实时操作系统(Real-Time Operating System,RTOS)被广泛应用于窄带物联网(Narrow Band Internet of Things,NB-IoT)设备之中。这类设备对体积、能耗与稳定性有着严格的限制。NB-IoT设备多采用宏内核的RTOS,能得到较好的运行性能,但要求...实时操作系统(Real-Time Operating System,RTOS)被广泛应用于窄带物联网(Narrow Band Internet of Things,NB-IoT)设备之中。这类设备对体积、能耗与稳定性有着严格的限制。NB-IoT设备多采用宏内核的RTOS,能得到较好的运行性能,但要求更多的硬件资源,并且内核中出现的问题很可能会导致整个系统崩溃。该文对传统RTOS进行改进,设计开发了无内存管理单元(Memory Management Unit,MMU)的微内核实时操作系统(nM-MKRTOS)。该系统针对NB-IoT中资源较少的设备,利用微内核的优势,其通过动态加载与链接(Dynamic Loading and Dynamic Linking,DL 2)技术实现内存复用和快速启动,并采用模块化开发的方式提高系统稳定性。在实际测试中,nM-MKRTOS通过内存复用技术将内存利用率提高了56.25%;在系统的启动测试中,通过在DL 2技术中引入权重加载,系统的核心功能在三个任务子集上的启动时间分别减少57.59%、52.55%与47.59%。该系统能够广泛应用于智慧农业、智慧校园等场合,能够降低系统成本,提高系统稳定性。展开更多
For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for...For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic Engineering(TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network’s Traffic Engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth,and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning(DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.展开更多
在室内停车场中应用基于RFID的LANDMARC算法进行车辆定位时,由于室内停车场的复杂结构以及多径效应的影响,车辆定位精度不能通过增加参考标签数目或均匀规则的部署参考标签等方式来提升。提出了一种基于虚拟RFID标签的室内定位算法(loca...在室内停车场中应用基于RFID的LANDMARC算法进行车辆定位时,由于室内停车场的复杂结构以及多径效应的影响,车辆定位精度不能通过增加参考标签数目或均匀规则的部署参考标签等方式来提升。提出了一种基于虚拟RFID标签的室内定位算法(location algorithm based on virtual tag,LAVT)。该算法通过近邻标签确定车辆的近邻区域,计算出近邻区域的外心并插入虚拟参考标签;通过虚拟参考标签替换原近邻标签、缩小近邻区域面积,使新近邻标签更临近待定位车辆,从而更精确地计算出车辆的位置。仿真实验表明:LAVT算法在室内停车场环境中将车辆定位精度提升了19.03%。LAVT算法应用于室内停车场环境中的车辆定位具有更好的适用性,能满足室内停车场车辆定位的基本需求。展开更多
文摘实时操作系统(Real-Time Operating System,RTOS)被广泛应用于窄带物联网(Narrow Band Internet of Things,NB-IoT)设备之中。这类设备对体积、能耗与稳定性有着严格的限制。NB-IoT设备多采用宏内核的RTOS,能得到较好的运行性能,但要求更多的硬件资源,并且内核中出现的问题很可能会导致整个系统崩溃。该文对传统RTOS进行改进,设计开发了无内存管理单元(Memory Management Unit,MMU)的微内核实时操作系统(nM-MKRTOS)。该系统针对NB-IoT中资源较少的设备,利用微内核的优势,其通过动态加载与链接(Dynamic Loading and Dynamic Linking,DL 2)技术实现内存复用和快速启动,并采用模块化开发的方式提高系统稳定性。在实际测试中,nM-MKRTOS通过内存复用技术将内存利用率提高了56.25%;在系统的启动测试中,通过在DL 2技术中引入权重加载,系统的核心功能在三个任务子集上的启动时间分别减少57.59%、52.55%与47.59%。该系统能够广泛应用于智慧农业、智慧校园等场合,能够降低系统成本,提高系统稳定性。
文摘For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic Engineering(TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network’s Traffic Engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth,and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning(DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.
文摘在室内停车场中应用基于RFID的LANDMARC算法进行车辆定位时,由于室内停车场的复杂结构以及多径效应的影响,车辆定位精度不能通过增加参考标签数目或均匀规则的部署参考标签等方式来提升。提出了一种基于虚拟RFID标签的室内定位算法(location algorithm based on virtual tag,LAVT)。该算法通过近邻标签确定车辆的近邻区域,计算出近邻区域的外心并插入虚拟参考标签;通过虚拟参考标签替换原近邻标签、缩小近邻区域面积,使新近邻标签更临近待定位车辆,从而更精确地计算出车辆的位置。仿真实验表明:LAVT算法在室内停车场环境中将车辆定位精度提升了19.03%。LAVT算法应用于室内停车场环境中的车辆定位具有更好的适用性,能满足室内停车场车辆定位的基本需求。
