蟻群算法在無線傳感器網(wǎng)絡路由協(xié)議中的應用研究
發(fā)布時間：2018-10-14 16:51
【摘要】：隨著當代信息科技的不斷發(fā)展,無線傳感器網(wǎng)絡在人們的日常生活中越來越受到重視,其應用范圍現(xiàn)已涉及軍事、醫(yī)療、環(huán)境等諸多領域。無線傳感器網(wǎng)絡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)點以自行組織和多跳的方式構成的網(wǎng)絡。其核心技術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)絡整體性能的重要依據(jù)。近年來,低功耗自適應集簇分層型協(xié)議、能量有效的閾值敏感路由協(xié)議、定向擴散協(xié)議、洪泛法,以及以數(shù)據(jù)為中心的自適應通信路由協(xié)議等傳統(tǒng)的路由協(xié)議往往無法滿足無線傳感器網(wǎng)絡的實際需求,因此文章提出了基于改進后的蟻群算法的無線傳感器網(wǎng)絡路由協(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,總結出了基本蟻群算法在求解最優(yōu)路徑問題時,雖然具有很強的發(fā)現(xiàn)較優(yōu)解的能力,但是存在容易陷入局部最優(yōu)解和收斂時間過長等問題�？紤]到基本蟻群算法在無線傳感器網(wǎng)絡路由上應用的不足,文章提出了一種改進后的蟻群算法,并將其應用到傳感器網(wǎng)絡路由中。該算法不僅在狀態(tài)轉移概率公式中引入罰函數(shù)以及動態(tài)權重因子,而且采用局部信息素更新和全局信息素更新結合的方式更新路徑信息,可以更加高效、全面地進行尋優(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)點與節(jié)點間的傳輸距離,并且充分考慮傳感器節(jié)點的剩余能量,提出了一種智能、動態(tài)、擴充性良好的路由選擇傳輸方式來獲取有效且節(jié)能的通信路由。 最后通過仿真實驗,得到了基本蟻群算法以及焦斌等人改進后的蟻群算法和本文改進后的蟻群算法在傳感器節(jié)點剩余能量和傳輸數(shù)據(jù)包時網(wǎng)絡延遲的不同曲線,驗證了本文改進后的蟻群算法在無線傳感器網(wǎng)絡路由選擇上的高效性,實驗結果表明本文改進后的蟻群算法能有效的降低傳感器網(wǎng)絡中節(jié)點與節(jié)點之間的傳輸能耗,最大程度上延長了整個網(wǎng)絡的生存周期。該算法具有很強的擴展性,因此特別適合大規(guī)模的網(wǎng)絡結構。
[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.
【學位授予單位】：陜西師范大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212.9;TN915.04;TP18
本文編號：2271044
[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.
【學位授予單位】：陜西師范大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212.9;TN915.04;TP18
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