基于網(wǎng)絡(luò)編碼的無線傳感器網(wǎng)絡(luò)能量效率技術(shù)研究
發(fā)布時間:2018-05-15 03:36
本文選題:無線傳感器網(wǎng)絡(luò) + 網(wǎng)絡(luò)編碼。 參考:《南京理工大學(xué)》2014年博士論文
【摘要】:近年來,技術(shù)的進步和制造成本的降低使得無線傳感器網(wǎng)絡(luò)(WSN, Wireless Sensor Network)得到了突飛猛進的發(fā)展。由于傳感器節(jié)點的易部署性和多功能性,WSN被廣泛應(yīng)用到各種領(lǐng)域,如醫(yī)療衛(wèi)生、目標跟蹤、環(huán)境監(jiān)控等。傳感器節(jié)點的主要任務(wù)是收集、保存數(shù)據(jù),并將數(shù)據(jù)傳輸給匯聚節(jié)點做進一步的操作。傳感器節(jié)點能量的有限性和無線鏈路的不可靠性給設(shè)計高效的通信、存儲機制帶來了巨大的挑戰(zhàn)。 路由技術(shù)是無線傳感器網(wǎng)絡(luò)中的一種重要的基礎(chǔ)支撐技術(shù),路由協(xié)議的好壞關(guān)系到組網(wǎng)的質(zhì)量。由于無線傳感器網(wǎng)絡(luò)在網(wǎng)絡(luò)特點、業(yè)務(wù)特點和應(yīng)用需求等方面與傳統(tǒng)網(wǎng)絡(luò)存在顯著差別,無線傳感器網(wǎng)絡(luò)路由的設(shè)計面臨一系列新的挑戰(zhàn)。尤其是近年來新技術(shù)的出現(xiàn)為傳統(tǒng)路由技術(shù)的發(fā)展帶來了新的活力。本文研究無線傳感器網(wǎng)絡(luò)中能量高效的數(shù)據(jù)傳輸機制、數(shù)據(jù)存儲與修復(fù)技術(shù)以及能量高效的組播技術(shù)。 (1)本文研究了無線傳感器網(wǎng)絡(luò)中基于網(wǎng)絡(luò)編碼的多徑路由的能量效率。采用的多徑網(wǎng)絡(luò)模型是纏繞多路徑模型,所用的網(wǎng)絡(luò)編碼方案為隨機線性網(wǎng)絡(luò)編碼。研究了基于網(wǎng)絡(luò)編碼的纏繞多路徑中成功交付率和能量消耗的分析模型。 (2)分析了網(wǎng)絡(luò)中不同參數(shù)對網(wǎng)絡(luò)性能的影響,如跳數(shù),數(shù)據(jù)包長度,子包大小,簇大小等,并通過對這些參數(shù)的分析,導(dǎo)出一種優(yōu)化的傳輸方案,該方案使得網(wǎng)絡(luò)能夠以更少的資源開銷完成網(wǎng)絡(luò)傳輸。此外,通過大量的離散事件仿真發(fā)現(xiàn),實驗結(jié)果與分析結(jié)果是一致的,并測試了在特殊環(huán)境下(如網(wǎng)絡(luò)擁塞,節(jié)點失效等)的網(wǎng)絡(luò)性能。 (3)本文提出了一種無線傳感器網(wǎng)絡(luò)中能量高效的數(shù)據(jù)存儲和修復(fù)方案。通過構(gòu)造具有稀疏特性的網(wǎng)絡(luò)碼字來實現(xiàn)能量高效的分布式存儲。此外,利用網(wǎng)絡(luò)編碼在中間節(jié)點進行編碼的思想,設(shè)計了一種迭代的修復(fù)策略,該方法使得在無線多跳網(wǎng)絡(luò)中能夠高效地進行數(shù)據(jù)恢復(fù),節(jié)約了數(shù)據(jù)包傳輸?shù)拇螖?shù)。并通過理論證明了該方案可以工作在非常小的有限域上。最后通過實驗證明,該方法相比傳統(tǒng)方法在降低能量消耗的同時,還能均衡網(wǎng)絡(luò)中的能量負載,從而能夠提升網(wǎng)絡(luò)的生存時間。 (4)提出將多速率網(wǎng)絡(luò)編碼方法應(yīng)用于無線多跳網(wǎng)絡(luò)的組播通信中,該方法能夠顯著提升組播網(wǎng)絡(luò)的吞吐量。并且提出了一種多速率網(wǎng)絡(luò)碼字的構(gòu)造方法,該方法在絕大多數(shù)的網(wǎng)絡(luò)情況下,都能使得接收節(jié)點以各自的最大流速率接收數(shù)據(jù)。并且提出了一個“流對齊”的方法來分離網(wǎng)絡(luò)中的獨立鏈路,從而顯著地降低網(wǎng)絡(luò)的復(fù)雜度。 (5)提出了一個充分條件,當(dāng)該條件滿足時,網(wǎng)絡(luò)中的所有目的節(jié)點均能以最大流的速率接收數(shù)據(jù)。大量的實驗證明,該方法所提出的多速率編碼方法能夠提升網(wǎng)絡(luò)的吞吐量,降低數(shù)據(jù)傳輸?shù)哪芰肯?并保證網(wǎng)絡(luò)中接收節(jié)點的解碼成功率。
[Abstract]:In recent years, with the development of technology and the reduction of manufacturing cost, wireless sensor networks (WSNs) and Wireless Sensor Network) (Wireless Sensor Networks) have been developed by leaps and bounds. Due to the deployable and multifunctional sensor nodes, WSN is widely used in various fields, such as medical and health, target tracking, environmental monitoring and so on. The main task of sensor node is to collect, save and transmit data to the sink node for further operation. The limited energy of sensor nodes and the unreliability of wireless links bring great challenges to the design of efficient communication and storage mechanisms. Routing technology is an important basic supporting technology in wireless sensor networks. The quality of network is related to the quality of routing protocols. Wireless sensor networks (WSN) face a series of new challenges due to the significant differences between wireless sensor networks (WSN) and traditional networks in terms of network characteristics, service characteristics and application requirements. Especially in recent years, the emergence of new technologies has brought new vitality to the development of traditional routing technology. This paper studies the energy-efficient data transmission mechanism, data storage and repair technology and energy-efficient multicast technology in wireless sensor networks. In this paper, the energy efficiency of multipath routing based on network coding in wireless sensor networks is studied. The multipath network model is winding multipath model and the network coding scheme is random linear network coding. The analysis model of successful delivery rate and energy consumption in winding multipath based on network coding is studied. This paper analyzes the influence of different parameters on network performance, such as hops, packet length, sub-packet size, cluster size, etc. By analyzing these parameters, an optimized transmission scheme is derived. This scheme enables the network to complete the network transmission with less resource cost. In addition, through a large number of discrete events simulation, it is found that the experimental results are consistent with the analytical results, and the performance of the network under special circumstances (such as network congestion, node failure, etc.) is tested. This paper presents an energy-efficient data storage and repair scheme for wireless sensor networks. Energy efficient distributed storage is realized by constructing network codewords with sparse characteristics. In addition, using the idea of network coding in the middle node, an iterative repair strategy is designed. This method enables efficient data recovery in wireless multi-hop networks and saves the number of packet transmissions. It is proved by theory that the scheme can work on very small finite fields. Finally, it is proved that compared with the traditional method, the proposed method can reduce the energy consumption and balance the energy load in the network at the same time, thus it can improve the lifetime of the network. 4) A multi-rate network coding method is proposed for multicast communication in wireless multi-hop networks, which can significantly improve the throughput of multicast networks. A method of constructing code words in multi-rate networks is proposed, which can make the receiving nodes receive data at their respective maximum flow rates in most networks. A "stream alignment" method is proposed to separate the independent links in the network, thus significantly reducing the complexity of the network. When the condition is satisfied, all the destination nodes in the network can receive data at the maximum flow rate. A large number of experiments show that the proposed multi-rate coding method can improve the throughput of the network, reduce the energy consumption of data transmission, and ensure the decoding success rate of the receiving node in the network.
【學(xué)位授予單位】:南京理工大學(xué)
【學(xué)位級別】:博士
【學(xué)位授予年份】:2014
【分類號】:TP212.9;TN929.5
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