本文選題：無線傳感器網(wǎng)絡 + 網(wǎng)絡編碼��； 參考：《廣西大學》2014年碩士論文

【摘要】：節(jié)點能量有限已成為制約無線傳感器網(wǎng)絡性能的主要瓶頸,在保障信息傳輸質(zhì)量的前提下,如何充分利用有限的網(wǎng)絡資源、減少網(wǎng)絡節(jié)點能耗、延長網(wǎng)絡生命周期等已成為無線傳感器網(wǎng)絡研究工作中的重點問題。網(wǎng)絡編碼通過對數(shù)據(jù)編碼后再轉發(fā)的方式,能夠有效提升數(shù)據(jù)投遞率、網(wǎng)絡吞吐量及網(wǎng)絡能量效率。壓縮感知將信號投影到稀疏域,通過部分數(shù)據(jù)能夠以較高概率恢復出原始信息的近似值,從而減少了網(wǎng)絡中傳輸?shù)臄?shù)據(jù)量,節(jié)約了網(wǎng)絡資源。本文的研究工作以降低網(wǎng)絡能耗為目標,從減少冗余傳輸數(shù)據(jù)量出發(fā),結合網(wǎng)絡編碼和壓縮感知,對無線傳感器網(wǎng)絡中傳感器節(jié)點的節(jié)能方式進行深入了研究,主要的工作和創(chuàng)新點如下： 1、提出一種基于隨機網(wǎng)絡編碼的無線傳感器網(wǎng)絡多路徑節(jié)能算法(RNC-ESMP)。該算法首先綜合考慮網(wǎng)絡節(jié)點剩余能量和節(jié)點間通信能耗的路徑選擇概率,引入條件傳輸價值比；接著構建從信宿節(jié)點到信源節(jié)點的反饋機制；最后提出中繼節(jié)點編碼選擇方案。實驗結果表明,該算法有效減少了傳輸時延和編碼節(jié)點數(shù),從而實現(xiàn)節(jié)能,而對比其他多路徑和網(wǎng)絡編碼算法,RNC-ESMP能有效降低網(wǎng)絡平均能耗約15%-50%,減少數(shù)據(jù)傳輸時延約12%-33%,從而提高了網(wǎng)絡性能。 2、提出一種結合隨機網(wǎng)絡編碼和占空比的無線傳感器網(wǎng)絡節(jié)能算法(NCDES)。該算法提出首先根據(jù)接收數(shù)據(jù)的ID信息決定節(jié)點處于工作或睡眠狀態(tài),以避免數(shù)據(jù)重復接收；并通過結合隨機網(wǎng)絡編碼,增加在相同傳輸次數(shù)下傳輸?shù)臄?shù)據(jù)信息量,從而實現(xiàn)節(jié)約網(wǎng)絡能耗。并且,本文通過理論計算分析了NCDES算法所構建傳輸模式下的網(wǎng)絡能耗最大值,并驗證了多跳網(wǎng)絡能耗的最優(yōu)解。實驗結果表明,對比其他聯(lián)合隨機占空比網(wǎng)絡編碼算法和改進型自適應網(wǎng)絡編碼算法,NCDES能分別延長網(wǎng)絡生命周期4.02%和8.51%,并分別提升包投遞率14.83%和4.65%,從而有效提升數(shù)據(jù)包投遞率和網(wǎng)絡能量效率。 3、提出一種融合壓縮感知和網(wǎng)絡編碼的無線傳感器網(wǎng)絡節(jié)能算法(CS-NCES)。該算法首先運用無線傳感器網(wǎng)絡數(shù)據(jù)的時間和空間相關性以及隨機網(wǎng)絡編碼矩陣和壓縮感知測量矩陣的相似性,在信源節(jié)點對數(shù)據(jù)進行編碼,并應用有限域壓縮感知對數(shù)據(jù)進行壓縮,將壓縮與編碼融為一體,以實現(xiàn)數(shù)據(jù)的編碼-壓縮-再編碼,從而使得中繼節(jié)點傳輸數(shù)據(jù)量少于原數(shù)據(jù)量,隨之降低網(wǎng)絡能耗,而信宿節(jié)點通過譯碼-重構-再譯碼的方式來提升數(shù)據(jù)傳遞率。并且,本文通過對壓縮感知和網(wǎng)絡編碼分別作用于實數(shù)域和有限域進行研究分析,構造了改進型多項式確定性矩陣,并對其可行性進行了驗證。實驗結果表明,CS-NCES對比其他網(wǎng)絡編碼算法,能有效降低網(wǎng)絡能耗25.3%-34.5%,提升數(shù)據(jù)重構效率1.56%-5.98%,從而提升網(wǎng)絡編碼在無線傳感器網(wǎng)絡中的實用性和網(wǎng)絡性能。
[Abstract]:Limited node energy has become the main bottleneck of wireless sensor network performance. Under the premise of ensuring the quality of information transmission, how to make full use of the limited network resources and reduce the energy consumption of network nodes.Prolonging the network life cycle has become a key issue in the research of wireless sensor networks (WSN).Network coding can effectively improve the data delivery rate, network throughput and network energy efficiency by the way of data coding and forwarding.Compressed perception projects the signal into sparse domain, which can restore the approximate value of the original information with a higher probability through partial data, thus reducing the amount of data transmitted in the network and saving the network resources.In order to reduce the energy consumption of wireless sensor network, the research work of this paper aims at reducing the redundant transmission data, combining with network coding and compression perception, the energy saving mode of sensor nodes in wireless sensor network is deeply studied.The main areas of work and innovation are as follows:1. A multipath energy saving algorithm for wireless sensor networks based on random network coding is proposed.The algorithm firstly considers the path selection probability of network nodes' residual energy and inter-node communication energy consumption, then introduces conditional transmission value ratio, and then constructs a feedback mechanism from the host node to the source node.Finally, a scheme of coding selection for relay nodes is proposed.Experimental results show that the proposed algorithm can effectively reduce the transmission delay and the number of coding nodes, thus achieving energy saving.Compared with other multipath and network coding algorithms, RNC-ESMP can effectively reduce the average energy consumption of the network by about 15 to 50, and reduce the delay of data transmission by about 12 to 33, thus improving the network performance.2. An energy saving algorithm for wireless sensor networks based on random network coding and duty cycle is proposed.The proposed algorithm firstly determines that the node is in the state of working or sleeping according to the ID information of the received data, so as to avoid the repeated receiving of the data, and increases the amount of data information transmitted under the same number of times by combining the random network coding.Thus, the network energy consumption can be saved.In addition, the maximum energy consumption in the transmission mode constructed by NCDES algorithm is analyzed by theoretical calculation, and the optimal solution of multi-hop network energy consumption is verified.The experimental results show that,Compared with other joint random duty cycle network coding algorithms and improved adaptive network coding algorithm, NCDES can prolong the network life cycle by 4.02% and 8.51%, and increase the packet delivery rate by 14.83% and 4.65%, respectively, thus effectively improving the packet delivery rate and network energy efficiency.3. An energy saving algorithm for wireless sensor networks based on compression sensing and network coding is proposed.The algorithm firstly uses the temporal and spatial correlation of wireless sensor network data and the similarity between random network coding matrix and compressed sensing measurement matrix to code the data at the source node.In order to realize the data encoding, compression and recoding, the relay nodes transmit less data than the original data, and then reduce the network energy consumption.The host node improves the data transfer rate by decoding-reconstructing-redecoding.Furthermore, through the research and analysis of compressed sensing and network coding acting on real and finite fields respectively, the improved polynomial deterministic matrix is constructed and its feasibility is verified.The experimental results show that compared with other network coding algorithms, CS-NCES can effectively reduce the network energy consumption by 25.3- 34.5and improve the efficiency of data reconfiguration 1.56-5.98. thus, the practicability and network performance of network coding in wireless sensor networks can be improved.
【學位授予單位】：廣西大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP212.9;TN929.5

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