【摘要】：無(wú)線多媒體傳感器網(wǎng)絡(luò),是一種新型的傳感器網(wǎng)絡(luò),由具有音頻、視頻、圖像等多媒體信息感知功能的傳感器節(jié)點(diǎn)組成的網(wǎng)絡(luò)。在該網(wǎng)絡(luò)中,由于大量傳感器節(jié)點(diǎn)隨機(jī)分布在監(jiān)測(cè)區(qū)域內(nèi),可能導(dǎo)致多個(gè)傳感器節(jié)點(diǎn)同時(shí)覆蓋一個(gè)目標(biāo)或目標(biāo)有遺漏等問(wèn)題,這樣會(huì)造成傳感器資源的浪費(fèi)和網(wǎng)絡(luò)性能的下降,為了實(shí)現(xiàn)有效的監(jiān)測(cè),監(jiān)控全部的目標(biāo)。即用最少的傳感器覆蓋全部的目標(biāo),這就是全目標(biāo)覆蓋問(wèn)題。本課題為解決全目標(biāo)覆蓋問(wèn)題,從以下三方面進(jìn)行研究,具體如下:由于全目標(biāo)問(wèn)題屬于NP-hard問(wèn)題,而群智能優(yōu)化算法是解決該問(wèn)題最為有效的方法。引力搜索算法是該領(lǐng)域現(xiàn)在最具前沿、最具典型性、性能最優(yōu)的進(jìn)化算法之一,與其他群智能優(yōu)化算法相比,引力搜索算法在解決無(wú)線傳感器網(wǎng)絡(luò)全目標(biāo)覆蓋問(wèn)題上具有一定優(yōu)勢(shì),但是在實(shí)際無(wú)線多媒體傳感器網(wǎng)絡(luò)中,所用的傳感器節(jié)點(diǎn)數(shù)量都非常多,這對(duì)核心優(yōu)化算法的性能提出更大要求。為了提高基礎(chǔ)引力搜索算法的優(yōu)化性能,在原有進(jìn)化策略的基礎(chǔ)上引入了差分變異策略;為了平衡算法的全局探索和局部搜索能力,引入權(quán)重函數(shù)公式;為最大限度的防止算法陷入局部最優(yōu)解,本課題把質(zhì)量值的大小進(jìn)行降序排列,將個(gè)體分為優(yōu)秀、中間、劣質(zhì)三類(lèi),在不同的迭代時(shí)期,采用不同類(lèi)別的個(gè)體進(jìn)行引力的計(jì)算,綜合以上分析提出一種基于權(quán)重函數(shù)分段的引力搜索算法。通過(guò)仿真實(shí)驗(yàn),證明本課題所提算法與其它改進(jìn)算法相比,收斂精度大部分可以達(dá)到理論最優(yōu)值,收斂速度明顯加快。為貼近無(wú)線多媒體傳感器網(wǎng)絡(luò)的實(shí)際監(jiān)測(cè)場(chǎng)景,提高覆蓋控制算法的實(shí)際應(yīng)用效果,建立三維有向感知模型的全目標(biāo)覆蓋數(shù)學(xué)模型。通過(guò)分析三維有向感知模型的拓?fù)浣Y(jié)構(gòu),明確各點(diǎn)坐標(biāo),經(jīng)過(guò)數(shù)學(xué)推導(dǎo),確定目標(biāo)覆蓋條件,即目標(biāo)同時(shí)滿足在傳感器的感知范圍之內(nèi)和區(qū)域視角中,判斷出傳感器與目標(biāo)的覆蓋關(guān)系,建立全目標(biāo)覆蓋數(shù)學(xué)模型。為解決全目標(biāo)覆蓋問(wèn)題,提出了全目標(biāo)覆蓋控制算法。該算法通過(guò)調(diào)整各傳感器的仰俯角和偏向角,使每個(gè)傳感器之間相互配合覆蓋全部目標(biāo)。而調(diào)整傳感器的仰俯角和偏向角屬于一個(gè)優(yōu)化問(wèn)題,從而采用本課題提出的基于權(quán)重函數(shù)分段的引力搜索算法作為解決該優(yōu)化問(wèn)題的核心算法,實(shí)驗(yàn)結(jié)果表明,該算法能夠用較少的傳感器覆蓋全部的目標(biāo)。
[Abstract]:Wireless multimedia sensor network (WSN) is a new type of sensor network, which is composed of sensor nodes with the functions of audio, video, image and other multimedia information perception. In this network, because a large number of sensor nodes are randomly distributed in the monitoring area, it may lead to multiple sensor nodes covering one target or missing targets at the same time, which will lead to the waste of sensor resources and the degradation of network performance. To achieve effective monitoring, monitor all targets. That is, using the least sensor to cover all the targets, this is the whole target coverage problem. In order to solve the whole target coverage problem, this paper studies the following three aspects: because the whole objective problem belongs to the NP-hard problem, the swarm intelligence optimization algorithm is the most effective method to solve the problem. Gravitational search algorithm is one of the most advanced, typical and optimal evolutionary algorithms in this field, compared with other swarm intelligence optimization algorithms. Gravity search algorithm has some advantages in solving the problem of full target coverage in wireless sensor networks, but in practical wireless multimedia sensor networks, the number of sensor nodes is very large. This puts forward more requirements for the performance of the core optimization algorithm. In order to improve the optimization performance of the basic gravitational search algorithm, the differential mutation strategy is introduced on the basis of the original evolutionary strategy, and the weight function formula is introduced to balance the global exploration and local search ability of the algorithm. In order to prevent the algorithm from falling into the local optimal solution, in this paper, the size of the mass value is arranged in descending order, and the individuals are divided into three categories: excellent, intermediate and inferior. In different iteration periods, different classes of individuals are used to calculate the gravity. Based on the above analysis, a gravity search algorithm based on weight function segmentation is proposed. The simulation results show that compared with other improved algorithms, the convergence accuracy of the proposed algorithm can reach the theoretical optimal value, and the convergence speed is obviously accelerated. In order to get close to the actual monitoring scene of wireless multimedia sensor network and improve the practical application effect of coverage control algorithm, a full target coverage mathematical model of 3D directed perception model is established. By analyzing the topological structure of the 3D directed perception model and defining the coordinates of each point, the target coverage conditions are determined by mathematical derivation, that is, the target is satisfied within the sensor's perceptual range and the regional perspective. The relation between sensor and target coverage is determined, and the mathematical model of full target coverage is established. In order to solve the problem of full target coverage, a full target coverage control algorithm is proposed. By adjusting the pitch angle and deflection angle of each sensor, the algorithm can cover all the targets by matching each sensor with each other. Adjusting the pitch angle and deflection angle of the sensor belongs to an optimization problem, so the gravity search algorithm based on the weight function segmentation is used as the core algorithm to solve the optimization problem. The experimental results show that, The algorithm can cover all targets with fewer sensors.
【學(xué)位授予單位】：東北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP212.9;TN919.8

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