳輸距離,并且充分考慮傳感器節(jié)點(diǎn)的剩余能量,提出了一種智能、動(dòng)態(tài)、擴(kuò)充性良好的路由選擇傳輸方式來(lái)獲取有效且節(jié)能的通信路由。 最后通過(guò)仿真實(shí)驗(yàn),得到了基本蟻群算法以及焦斌等人改進(jìn)后的蟻群算法和本文改進(jìn)后的蟻群算法在傳感器節(jié)點(diǎn)剩余能量和傳輸數(shù)據(jù)包時(shí)網(wǎng)絡(luò)延遲的不同曲線,驗(yàn)證了本文改進(jìn)后的蟻群算法在無(wú)線傳感器網(wǎng)絡(luò)路由選擇上的高效性,實(shí)驗(yàn)結(jié)果表明本文改進(jìn)后的蟻群算法能有效的降低傳感器網(wǎng)絡(luò)中節(jié)點(diǎn)與節(jié)點(diǎn)之間的傳輸能耗,最大程度上延長(zhǎng)了整個(gè)網(wǎng)絡(luò)的生存周期。該算法具有很強(qiáng)的擴(kuò)展性,因此特別適合大規(guī)模的網(wǎng)絡(luò)結(jié)構(gòu)。
[Abstract]:With the development of modern information technology, wireless sensor networks (WSN) have been paid more and more attention in people's daily life. The application of WSN has been involved in military, medical, environmental and other fields. The three main functions of wireless sensor networks (WSN) include data acquisition, data processing and data transmission. It is a network composed of many static sensor nodes organized by themselves and multi-hop. Its core technology is how to select a reasonable and efficient communication route, which is also an important basis to determine the overall performance of the network. In recent years, low power adaptive clustering protocols, energy-efficient threshold sensitive routing protocols, directional diffusion protocols, flooding methods, Traditional routing protocols, such as data-centric adaptive communication routing protocols, are often unable to meet the actual needs of wireless sensor networks. Therefore, an improved ant colony algorithm based routing protocol for wireless sensor networks is proposed in this paper. The core work of this paper is as follows: 1. This paper introduces the principle and application scope of basic ant colony algorithm, and concludes that the basic ant colony algorithm has a strong ability to find a better solution in solving the optimal path problem. However, there are some problems such as easy to fall into local optimal solution and long convergence time. Considering the deficiency of basic ant colony algorithm in wireless sensor network routing, this paper proposes an improved ant colony algorithm and applies it to sensor network routing. The algorithm not only introduces penalty function and dynamic weight factor into the formula of state transition probability, but also updates path information by combining local pheromone update with global pheromone update. In order to prevent the basic ant colony algorithm from falling into the local optimal solution earlier. 2, this algorithm model fully considers the transmission distance between sensor nodes and nodes, and fully considers the residual energy of sensor nodes, and proposes an intelligent and dynamic algorithm. The extended route choice transmission mode to obtain the effective and energy-efficient communication route. Finally, through the simulation experiments, the different curves of the network delay between the sensor node residual energy and the transmission packet are obtained by the basic ant colony algorithm, the improved ant colony algorithm of Jiao Bin and the improved ant colony algorithm in this paper. The experimental results show that the improved ant colony algorithm can effectively reduce the transmission energy consumption between nodes in wireless sensor networks. The life cycle of the whole network is extended to the maximum extent. This algorithm has strong expansibility, so it is especially suitable for large scale network structure.
【學(xué)位授予單位】：陜西師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP212.9;TN915.04;TP18

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