有效能量空洞避免的混合傳輸分簇路由算法研究
發(fā)布時(shí)間：2019-06-11 20:22
【摘要】：近年來(lái)隨著低成本低功耗微型傳感器的大規(guī)模生產(chǎn),無(wú)線傳感器網(wǎng)絡(luò)的實(shí)用價(jià)值和應(yīng)用前景非常廣闊。但傳感器節(jié)點(diǎn)能量高度受限,且工作環(huán)境通常十分惡劣,更換電池可行性不高,因此,如何高效利用有限能量以最大化網(wǎng)絡(luò)生命周期是無(wú)線傳感器網(wǎng)絡(luò)研究的關(guān)鍵問(wèn)題。其中由于部分節(jié)點(diǎn)過(guò)早耗盡自身能量,導(dǎo)致失效節(jié)點(diǎn)覆蓋區(qū)域缺失或數(shù)據(jù)無(wú)法送達(dá)sink節(jié)點(diǎn)的能量空洞現(xiàn)象是無(wú)線傳感器網(wǎng)絡(luò)的一個(gè)研究重點(diǎn)和難點(diǎn)。該現(xiàn)象嚴(yán)重情況下使整個(gè)網(wǎng)絡(luò)無(wú)法正常工作,造成大量剩余資源的浪費(fèi)。本文主要針對(duì)WSN中節(jié)點(diǎn)能耗不均衡而產(chǎn)生的能量空洞現(xiàn)象,在低功耗自適應(yīng)集簇分層型協(xié)議基礎(chǔ)上,從簇頭選擇、節(jié)點(diǎn)部署、數(shù)據(jù)通信方面,設(shè)計(jì)了兩種新的分簇路由算法。具體的創(chuàng)新性工作如下:(1)為解決網(wǎng)絡(luò)邊緣區(qū)域能量空洞問(wèn)題,提出了一種基于吸引因子和混合傳輸?shù)姆执芈酚伤惴?CRAH)。CRAH采用加權(quán)和的方式將節(jié)點(diǎn)剩余能量和位置作為合理選取簇頭的新指標(biāo),并將簇頭的任務(wù)重新分配給新選出的融合節(jié)點(diǎn);在數(shù)據(jù)通信階段,設(shè)計(jì)吸引因子模型,使融合節(jié)點(diǎn)采用混合傳輸模式進(jìn)行簇間數(shù)據(jù)通信,并改進(jìn)Dijkstra算法,提出新的AF-DK算法,為簇間數(shù)據(jù)傳輸選擇最優(yōu)路徑,節(jié)省了通信開銷。(2)此外,CRAH中存在基站數(shù)據(jù)接收率低的問(wèn)題,且多跳傳輸方式又會(huì)造成sink附近節(jié)點(diǎn)負(fù)載過(guò)重,產(chǎn)生內(nèi)層網(wǎng)絡(luò)能量空洞現(xiàn)象,因此提出了群智能優(yōu)化和密度控制的能量空洞避免算法(EASD)。該算法根據(jù)感知數(shù)據(jù)轉(zhuǎn)發(fā)能耗建立節(jié)點(diǎn)密度遞減模型,保證數(shù)據(jù)轉(zhuǎn)發(fā)負(fù)載由相應(yīng)數(shù)量的簇頭分擔(dān),均衡每個(gè)簇頭的負(fù)載。為搜索簇頭到基站間多跳數(shù)據(jù)通信的最優(yōu)路徑,優(yōu)化群智能算法,加入每個(gè)鄰居節(jié)點(diǎn)的剩余能量、位置信息、傳輸距離和信息素等上下文信息,改進(jìn)螞蟻選擇下一跳節(jié)點(diǎn)的轉(zhuǎn)移概率。其中,信息素更新時(shí),結(jié)合數(shù)據(jù)包接收率,綜合考慮了能量、路徑長(zhǎng)度和路徑質(zhì)量,提高了網(wǎng)絡(luò)轉(zhuǎn)發(fā)路徑的可靠性,解決了基站接收數(shù)據(jù)率低的問(wèn)題。(3)最后,通過(guò)模擬實(shí)驗(yàn)表明兩種新算法有效避免了能量空洞問(wèn)題,延長(zhǎng)了網(wǎng)絡(luò)生命周期。同時(shí)在數(shù)據(jù)送達(dá)率方面對(duì)兩種新方案做了單獨(dú)對(duì)比,驗(yàn)證了EASD進(jìn)一步解決了CRAH中基站數(shù)據(jù)接收率低的問(wèn)題,增強(qiáng)了路徑可靠性。
[Abstract]:In recent years, with the large-scale production of low-cost and low-power micro-sensors, the practical value and application prospect of wireless sensor networks are very broad. However, the energy of sensor nodes is highly limited, and the working environment is usually very bad, so it is not feasible to replace batteries. Therefore, how to make efficient use of limited energy to maximize the network life cycle is the key problem in wireless sensor networks. It is a research focus and difficulty in wireless sensor networks that some nodes exhaust their own energy prematurely, resulting in the lack of coverage area of invalid nodes or the inability of data to reach sink nodes. This phenomenon makes the whole network unable to work properly, resulting in the waste of a large number of remaining resources. In this paper, aiming at the phenomenon of energy hole caused by uneven energy consumption of nodes in WSN, two new clustering routing algorithms are designed from the aspects of cluster head selection, node deployment and data communication on the basis of low power adaptive cluster layer protocol. The specific innovative work is as follows: (1) in order to solve the problem of energy hole in the edge region of the network, a clustering routing algorithm (CRAH). CRH based on attraction factor and hybrid transmission is proposed, which takes the residual energy and position of the nodes as a new index to reasonably select the cluster head, and redistributes the task of the cluster head to the newly selected fusion node. In the stage of data communication, the attraction factor model is designed to make the fusion node use mixed transmission mode for inter-cluster data communication, and the Dijkstra algorithm is improved, and a new AF-DK algorithm is proposed to select the optimal path for inter-cluster data transmission, which saves the communication overhead. (2) in addition, there is a problem of low base station data reception rate in CRAH, and the multi-hop transmission mode will cause the node near sink to be overloaded. The energy hole phenomenon in the inner layer network is produced, so the energy hole avoidance algorithm (EASD)., which is a group intelligent optimization and density control algorithm, is proposed. The algorithm establishes a node density decline model according to the perceived data forwarding energy consumption, which ensures that the data forwarding load is shared by the corresponding number of cluster heads and balances the load of each cluster head. In order to search the optimal path of multi-hop data communication between cluster head and base station, the swarm intelligence algorithm is optimized. The context information such as residual energy, position information, transmission distance and pheromone of each neighbor node is added to improve the transfer probability of ant selection of the next hop node. Among them, when the pheromone is updated, combined with the packet reception rate, the energy, path length and path quality are considered synthetically, which improves the reliability of the network forwarding path and solves the problem of low data reception rate of the base station. (3) finally, the simulation results show that the two new algorithms effectively avoid the problem of energy voids and prolong the network life cycle. At the same time, the two new schemes are compared separately in the aspect of data delivery rate, which verifies that EASD further solves the problem of low data reception rate of base station in CRAH and enhances the path reliability.
【學(xué)位授予單位】：中國(guó)礦業(yè)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
本文編號(hào)：2497427
[Abstract]:In recent years, with the large-scale production of low-cost and low-power micro-sensors, the practical value and application prospect of wireless sensor networks are very broad. However, the energy of sensor nodes is highly limited, and the working environment is usually very bad, so it is not feasible to replace batteries. Therefore, how to make efficient use of limited energy to maximize the network life cycle is the key problem in wireless sensor networks. It is a research focus and difficulty in wireless sensor networks that some nodes exhaust their own energy prematurely, resulting in the lack of coverage area of invalid nodes or the inability of data to reach sink nodes. This phenomenon makes the whole network unable to work properly, resulting in the waste of a large number of remaining resources. In this paper, aiming at the phenomenon of energy hole caused by uneven energy consumption of nodes in WSN, two new clustering routing algorithms are designed from the aspects of cluster head selection, node deployment and data communication on the basis of low power adaptive cluster layer protocol. The specific innovative work is as follows: (1) in order to solve the problem of energy hole in the edge region of the network, a clustering routing algorithm (CRAH). CRH based on attraction factor and hybrid transmission is proposed, which takes the residual energy and position of the nodes as a new index to reasonably select the cluster head, and redistributes the task of the cluster head to the newly selected fusion node. In the stage of data communication, the attraction factor model is designed to make the fusion node use mixed transmission mode for inter-cluster data communication, and the Dijkstra algorithm is improved, and a new AF-DK algorithm is proposed to select the optimal path for inter-cluster data transmission, which saves the communication overhead. (2) in addition, there is a problem of low base station data reception rate in CRAH, and the multi-hop transmission mode will cause the node near sink to be overloaded. The energy hole phenomenon in the inner layer network is produced, so the energy hole avoidance algorithm (EASD)., which is a group intelligent optimization and density control algorithm, is proposed. The algorithm establishes a node density decline model according to the perceived data forwarding energy consumption, which ensures that the data forwarding load is shared by the corresponding number of cluster heads and balances the load of each cluster head. In order to search the optimal path of multi-hop data communication between cluster head and base station, the swarm intelligence algorithm is optimized. The context information such as residual energy, position information, transmission distance and pheromone of each neighbor node is added to improve the transfer probability of ant selection of the next hop node. Among them, when the pheromone is updated, combined with the packet reception rate, the energy, path length and path quality are considered synthetically, which improves the reliability of the network forwarding path and solves the problem of low data reception rate of the base station. (3) finally, the simulation results show that the two new algorithms effectively avoid the problem of energy voids and prolong the network life cycle. At the same time, the two new schemes are compared separately in the aspect of data delivery rate, which verifies that EASD further solves the problem of low data reception rate of base station in CRAH and enhances the path reliability.
【學(xué)位授予單位】：中國(guó)礦業(yè)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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，本文編號(hào)：2497427
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