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类型 基础研究 预答辩日期 2018-03-09
开始(开题)日期 2016-12-22 论文结束日期 2018-01-15
地点 李文正楼北512 论文选题来源 国家社科规划、基金项目     论文字数 6.4 (万字)
题目 软件定义无线网络中资源分配算法研究
主题词 软件定义无线网络,资源分配,无线资源和云资源,能效最优,集中式算法
摘要 为了满足无线通信业务迅猛增长的需求,未来通信系统需要具备更强的灵活性和鲁棒性,软件定义网络(Software Defined Networking,SDN)能够管理日益复杂的网络结构和提供多样化的服务,其中资源分配是优化网络资源和保证用户服务质量(Quality of Service,QoS)的关键技术。本学位论文着重研究软件定义无线网络(Software Defined Wireless Networks,SDWN)架构中的资源分配算法,主要包括SDWN中基于半定规划的高精度定位算法、软件定义无线传感网(Software Defined Wireless Sensor Networks,SDWSN)中最小化能耗的资源分配算法,软件定义蜂窝网(Software Defined Cellular Networks,SDCN)中基于能效最优的资源分配算法,以及移动自组织云网络(Ad Hoc Mobile Cloud,AHMC)中基于定价的资源分配算法等。 论文的主要研究工作如下: 1. 针对SDWN场景中实现移动目标精确定位的问题,提出一种集中式的高精度定位算法。该算法中,移动终端采用基于OpenFlow流表转发的方式,将采集的测距信息和惯导信息上传至SDN控制器。在控制器端,将获得的测距误差和步长估计值分别建模为高斯混合随机变量,并通过最大似然估计确定移动终端的位置坐标。为了降低最大似然估计的算法复杂度,通过Jenson不等式和半定松弛,将原始NP难问题转化为凸优化问题。进而,提出一种非高斯噪声条件下基于半定规划的定位算法,从而获得凸问题的全局最优解,即原问题的次优解。仿真和实验结果表明,所提的算法较传统的滤波算法可以获得更高的定位精度,特别地,当状态空间模型中的系统噪声和观测噪声不再服从高斯分布时,所提算法可以通过混合模型对非高斯噪声进行近似,以提升定位性能,从而为SDWN中的上层服务奠定基础。 2. 针对SDWSN中降低传感器节点能量消耗的问题,提出一种最小化节点能耗的资源分配算法。该算法考虑传感器节点传输所需的最小信干噪比,以最小化传感器节点能耗为目标建立优化问题。其次,通过松弛将原非凸问题转换为凸优化问题进行求解,提出一种集中式的自适应带宽和功率分配的资源分配算法。随后,为了分析所提算法的性能,重点阐述了两个特例,即自适应带宽分配算法和自适应功率分配算法。为了获取和利用网络的全局信息,设计一种基于OpenFlow通信协议的集中式资源分配方案。作为对比,给出一种分布式自适应带宽和功率分配的资源分配方案。仿真结果表明,所提集中式算法可以更好地权衡功率和带宽的利用,同时,通过全局优化可以减少小区大小和节点异质性对网络整体性能的影响。 3. 针对SDCN架构下提高异构网络中接入用户能效的问题,提出一种基于能效最优的资源分配算法。该算法考虑QoS需求和干扰容限,建立最大化网络能效的优化问题。其次,为了降低求解原混合整数规划问题的算法复杂度,通过松弛将原问题转化为凸优化,提出一种集中式资源分配算法。为了分析所提算法性能,采用柯西不等式获得原优化目标的上下界,将原集中式优化问题转化为分布式的非合作博弈问题。进而,在满足最大最小公平准则的条件下,给出了一种分布式能效最优算法作为比较。仿真结果表明,相比较分布式算法而言,所提集中式算法能够提高Femtocell网络的能效,更加接近能效性能的上界,同时能够提升网络的吞吐量。 4. 针对AHMC中高效利用无线资源和云计算资源的问题,提出一种基于定价的资源分配的算法。首先,综合考虑通信与计算成本,以最大化移动用户或基站的个体效用为目标函数,构造买家-卖家博弈模型。用户和基站在SDN控制器的集中管理下进行定价协商,从而达到Stackelberg均衡点。并分别针对准静态和动态场景,采用统一定价和非统一定价策略,提出一种基于定价的资源分配算法。同时,在SDN的框架下,给出了基于OpenFlow协议的联合任务卸载和资源分配方案,即分别在用户侧和基站侧部署流表规则,以增强网络功能的灵活性。一方面,在定价协商和任务卸载的不同阶段,可以通过增删流表,满足不同用户不同类型数据的传输需求。另一方面,在动态场景中,基站或者用户可以通过更新流表规则,提高算法收敛速度,以快速达到均衡点。仿真结果表明:所提算法可以通过任务卸载,使得买家充分利用网络中的云计算资源,并通过非均匀定价拍卖的方式激励基站和其他用户为买家提供无线资源和计算资源。
英文题目 RESEARCH ON RESOURCE ALLOCATION ALGORITHMS IN SOFTWARE DEFINED WIRELESS NETWORKS
英文主题词 Software Defined Wireless Networks, resource allocation, wireless and cloud resources, energy-efficient, centralized algorithm
英文摘要 In order to meet the rapidly growing demand for wireless services, future communications systems need to be more flexible and robust. Software Defined Networking (SDN) is a recent networking architecture with promising properties relative to the management of increasingly complex network structures, thus providing diversified services. Specifically, resource allocation is one of the key technologies to optimize network resources and ensure Quality of Service (QoS). This dissertation focuses on resource allocation algorithms in Software Defined Wireless Networks (SDWN), including a high precision localization algorithm based on semi-definite programming in SDWN, a wireless resource allocation algorithm for energy consumption minimization in Software Defined Wireless Sensor Networks (SDWSN), an energy-efficient resource allocation algorithm in Software Defined Cellular Networks (SDCN), and a price-based resource allocation algorithm in Ad Hoc Mobile Cloud (AHMC). The main contributions of this dissertation can be summarized as follows: 1. To obtain the precise location estimation of mobile targets, a centralized localization algorithm is proposed in SDWN. Firstly, the mobile targets obtain the ranging information and inertial information, and then upload the information to the controller based on OpenFlow forwarding scheme. Then, both the ranging measurement errors and step size are modeled using Gaussian mixtures, respectively, and the locations of the mobile nodes are determined by the maximum likelihood estimator. Additionally, by using Jenson’s inequality and semidefinite relaxation, the initial NP-hard problem is transformed into a convex optimization problem, which globally optimal solution could be attained using semidefinite programming. Simulation and experimental results show that the proposed algorithm can achieve higher positioning accuracy than the traditional algorithms. Especially, when the system noise and observation noise in the state space model are no more following Gaussian distributions, the propose algorithm could improve the localization performance with the approximation of the noise distribution, thus, laying the foundation for upper-level services in SDWN. 2. To solve the energy limitation of sensor nodes and extend the lifetime of SDWSN, a wireless resource allocation algorithm is proposed to minimize the energy consumption. Considering the minimum signal to interference plus noise ratio required for the transmission, an optimization problem is formulated to minimize total energy consumed by the sensor nodes in SDWSN. Then, the original non-convex problem is transformed into a convex optimization problem via convex relaxation, and a centralized algorithm is proposed to realize adaptive bandwidth and power allocation. Besides, to analyze the performance of the proposed algorithm, two special cases are elaborated for adaptive bandwidth allocation and adaptive power allocation, respectively. Moreover, in order to fully acquire and utilize the global information of the network, a centralized resource allocation scheme is designed based on the OpenFlow communication protocol. In contrast, a distributed resource allocation scheme is also given to serve as a performance benchmark. The simulation results show that the proposed centralized algorithm could balance the utilization of power and bandwidth resources. Meanwhile, by taking advantage of global optimization, the proposed centralized algorithm could reduce the impact of network size and node heterogeneity on the overall network performance. 3. To improve the energy efficiency (EE) of the users accessed through Femtocell, an energy efficient resource allocation algorithm is proposed in SDCN architecture. Considering the user QoS and cross-tier interference tolerance, a mixed integer programming (MIP) problem is developed to maximize the network EE. Then, to reduce the complexity of solving the original nonlinear and nonconvex problem, a centralized resource allocation algorithm is proposed via convex relaxation. Additionally, a distributed non-cooperative game is derived using Cauchy inequality to act as the performance baseline of the proposed centralized algorithm. Furthermore, an SDN-based centralized resource allocation scheme is designed with elaborate forwarding rules. The simulation results show that the proposed centralized algorithm could be much closer to the upper bound of EE than the distributed algorithm at the cost of computation complexity, and improve the overall network throughput as well. 4. To study the efficient utilization of wireless and computing resources, a price-based resource allocation algorithm is proposed in AHMC. First, by taking into consideration of communication and computational costs, a buyer-seller game is formulated to maximize the individual utility of mobile users and base stations, which is handled by the SDN controller. Then, the Stackelberg equilibrium of the game is derived in a quasi-static scenario with non-uniform pricing and uniform pricing, respectively. Additionally, an OpenFlow-based forwarding rules placement is designed to make the game reach the equilibrium more efficiently. Furthermore, the proposed algorithm is extended to the dynamic scenario with guaranteed convergence. Simulation results show that through workload offloading, the buyer can make full use of the cloud computing resource in the AHMC, and in the non-uniform pricing scheme the base stations and other users could be motivated to provide more wireless and cloud computing resources.
学术讨论
主办单位时间地点报告人报告主题
东南大学移动通信国家重点实验室 2014.10.17 中国无线谷2号楼2324会议室 黄建伟 Incentive mechanisms for user-provided networks
东南大学移动通信国家重点实验室 2015.10.16 中国无线谷1号楼1319会议室 杨伟豪 Cut-set bounds for networks with zero-delay nodes
东南大学移动通信国家重点实验室 2015.10.21 中国无线谷1号楼1319会议室 Gérard Memmi Data protection and fragmentation
东南大学移动通信国家重点实验室 2016.6.3 中国无线谷1号楼1319会议室 黄建伟 Crowdsourced mobile video streaming
东南大学移动通信国家重点实验室 2017.4.19 中国无线谷1号楼1319会议室 李俨 车联网之路-从技术到应用
东南大学移动通信国家重点实验室 2017.5.16 中国无线谷1号楼1319会议室 薛国良 Opportunities and challenges in crowdsourcing, smart device authentication, and vehicle to grid communications
东南大学移动通信国家重点实验室 2017.5.16 中国无线谷1号楼1319会议室 宋文战 Fog computing in cyber-physical system and security
东南大学移动通信国家重点实验室 2017.7.10 中国无线谷2号楼2324会议室 林子怀 Distributed resource allocation and spectrum sharing in future heterogeneous wireless cellular networks
IEEE北京分会 福建光学学会 2014.11.15 中国福州 章跃跃 Indoor positioning algorithm for mobile objects based on track smoothing
国家电网公司 2015.1.12 中国南京 章跃跃 室内移动目标精确定位系统的设计与实现
东南大学移动通信国家重点实验室 2015.11.13 中国无线谷2号楼2324会议室 章跃跃 窄带物联网
东南大学移动通信国家重点实验室 2015.6.29 中国无线谷1号楼1319会议室 Philippe Martins Spatial methods for planning and dimensioning of wireless systems
东南大学移动通信国家重点实验室 2017.4.12 中国无线谷2号楼2324会议室 章跃跃 异构网络融合的资源管理及优化
     
学术会议
会议名称时间地点本人报告本人报告题目
ITU 2017万花筒国际学术会议(ITU 南京邮电大学) 2017.11.27-29 中国南京
2017“现代无线通信论坛”WAWC(东南大学移动通信国家重点实验室) 2017.7.18 中国南京
2015“现代无线通信论坛”(东南大学移动通信国家重点实验室) 2015.7.9 中国南京
IEEE PIMRC 2016 2016.9.4-6 西班牙 瓦伦西亚 Semidefinite programming based resource allocation for energy consumption minimization in software defined wireless sensor networks
IEEE PIMRC 2016 2016.9.4-6 西班牙 瓦伦西亚 Non-line-of-sight mitigation in wireless localization and tracking via semidefinite programming
VTC2016-Fall 2016.9.18-21 加拿大 蒙特利尔 Indoor positioning and tracking using particle filters with suboptimal importance density
VTC2016-Spring(东南大学) 2016.5.15-18 中国南京 A semidefinite relaxation approach to positioning in hybrid sensor networks
WCSP 2015(中国人民解放军大学,南京邮电大学) 2017.10.15-17 中国南京 A single-anchor calibration indoor positioning system using heterogeneous sensors
WCSP 2017 (东南大学) 2017.10.11-13 中国南京 Localization for visible light communication with practical non-Gaussian noise model
IEEE/CIC ICCC 2017 (山东大学) 2017.10.22-24 中国青岛 Robust fingerprinting-based localization using directed graphical models
     
代表作
论文名称
RSS-based localization in WSNs using Gaussian mixture model via semidefinite relaxation
A semidefinite programming based localisation and tracking algorithm using Gaussian mixture modellin
超密集网络中基于能效最优的资源分配算法
Non-line-of-sight mitigation in wireless localization and tracking via semidefinite programming
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
张顺颐 正高 教授 博导 南京邮电大学
王海 正高 教授 博导 陆军工程大学
郑军 正高 教授 博导 东南大学
宋铁成 正高 教授 博导 东南大学
徐平平 正高 教授 博导 东南大学
      
答辩秘书信息
姓名职称工作单位备注
燕锋 副高 副教授 东南大学