本文關(guān)鍵詞：無線傳感器網(wǎng)絡(luò)數(shù)據(jù)收集若干問題的研究　出處：《哈爾濱工業(yè)大學(xué)》2014年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 無線傳感器網(wǎng)絡(luò) 數(shù)據(jù)收集 數(shù)據(jù)聚集 路由協(xié)議 多信道調(diào)度

【摘要】：數(shù)據(jù)收集問題是無線傳感器網(wǎng)絡(luò)的非常重要的研究問題之一，近幾年對(duì)數(shù)據(jù)收集問題的研究也很廣泛。數(shù)據(jù)收集問題即是研究外界用戶如何通過無線傳感器網(wǎng)絡(luò)從監(jiān)控區(qū)域收集感應(yīng)數(shù)據(jù)。在數(shù)據(jù)收集問題中，用戶先在監(jiān)控區(qū)域中放置大量特定用途的傳感器節(jié)點(diǎn)，監(jiān)控區(qū)域內(nèi)的傳感器節(jié)點(diǎn)以自適應(yīng)方式組成無線傳感器網(wǎng)絡(luò)。數(shù)據(jù)收集是就將采集到的傳感器數(shù)據(jù)通過多跳的形式傳輸給用戶進(jìn)行處理的過程。傳感器網(wǎng)絡(luò)數(shù)據(jù)收集問題包含的范圍非常廣，從數(shù)據(jù)收集協(xié)議，到多信道調(diào)度，從靜態(tài)網(wǎng)絡(luò)，到可移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)收集等，都存在大量的研究問題。本文將從如何減少數(shù)據(jù)收集過程中的數(shù)據(jù)傳輸量、數(shù)據(jù)收集協(xié)議、增大網(wǎng)絡(luò)吞吐量等幾方面開展工作。 首先，本文研究了在多任務(wù)共享的傳感器網(wǎng)絡(luò)如何減少數(shù)據(jù)傳輸量問題。在多任務(wù)共享的傳感器網(wǎng)絡(luò)中，人們可以利用數(shù)據(jù)可被多任務(wù)共享這一特性來減少數(shù)據(jù)傳輸量。本文提出一個(gè)區(qū)間數(shù)據(jù)共享問題。與現(xiàn)有研究中每個(gè)任務(wù)只采集一個(gè)數(shù)據(jù)不同，本文的問題中每個(gè)任務(wù)需要采集一段連續(xù)的數(shù)據(jù)。由于數(shù)據(jù)可以被多任務(wù)共享，該問題的目的是采集最少的連續(xù)數(shù)據(jù)，，滿足所有任務(wù)的數(shù)據(jù)需求。本文將該的問題刻畫為非線性非凸問題，并提出一個(gè)近似算法來減少非線性非凸問題求解的復(fù)雜性。文章還分析了該問題的一個(gè)特例，并提出一個(gè)動(dòng)態(tài)規(guī)劃算法求解最優(yōu)解。針對(duì)任務(wù)陸續(xù)到達(dá)的情況，文章還提出了三個(gè)在線算法。文章對(duì)每個(gè)算法的理論性能、時(shí)間復(fù)雜性和空間復(fù)雜性都進(jìn)行了分析。 其次，本文研究了多對(duì)象計(jì)數(shù)聚集過程中如何減少數(shù)據(jù)傳輸量問題。與現(xiàn)有的單對(duì)象計(jì)數(shù)問題的研究不同，本文研究多對(duì)象計(jì)數(shù)問題。由于所有的對(duì)象都需要返回各自的計(jì)數(shù)結(jié)果，因此，多對(duì)象計(jì)數(shù)問題會(huì)造成大量的通信開銷。本文提出一個(gè)分布式的多對(duì)象計(jì)數(shù)算法。該算法可以保證在每個(gè)節(jié)點(diǎn)最多發(fā)送一定數(shù)量數(shù)據(jù)包的情況下，使得返回具有上界誤差的結(jié)果。針對(duì)每個(gè)對(duì)象權(quán)重不同的情況，本文還分析了帶權(quán)多對(duì)象計(jì)數(shù)問題。帶權(quán)多對(duì)象問題可以刻畫為不帶權(quán)問題的一個(gè)特例。文章對(duì)所提出的算法的誤差上界、節(jié)點(diǎn)數(shù)據(jù)發(fā)送量以及內(nèi)存使用量都進(jìn)行了分析。 然后，本文研究了數(shù)據(jù)收集過程中的地理路由協(xié)議。地理路由協(xié)議只需維護(hù)一小部分節(jié)點(diǎn)的信息就可實(shí)驗(yàn)路由數(shù)據(jù)的功能，因此得到廣泛關(guān)注。但是地理路由算法都需要將網(wǎng)絡(luò)進(jìn)行拓?fù)淦矫婊幚�，從而避免路由環(huán)問題。針對(duì)現(xiàn)有平面化方法維護(hù)代價(jià)很高的問題，本文提出一種具有高可靠性和低維護(hù)成本的地理路由協(xié)議。該協(xié)議的基本思想是將網(wǎng)絡(luò)劃分為規(guī)則多邊形區(qū)域,并在貪心路由失敗時(shí)將多邊形區(qū)域內(nèi)的所有節(jié)點(diǎn)看作一個(gè)虛擬節(jié)點(diǎn)進(jìn)行周邊路由。多邊形區(qū)域間通信能夠降低平均路由路徑長度,從而提高了路由的可靠性。 最后，本文研究了如何最大化網(wǎng)絡(luò)吞吐量的問題。文章提出一個(gè)多信道TDMA調(diào)度算法最大化數(shù)據(jù)聚集網(wǎng)絡(luò)的數(shù)據(jù)收集速率。為了更接近真實(shí)網(wǎng)絡(luò)，本文使用的干擾模型是物理干擾模型。本文所提方法共包括三個(gè)步驟。首先需建立一棵路由樹，其次在路由樹的基礎(chǔ)上進(jìn)行時(shí)間槽分配，最后是進(jìn)行信道分配。本文提出的方法是分布式的，其比集中式的方法的調(diào)度代價(jià)更低。本文分析了所給算法的時(shí)間槽數(shù)的上界，通過最小化所使用的時(shí)間槽數(shù)，從而最大化吞吐量。
[Abstract]:Data collection is one of the important research issues in wireless sensor networks, the research on the data gathering problem in recent years is also very extensive. Data collection problem is how to collect sensor data from the outside user monitoring area through the wireless sensor network. The problem in the data collection, the user first place a large number of sensor nodes in specific applications in the monitoring area, sensor nodes in the monitoring area of the wireless sensor network in an adaptive way. Data collection is the sensor data collected for the user for processing through multi hop transmission form. The range contains the problem of data collection sensor network is very wide, from the data collection protocol, multi channel scheduling. From the static network, to the mobile network data collection, there are a host of problems. This article from how to reduce the data collection process The amount of data transmission, data collection protocol, increase network throughput and other aspects of work.
Firstly, this paper studies how the sensor network sharing in multi task problem. Reduce the amount of data transmission in sensor networks multi task sharing, people can use the data can be multiple tasks share this property to reduce the amount of data transmission. This paper proposes an interval data sharing problem. With each existing research tasks in the acquisition of a a different data, the problems in each task requires a continuous data acquisition. The data can be multi task sharing, the problem is the purpose of continuous data acquisition at least, meet all task data needs. The problems are characterized as nonlinear and non convex problem, and propose an approximate algorithm to reduce the complexity of solving nonlinear nonconvex problems. The paper also analyzes a special case of this problem, and propose a dynamic programming algorithm for solving the optimal solution for the task. Arriving. In addition, three online algorithms are proposed. The paper analyzes the theoretical performance, time complexity and space complexity of each algorithm.
Secondly, this paper studies how to reduce the amount of data transmission problem of multi object counting during aggregation. Research and the existing problems of the single object counting, this paper studies a multi object counting problem. Because all objects need to return to their respective counting results, therefore, multi object counting problems will cause a large amount of communication overhead is proposed in this paper. A distributed algorithm for multi object counting. The algorithm can guarantee that each node in the data packet sent in a certain number of cases, make the return error with upper bound results. For each object with different weights, this paper also analyzes the multi object counting problem with multi object problem with the right. The right can be described as a special case the problem with no right. The error bounds of the proposed algorithm, the sending node data and memory usage are analyzed.
Then, this paper studies the geographic routing protocol in the process of data collection. Geographic routing protocol maintains only a small part of the node information can be experimental data routing function, so it has been widely attention. But the geographic routing algorithms require the network topology of the plane processing, so as to avoid the problem. Aiming at the cost of the existing routing ring plane method of maintenance is very high, this paper presents a high reliability and low maintenance cost. The basic idea of the geographical routing protocol is the network is divided into regular polygon area, and the greedy routing failure when all nodes in the polygon as a virtual node routing. The communication between the surrounding polygon to reduce the average path length, thus improving the reliability of routing.
Finally, this paper studies how to maximize the throughput of the network. This paper proposes a multi-channel TDMA scheduling algorithm to maximize the data gathering network data collection rate. In order to be closer to the real network, the interference model used in this thesis is the physical interference model. The proposed method consists of three steps. The first need to establish a route the tree, then the time slot assignment based on routing tree, finally is the channel assignment. The method proposed in this paper is distributed, the centralized scheduling method than lower cost. This paper analyzes the given upper bound algorithm time slot number, time slot number by minimizing the use, to maximize throughput.

【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5;TP212.9

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 李建中,李金寶,石勝飛;傳感器網(wǎng)絡(luò)及其數(shù)據(jù)管理的概念、問題與進(jìn)展[J];軟件學(xué)報(bào);2003年10期

2 ;人物[J];現(xiàn)代制造;2002年12期

本文編號(hào)：1397673