本文選題：可充電傳感器網(wǎng)絡(luò)　切入點(diǎn)：時(shí)間片調(diào)度　出處：《南京郵電大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：可充電無(wú)線傳感器網(wǎng)絡(luò)技術(shù)正在成為許多應(yīng)用領(lǐng)域的關(guān)鍵技術(shù),如環(huán)境監(jiān)測(cè)、農(nóng)業(yè)生產(chǎn)、區(qū)域監(jiān)控等。而數(shù)據(jù)收集是無(wú)線傳感器網(wǎng)技術(shù)應(yīng)用關(guān)注的重要問(wèn)題之一�；谝苿�(dòng)sink的數(shù)據(jù)收集方案由于其所具有的優(yōu)點(diǎn)逐漸成為研究工作熱點(diǎn),數(shù)據(jù)收集算法在很大程度上影響著網(wǎng)絡(luò)工作性能,提升和優(yōu)化數(shù)據(jù)收集算法對(duì)推動(dòng)無(wú)線傳感器網(wǎng)絡(luò)技術(shù)的發(fā)展具有重要意義。本文首先研究了移動(dòng)sink在固定路徑情況下的數(shù)據(jù)收集算法,在可充電無(wú)線傳感網(wǎng)中,移動(dòng)sink周期性地沿著固定路徑運(yùn)動(dòng),同時(shí)收集附近單跳感應(yīng)節(jié)點(diǎn)發(fā)送來(lái)的數(shù)據(jù),傳感器節(jié)點(diǎn)隨機(jī)部署在路徑兩邊,并且能夠通過(guò)太陽(yáng)能進(jìn)行充電,為了最大化移動(dòng)sink收集數(shù)據(jù)的效用,本文設(shè)計(jì)了一種固定路徑的數(shù)據(jù)收集算法,我們將移動(dòng)sink的整個(gè)運(yùn)動(dòng)周期劃分為若干個(gè)等長(zhǎng)的時(shí)間片,通過(guò)分配時(shí)間片來(lái)決定移動(dòng)sink在各個(gè)時(shí)間片通信的感應(yīng)節(jié)點(diǎn),每個(gè)時(shí)間片都是盡可能分配給通信范圍內(nèi)數(shù)據(jù)效用最大的感應(yīng)節(jié)點(diǎn)。其次,本文研究了移動(dòng)sink路徑規(guī)劃算法,在一個(gè)可充電無(wú)線傳感器網(wǎng)絡(luò)中,移動(dòng)sink沿著預(yù)先規(guī)劃好的路徑在規(guī)定時(shí)延范圍內(nèi)收集感應(yīng)數(shù)據(jù),該路徑由若干停留點(diǎn)組成,移動(dòng)sink在停留點(diǎn)收集附近單跳節(jié)點(diǎn)發(fā)送來(lái)的感應(yīng)數(shù)據(jù),為了使移動(dòng)sink在各個(gè)停留點(diǎn)收集的總數(shù)據(jù)量最大,本文設(shè)計(jì)了移動(dòng)sink路徑規(guī)劃算法,算法首先通過(guò)網(wǎng)絡(luò)路由樹(shù)計(jì)算所有節(jié)點(diǎn)的預(yù)計(jì)收益,選擇收益最大的節(jié)點(diǎn)作為停留點(diǎn),并且,每次選擇停留點(diǎn)后,計(jì)算通過(guò)所有停留點(diǎn)的最短路徑,保證移動(dòng)sink在規(guī)定時(shí)延范圍內(nèi)回到出發(fā)點(diǎn)。最后,通過(guò)仿真實(shí)驗(yàn)對(duì)兩種情況下的算法性能進(jìn)行驗(yàn)證,試驗(yàn)結(jié)果表明兩種方案下的數(shù)據(jù)收集算法有著很好的表現(xiàn)。
[Abstract]:Rechargeable wireless sensor network technology is becoming a key technology in many application fields, such as environmental monitoring, agricultural production, Data collection is one of the most important issues in wireless sensor network application. Data collection based on mobile sink has become a hot research topic because of its advantages. Data collection algorithms affect the performance of the network to a large extent. It is important to improve and optimize the data collection algorithm for the development of wireless sensor network technology. Firstly, this paper studies the data collection algorithm of mobile sink in the case of fixed path, which can be used in rechargeable wireless sensor network. The mobile sink moves periodically along a fixed path while collecting data from nearby single-hop sensor nodes that are randomly deployed on either side of the path and can be charged by solar energy. In order to maximize the utility of mobile sink data collection, a fixed path data collection algorithm is designed in this paper. We divide the entire mobile sink motion cycle into several equal time slices. By allocating time slices to determine the sensing nodes of mobile sink communication in each time slice, each time slice is assigned to the sensor node with the greatest data utility in the communication range as far as possible. Secondly, the mobile sink path planning algorithm is studied in this paper. In a rechargeable wireless sensor network, mobile sink collects induction data within a specified delay range along a pre-planned path, which consists of a number of residence points. The mobile sink collects the sensing data from the single hop node nearby at the stop point. In order to make the total data collected by the mobile sink at each stop point maximum, a path planning algorithm for mobile sink is designed in this paper. The algorithm first calculates the expected income of all nodes through the network routing tree, and selects the node with the highest return as the stopover point, and calculates the shortest path through all the stopping points each time after selecting the stopover point. The mobile sink is guaranteed to return to the starting point within the specified time delay. Finally, the performance of the algorithm is verified by simulation experiments. The experimental results show that the data collection algorithm under the two schemes has a good performance.
【學(xué)位授予單位】：南京郵電大學(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)：1639241