RFID系統(tǒng)優(yōu)化調(diào)度模型及算法研究
發(fā)布時間：2018-08-01 09:15
【摘要】：隨著物聯(lián)網(wǎng)技術(shù)的發(fā)展和泛在應(yīng)用,作為感知層的RFID系統(tǒng)也發(fā)展為多個閱讀器組成的近距離無線局域網(wǎng)絡(luò)系統(tǒng),實(shí)現(xiàn)廣域范圍內(nèi)標(biāo)簽標(biāo)識物品的互聯(lián)、信息感知和共享。由于RFID系統(tǒng)本身的動態(tài)性和不確定性,系統(tǒng)的資源分配與優(yōu)化調(diào)度問題一般是非線性、多目標(biāo)、大規(guī)模的復(fù)雜系統(tǒng)優(yōu)化問題。研究復(fù)雜環(huán)境下RFID系統(tǒng)的優(yōu)化調(diào)度模型及其智能優(yōu)化算法,尋求在資源受限約束條件下的系統(tǒng)運(yùn)行優(yōu)化調(diào)度方案,成為物聯(lián)網(wǎng)技術(shù)領(lǐng)域研究的面臨的重要課題。此類課題的研究,對提高現(xiàn)有RFID系統(tǒng)的運(yùn)行效率、服務(wù)質(zhì)量以及自動化、智能化、協(xié)同化水平,推動物聯(lián)網(wǎng)領(lǐng)域技術(shù)的進(jìn)步,具有重要的理論意義和應(yīng)用價值。論文針對目前RFID系統(tǒng)運(yùn)行調(diào)度中普遍存在的優(yōu)化問題,在對國內(nèi)外相關(guān)研究綜述的基礎(chǔ)上,分析了現(xiàn)有系統(tǒng)的組成及運(yùn)行調(diào)度模式,推導(dǎo)了閱讀器識別范圍的計算模型,確定了系統(tǒng)優(yōu)化運(yùn)行的邊界參數(shù),建立了多閱讀器優(yōu)化調(diào)度模型及求解模型的B細(xì)胞優(yōu)化算法,設(shè)計了識別大量被動標(biāo)簽的DFSA時隙段識別算法以及多閱讀器協(xié)作的分組標(biāo)簽識別算法,最后設(shè)計了一個基于情景感知的RFID系統(tǒng)框架,在MATLAB環(huán)境下,對不同標(biāo)準(zhǔn)下的RFID系統(tǒng)場景進(jìn)行了仿真實(shí)驗,驗證了所提模型及算法的有效性和實(shí)用性。論文研究內(nèi)容融合物聯(lián)網(wǎng)技術(shù)、信息科學(xué)、計算機(jī)科學(xué)、自動化科學(xué)、運(yùn)籌學(xué)、概率統(tǒng)計學(xué)、進(jìn)化計算以及管理科學(xué)等多個學(xué)科的交叉領(lǐng)域。論文的主要創(chuàng)新工作包括以下內(nèi)容:(1)針對現(xiàn)有rfid系統(tǒng)內(nèi)多閱讀器環(huán)境(mre)和稠密閱讀器環(huán)境(dre)中,閱讀器之間存在的干擾和碰撞問題,推導(dǎo)了基于信號干擾噪聲比(sinr)的閱讀器識別范圍計算模型,根據(jù)閱讀器功率和頻道資源確定了產(chǎn)生閱讀器-標(biāo)簽碰撞(rtc)問題的臨界距離。在此基礎(chǔ)上,針對多閱讀器共享時隙和頻道產(chǎn)生的資源競爭問題,把多閱讀器調(diào)度分解為對孤立閱讀器節(jié)點(diǎn)、多閱讀器節(jié)點(diǎn)和稠密閱讀器節(jié)點(diǎn)的優(yōu)化調(diào)度問題,提出了資源分配的約束條件以及保證調(diào)度公平性的約束條件,建立了多閱讀器調(diào)度的動態(tài)規(guī)劃模型。該模型符合rfid標(biāo)準(zhǔn)和協(xié)議,有效降低了閱讀器-閱讀器碰撞(rrc)問題,避免了rtc問題;(2)提出了基于幾何概率分布函數(shù)求解模型的b細(xì)胞優(yōu)化算法(gd-oa-bcell)以及考慮調(diào)度公平性的bgd-oa-bcell算法,將動態(tài)規(guī)劃模型按照稠密閱讀器節(jié)點(diǎn)和非稠密閱讀器節(jié)點(diǎn)細(xì)分成底層目標(biāo)函數(shù)和頂層目標(biāo)函數(shù),以全局識別范圍最大和工作閱讀器最多為目標(biāo)并統(tǒng)一作為抗原,將每一套可行調(diào)度方案作為抗體,根據(jù)親和度值劃分為優(yōu)秀個體和普通個體,基于幾何概率分布函數(shù)分別對普通個體的稠密閱讀器節(jié)點(diǎn)基因段提出了底層區(qū)域變異算子,對優(yōu)秀個體的非稠密閱讀器節(jié)點(diǎn)基因段提出了頂層多點(diǎn)變異算子,加快了算法的收斂速度,提高了抗體的多樣性,避免了局部最優(yōu)。gd-oa-bcell算法得到的優(yōu)化調(diào)度方案,既有效避免了rrc和rtc問題,又保證了公平性,以調(diào)度多閱讀器協(xié)同、并行工作。bgd-oa-bcell在此基礎(chǔ)上,具有更好的公平性和實(shí)用性;(3)提出了基于dfsa框架的時隙采樣極大似然函數(shù)標(biāo)簽數(shù)估計方法以及相應(yīng)的標(biāo)簽識別算法(sia),針對sia算法幀調(diào)整不穩(wěn)定的問題,進(jìn)一步設(shè)計了時隙段采樣幀調(diào)整算法(SS-ASF),以降低TTC問題。仿真實(shí)驗表明,該標(biāo)簽數(shù)估計方法在標(biāo)簽數(shù)較大時依然能夠保持理想的估計誤差,SS-ASF在SIA基礎(chǔ)上進(jìn)一步提高時隙利用率和標(biāo)簽識別速度,同時顯著減少幀調(diào)整次數(shù),實(shí)現(xiàn)了閱讀器在標(biāo)簽識別過程的高效性;(4)針對RFID系統(tǒng)中多閱讀器識別大量被動標(biāo)簽的需求,提出了基于標(biāo)簽分組的標(biāo)簽識別算法(G-SIA),并進(jìn)一步設(shè)計了分組多級隨機(jī)數(shù)標(biāo)簽識別算法(GM-IP)以及多閱讀器協(xié)同并行工作方式,采用三種負(fù)載均衡策略,解決算法中的負(fù)載不均衡問題。仿真實(shí)驗表明,G-SIA和GM-IP能夠有效處理數(shù)量規(guī)模較大的標(biāo)簽,顯著提高時隙利用率,實(shí)現(xiàn)了多閱讀器協(xié)同并行識別過程。在上述研究的基礎(chǔ)上,設(shè)計了基于情景感知的RFID系統(tǒng)自優(yōu)化調(diào)度子系統(tǒng)(AODS-Bcell)框架,并在MATLAB下開發(fā)了仿真程序,對符合EPCGlobal C1 G2標(biāo)準(zhǔn)和GB/T 29768-2013標(biāo)準(zhǔn)規(guī)范下的RFID系統(tǒng)場景進(jìn)行了仿真實(shí)驗,驗證了所提模型和算法的有效性,以及與RFID系統(tǒng)標(biāo)準(zhǔn)的兼容性。AODS-Bcell以已有優(yōu)化調(diào)度方案為基礎(chǔ),結(jié)合情景感知參數(shù),可進(jìn)一步實(shí)現(xiàn)自優(yōu)化過程。研究成果對現(xiàn)有RFID系統(tǒng)優(yōu)化調(diào)度及規(guī)劃設(shè)計具有重要的借鑒作用和實(shí)際應(yīng)用價值。
[Abstract]:With the development and widespread application of the Internet of things technology, the RFID system, as a perceptual layer, also develops into a wireless local network system composed of multiple readers, which realizes the interconnection of labels identifying items in the wide area, information perception and sharing. Because of the dynamic and uncertainty of the RFID system itself, the resource allocation and optimization of the system The degree problem is generally nonlinear, multi-objective and large-scale complex system optimization problem. The optimization scheduling model of RFID system and its intelligent optimization algorithm under the complex environment are studied, and the optimal scheduling scheme for system operation under the constraint of resource constraints is sought, and it becomes an important subject in the research of the technology domain of the Internet of things. In order to improve the operating efficiency of the existing RFID system, the quality of service, the automation, the intelligence, the level of cooperation and the advancement of the technology in the field of animal networking, it has important theoretical significance and application value. This paper, based on the general optimization problems of the current RFID system operation and scheduling, is based on the summary of related research at home and abroad. The composition and operation scheduling mode of the existing system are analyzed, the calculation model of the reader recognition range is derived, the boundary parameters of the optimized operation of the system are determined, the B cell optimization algorithm of the multi reader optimization scheduling model and the solution model is established, and the DFSA time slot recognition algorithm for identifying a large number of passive tags and the multi reader association are designed. In the end, a RFID system framework based on situational awareness is designed. Under the environment of MATLAB, the simulation experiments of the RFID system scenes under different standards are carried out to verify the validity and practicability of the proposed model and algorithm. The research content is integrated with the technology of Internet of things, information science, computer science, and automation. The main innovations of this paper are as follows: (1) the interference and collision between the readers in the existing RFID system and the dense reader environment (MRE) and the dense reader environment (DRE), and the derivation of the signal stem based on the signal stem are derived. According to the reader power and channel resources, the critical distance of the reader - label collision (RTC) problem is determined according to the reader power and channel resources. On this basis, the multi reader scheduling is decomposed to the isolated reader node for the sharing of time slot and channel resource competition in the multi reader. The optimal scheduling problem of reader node and dense reader node is proposed. Constraints of resource allocation and constraints of scheduling fairness are proposed. A dynamic programming model for multiple reader scheduling is established. The model conforms to RFID standards and protocols, effectively reduces the reader reader collision (RRC) problem and avoids the RTC problem. (2) (2) The B cell optimization algorithm (gd-oa-bcell) based on the geometric probability distribution function (geometric probability distribution function) and the bgd-oa-bcell algorithm considering scheduling fairness are presented. The dynamic programming model is subdivided into the underlying objective function and the top target function according to the dense reader node and the non dense reader node, and the global recognition range is the largest and the work is read. The device is the target and unified as an antigen. Each set of feasible scheduling schemes is used as an antibody. According to the affinity value, it is divided into excellent individuals and ordinary individuals. Based on the geometric probability distribution function, the underlying region mutation operator is proposed for the dense reader node gene segment of the ordinary individual, and the non dense reader node of the outstanding individual is used. The gene segment proposes the top-level multipoint mutation operator, which speeds up the convergence speed of the algorithm, improves the diversity of the antibody and avoids the optimal scheduling scheme obtained by the local optimal.Gd-oa-bcell algorithm. It not only effectively avoids the RRC and RTC problems, but also guarantees the fairness to dispatch the multi reader synergy and the parallel work.Bgd-oa-bcell. It has better fairness and practicability; (3) a method of estimation of the maximum likelihood function tag number of time slot sampling and the corresponding label recognition algorithm (SIA) based on the DFSA framework are proposed. In view of the problem of the instability of the frame adjustment in the SIA algorithm, a time slot sampling frame adjustment algorithm (SS-ASF) is designed to reduce the TTC problem. Simulation experiments show that the label is the standard. The number estimation method can still maintain the ideal estimation error when the number of tags is large. SS-ASF can further improve the time slot utilization and label recognition speed on the basis of SIA, and reduce the number of frame adjustment significantly, and realize the efficiency of the reader in the label recognition process. (4) a large number of passive tags are identified for the multi reader in the RFID system. The label recognition algorithm based on label packet (G-SIA) is proposed, and the packet multilevel random number label recognition algorithm (GM-IP) and multi reader cooperative parallel working mode are designed. Three load balancing strategies are used to solve the load imbalance in the algorithm. The simulation experiment shows that the number of G-SIA and GM-IP can effectively deal with the number. On the basis of the above research, the framework of RFID system self optimized scheduling subsystem (AODS-Bcell) is designed on the basis of the above research, and the simulation process is developed under MATLAB, which conforms to the EPCGlobal C1 G2 standard and the GB/T 29768-2013 standard. The simulation experiment of RFID system scene under the quasi standard has been carried out to verify the validity of the proposed model and algorithm, and the compatibility with the standard of the RFID system..AODS-Bcell, based on the existing optimal scheduling scheme, combined with the situational awareness parameters, can further realize the self optimization process. The research results are the optimal scheduling and planning of the existing RFID system. It has important reference function and practical application value.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP391.44;TN929.5
本文編號：2157102
[Abstract]:With the development and widespread application of the Internet of things technology, the RFID system, as a perceptual layer, also develops into a wireless local network system composed of multiple readers, which realizes the interconnection of labels identifying items in the wide area, information perception and sharing. Because of the dynamic and uncertainty of the RFID system itself, the resource allocation and optimization of the system The degree problem is generally nonlinear, multi-objective and large-scale complex system optimization problem. The optimization scheduling model of RFID system and its intelligent optimization algorithm under the complex environment are studied, and the optimal scheduling scheme for system operation under the constraint of resource constraints is sought, and it becomes an important subject in the research of the technology domain of the Internet of things. In order to improve the operating efficiency of the existing RFID system, the quality of service, the automation, the intelligence, the level of cooperation and the advancement of the technology in the field of animal networking, it has important theoretical significance and application value. This paper, based on the general optimization problems of the current RFID system operation and scheduling, is based on the summary of related research at home and abroad. The composition and operation scheduling mode of the existing system are analyzed, the calculation model of the reader recognition range is derived, the boundary parameters of the optimized operation of the system are determined, the B cell optimization algorithm of the multi reader optimization scheduling model and the solution model is established, and the DFSA time slot recognition algorithm for identifying a large number of passive tags and the multi reader association are designed. In the end, a RFID system framework based on situational awareness is designed. Under the environment of MATLAB, the simulation experiments of the RFID system scenes under different standards are carried out to verify the validity and practicability of the proposed model and algorithm. The research content is integrated with the technology of Internet of things, information science, computer science, and automation. The main innovations of this paper are as follows: (1) the interference and collision between the readers in the existing RFID system and the dense reader environment (MRE) and the dense reader environment (DRE), and the derivation of the signal stem based on the signal stem are derived. According to the reader power and channel resources, the critical distance of the reader - label collision (RTC) problem is determined according to the reader power and channel resources. On this basis, the multi reader scheduling is decomposed to the isolated reader node for the sharing of time slot and channel resource competition in the multi reader. The optimal scheduling problem of reader node and dense reader node is proposed. Constraints of resource allocation and constraints of scheduling fairness are proposed. A dynamic programming model for multiple reader scheduling is established. The model conforms to RFID standards and protocols, effectively reduces the reader reader collision (RRC) problem and avoids the RTC problem. (2) (2) The B cell optimization algorithm (gd-oa-bcell) based on the geometric probability distribution function (geometric probability distribution function) and the bgd-oa-bcell algorithm considering scheduling fairness are presented. The dynamic programming model is subdivided into the underlying objective function and the top target function according to the dense reader node and the non dense reader node, and the global recognition range is the largest and the work is read. The device is the target and unified as an antigen. Each set of feasible scheduling schemes is used as an antibody. According to the affinity value, it is divided into excellent individuals and ordinary individuals. Based on the geometric probability distribution function, the underlying region mutation operator is proposed for the dense reader node gene segment of the ordinary individual, and the non dense reader node of the outstanding individual is used. The gene segment proposes the top-level multipoint mutation operator, which speeds up the convergence speed of the algorithm, improves the diversity of the antibody and avoids the optimal scheduling scheme obtained by the local optimal.Gd-oa-bcell algorithm. It not only effectively avoids the RRC and RTC problems, but also guarantees the fairness to dispatch the multi reader synergy and the parallel work.Bgd-oa-bcell. It has better fairness and practicability; (3) a method of estimation of the maximum likelihood function tag number of time slot sampling and the corresponding label recognition algorithm (SIA) based on the DFSA framework are proposed. In view of the problem of the instability of the frame adjustment in the SIA algorithm, a time slot sampling frame adjustment algorithm (SS-ASF) is designed to reduce the TTC problem. Simulation experiments show that the label is the standard. The number estimation method can still maintain the ideal estimation error when the number of tags is large. SS-ASF can further improve the time slot utilization and label recognition speed on the basis of SIA, and reduce the number of frame adjustment significantly, and realize the efficiency of the reader in the label recognition process. (4) a large number of passive tags are identified for the multi reader in the RFID system. The label recognition algorithm based on label packet (G-SIA) is proposed, and the packet multilevel random number label recognition algorithm (GM-IP) and multi reader cooperative parallel working mode are designed. Three load balancing strategies are used to solve the load imbalance in the algorithm. The simulation experiment shows that the number of G-SIA and GM-IP can effectively deal with the number. On the basis of the above research, the framework of RFID system self optimized scheduling subsystem (AODS-Bcell) is designed on the basis of the above research, and the simulation process is developed under MATLAB, which conforms to the EPCGlobal C1 G2 standard and the GB/T 29768-2013 standard. The simulation experiment of RFID system scene under the quasi standard has been carried out to verify the validity of the proposed model and algorithm, and the compatibility with the standard of the RFID system..AODS-Bcell, based on the existing optimal scheduling scheme, combined with the situational awareness parameters, can further realize the self optimization process. The research results are the optimal scheduling and planning of the existing RFID system. It has important reference function and practical application value.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP391.44;TN929.5
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