Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains

This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.

A Hybrid Algorithm for Satellite Data Transmission Schedule Based on Genetic Algorithm

A hybrid scheduling algorithm based on genetic algorithm is proposed in this paper for reconnaissance satellite data transmission.At first,based on description of satellite data transmission request,satellite data transmission task model and satellite data transmission scheduling problem model are established.Secondly,the conflicts in scheduling are discussed.According to the meaning of possible conflict,the method to divide possible conflict task set is given.Thirdly,a hybrid algorithm which consists of genetic algorithm and heuristic information is presented.The heuristic information comes from two concepts,conflict degree and conflict number.Finally,an example shows the algorithm's feasibility and performance better than other traditional

High Performance Priority Packets Scheduling Mechanism for Big Data in Smart Cities

Today,Internet of Things(IoT)is a technology paradigm which convinces many researchers for the purpose of achieving high performance of packets delivery in IoT applications such as smart cities.Interconnecting various physical devices such as sensors or actuators with the Internet may causes different constraints on the network resources such as packets delivery ratio,energy efficiency,end-to-end delays etc.However,traditional scheduling methodologies in large-scale environments such as big data smart cities cannot meet the requirements for high performance network metrics.In big data smart cities applications which need fast packets transmission ratio such as sending priority packets to hospitals for an emergency case,an efficient schedulingmechanism ismandatory which is the main concern of this paper.In this paper,we overcome the shortcoming issues of the traditional scheduling algorithms that are utilized in big data smart cities emergency applications.Transmission information about the priority packets between the source nodes(i.e.,people with emergency cases)and the destination nodes(i.e.,hospitals)is performed before sending the packets in order to reserve transmission channels and prepare the sequence of transmission of theses priority packets between the two parties.In our proposed mechanism,Software Defined Networking(SDN)with centralized communication controller will be responsible for determining the scheduling and processing sequences for priority packets in big data smart cities environments.In this paper,we compare between our proposed Priority Packets Deadline First scheduling scheme(PPDF)with existing and traditional scheduling algorithms that can be used in urgent smart cities applications in order to illustrate the outstanding network performance parameters of our scheme such as the average waiting time,packets loss rates,priority packets end-to-end delay,and efficient energy consumption.

A data transmission scheduling algorithm for rapid-response earth-observing operations

With the development of rapid-response Earth-observing techniques, the demand for reducing a requirements-tasking-effects cycle from 1 day to hours grows rapidly. For instance, a satellite user always wants to receive requested data in near real-time to support their urgent mis- sions, such as dealing with wildfires, volcanoes, flooding events, etc. In this paper, we try to reduce data transmission time for achieving this goal. The new feature of a responsive satellite is that users can receive signals from it directly. Therefore, the traditional satellite control and operational tech- niques need to be improved to accommodate these changes in user needs and technical upgrading. With that in mind, a data transmission topological model is constructed. Based on this model, we can deal with the satellite data transmission problem as a multi-constraint and multi-objective path- scheduling problem. However, there are many optional data transmission paths for each target based on this model, and the shortest path is preferred. In addition, satellites represent scarce resources that must be carefully scheduled in order to satisfy as many consumer requests as possible. To efficiently balance response time and resource utilization, a K-shortest path genetic algorithm is proposed for solving the data transmission problem. Simulations and analysis show the feasibility and the adaptability of the proposed approach.

Approach for earth observation satellite real-time and playback data transmission scheduling

The scheduling of earth observation satellites(EOSs)data transmission is a complex combinatorial optimization problem. Current researches mainly deal with this problem on the assumption that the data transmission mode is fixed, either playback or real-time transmission. Considering the characteristic of the problem, a multi-satellite real-time and playback data transmission scheduling model is established and a novel algorithm based on quantum discrete particle swarm optimization(QDPSO)is proposed. Furthermore, we design the longest compatible transmission chain mutation operator to enhance the performance of the algorithm. Finally, some experiments are implemented to validate correctness and practicability of the proposed algorithm.

STK/Scheduler在卫星数传调度中的应用研究

卫星数传调度问题是一类复杂的组合优化问题,即如何为卫星数传任务分配地面资源的问题,它是当前航天领域需要重点研究的问题之一。STK/Scheduler模块是STK工具包中的调度模块,对外提供了二次开发功能。针对卫星数传调度问题,研究了STK/Scheduler模块在该问题中的应用。首先在分析问题的基础上建立了卫星数传任务模型和调度模型,然后对基于STK/Scheduler的卫星数传调度系统进行了设计。最后利用AFIT基准数据进行了验证,结果表明在卫星数传任务规模不太大的情况下,STK/Scheduler为卫星数传调度问题的求解提供了一条捷径。

A Fast Insertion Tabu Search with Conflict-Avoidance Heuristic for the Multisatellite Multimode Crosslink Scheduling Problem

An agile earth-observing satellite equipped with multimode cameras capable of transmitting observation data to other satellites is developed to rapidly respond to requests with multiple observation modes.This gives rise to the Multisatellite Multimode Crosslink Scheduling(MMCS)problem,which involves allocating observation requests to agile satellites,selecting appropriate timing and observation modes for the requests,and transmitting the data to the ground station via the satellite communication system.Herein,a mixed integer programming model is introduced to include all complex time and operation constraints.To solve the MMCS problem,a two-stage heuristic method,called Fast insertion Tabu Search with Conflict-avoidance(FTS-C)heuristic,is developed.In the first stage,a conflict-avoidance insertion algorithm is designed to generate a high-quality initial solution by considering the requests transmission and download.Further,the tabu search-based second stage optimizes the initial solution.Finally,an extensive empirical study based on a real-world situation demonstrates that FTS-C can generate a solution with higher quality in less time than other state-of-the-art algorithms and the CPLEX solver.

多通道遥感图像光纤高速传输系统

遥感相机一般使用TLK2711接口输出图像数据,地面测试设备不能直接对其采集存储。文中设计了一种多通道遥感图像高速光纤传输系统,可对相机输出的TLK2711图像数据进行采集与缓存,并通过光纤接口传输给存储设备。实现了遥感相机与地面存储设备之间的高速图像数据通信,解决了现有地检存储设备不能直接进行数据通信的问题。系统设计了多通道TLK2711图像采集模块,多路图像数据分时复用处理模块,基于Aurora64B/66B传输协议光纤传输模块等,使相机图像数据稳定可靠地传给地面存储。经过实验测试,系统图像数据采集准确,数据传输无误码。系统效率高,稳定可靠,满足实际使用需求。

An Efficient Priority-Driven Congestion Control Algorithm for Data Center Networks

With the emerging diverse applications in data centers,the demands on quality of service in data centers also become diverse,such as high throughput of elephant flows and low latency of deadline-sensitive flows.However,traditional TCPs are ill-suited to such situations and always result in the inefficiency(e.g.missing the flow deadline,inevitable throughput collapse)of data transfers.This further degrades the user-perceived quality of service(QoS)in data centers.To reduce the flow completion time of mice and deadline-sensitive flows along with promoting the throughput of elephant flows,an efficient and deadline-aware priority-driven congestion control(PCC)protocol,which grants mice and deadline-sensitive flows the highest priority,is proposed in this paper.Specifically,PCC computes the priority of different flows according to the size of transmitted data,the remaining data volume,and the flows’deadline.Then PCC adjusts the congestion window according to the flow priority and the degree of network congestion.Furthermore,switches in data centers control the input/output of packets based on the flow priority and the queue length.Different from existing TCPs,to speed up the data transfers of mice and deadline-sensitive flows,PCC provides an effective method to compute and encode the flow priority explicitly.According to the flow priority,switches can manage packets efficiently and ensure the data transfers of high priority flows through a weighted priority scheduling with minor modification.The experimental results prove that PCC can improve the data transfer performance of mice and deadline-sensitive flows while guaranting the throughput of elephant flows.

地面资源保障航天测运控任务质量评价指标体系构建

针对目前航天测运控任务完成质量评价主要集中在设备运行质量、资源调度能力评估等方面,缺乏从用户申请提交到执行效果反馈的全过程闭环评价问题,区分地面资源完成测控、数传两类任务质量情况,从设备跟踪任务质量情况、资源调度系统保障用户资源使用需求情况、用户对执行效果反馈及自身行为评价3个环节构建分类分层的评价指标体系。采用1-9标度法确立指标权重,研究对不同类型任务完成质量的综合评价,并利用实例验证所构建指标体系的可行性。为标准化、精细化评价地面资源保障航天测运控任务质量提供理论依据,并给出质量改进相关参考建议。

复杂光纤网络数据线性均衡调度方法设计

为了解决因数据传输量过大而造成的网络传输拥堵的问题,提高数据调度效率,提出一种复杂光纤网络数据线性均衡调度方法。构建复杂光纤网络信道框架模型,分析数据分布形态,研究网络中传输干扰项及影响数据传输失衡的主要原因,计算碰撞冲突的距离估计特征向量,调节碰撞光波传播方向,重构数据分布和光波信号传输位置,利用多路加载机制,提取数据信息流平均互信息特征,计算传输数据的波谱聚焦输出,通过对信号比特信息流实行自适应线性均衡控制调度。经过实验分析证明,所提方法对网络资源利用率高,调度耗能小,能够有效地平衡网络的负载,调度效率较高,数据传输时延较小,整体性能良好。

基于RDMA的高性能单向数据采集技术研究

高性能数据采集技术是提高数据分析效率的重要前提。为解决当前数据采集技术中安全性低、传输时延高、CPU开销大的问题,设计一种基于远程直接内存访问的高性能单向数据采集(ODAR)架构,提高数据采集过程中的安全性和传输性能。针对传输时数据正确性问题,基于可靠性的数据封装策略,设计动态内存优化策略解决内存分配时存在的时延问题,并提出基于优先级的数据传输调度算法解决高吞吐量数据传输中存在的带宽利用率低的问题。实验结果表明,相对于基于UDP协议实现的单向数据采集技术,ODAR架构的吞吐量平均提高了57.01%,传输时延与CPU开销平均降低了61.27%与68.01%,并且大幅提高了数据传输的准确率,内存分配时的时延平均降低了80.15%,网卡带宽利用率平均提高了33.03%。

基于网络切片的电力调度通信IP over E1方法研究

随着电力调度脉冲编码调制(PCM)设备的逐步退运,电网公司将逐步采用光传输设备替代调度PCM设备。在设备更换的过渡期,存在大量光传输设备与PCM设备混用的情况。为解决电力调度传输网络中存在的E1与互联网协议(IP)分组业务转换难度大、转换速率低的问题,提出了1种基于网络切片的IP over E1方法。首先,将要传输的数据打包成IP数据。然后,基于网络切片技术,将IP数据包切片后,封装成E1帧。在此基础上,通过E1链路进行数据传输,在接收端通过E1数据帧拆解完成IP数据包的重组发送。最后,将所提方法在某省电力公司进行实例运行,IP over E1转换准确率为99.86%。其结果验证了该方法的有效性。该方法可有效提高IP over E1转换速度和准确率。

基于“调度+反馈”策略的多队列数据流发送控制系统设计

针对多队列数据流发送控制实现时占用逻辑资源多和流量控制的粒度大、误差大等问题,利用现场可编程门阵列(FPGA)和Verilog HDL设计了一种基于“调度+反馈”的多队列数据流发送控制系统。将寄存器与存储器模块作为指令控制模块以满足多样化需求;使用状态机控制系统工作流程以保障各模块间的协同工作;利用调度控制缓冲区数据的发送状态,以完成多队列数据的控制与隔离;在流量计算与控制的过程中利用误差采集反馈来减少误差并降低控制粒度,并在FPGA设计上利用分时复用来节省逻辑资源。对所设计的Verilog HDL程序进行EDA仿真和基于自主搭建平台的FPGA系统试验,结果证实了多队列数据流发送控制系统的有效性和先进性。

Data Transmission with the Battery Utilization Maximization

With the growing popularity of 3G-powered devices, there are growing demands on energy-efficient data trans- mission strategies for various embedded systems. Different from the past work in energy-efficient real-time task scheduling, we explore strategies to maximize the amount of data transmitted by a 3G module under a given battery capacity. In particular, we present algorithms under different workload configurations with and without timing constraint considerations. Experiments were then conducted to verify the validity of the strategies and develop insights in energy-efficient data transmission.

工业互联网在火力发电厂中的应用

阐述火力发电厂的数据传输特点,实时监控和优化调度,包括前端框架Vue和LayUI组件库,可以快速高效的搭建页面优美而且效果炫酷的后端页面和特效,后端SpringBoot框架,可以高效构建JavaEE项目,数据库采用MySQL,支持分片、分库、分表,有利于以后的程序的扩展。

云环境下数据密集型工作流调度

相比于传统的计算密集型工作流,云环境下数据密集型工作流中数据传输量大,任务数量多,任务之间依赖关系复杂。为此,文章提出了一种基于最大数据传输路径的数据密集型工作流调度方法,首先对工作流进行分层,找出工作流中最大数据传输量路径,并开展对最大数据传输量路径的分配工作,然后对其余任务分配服务商,以此缩短工作流的完成时间,最后通过具体实验验证了该方法的可行性和有效性。

一种基于信号比对机制的新型变电站信号核对系统

针对现有变电站信号核对效率低下,耗时长的问题,开发一种基于信号比对机制的新型变电站信号核对系统,它能快速核对主站收到的信号和厂站收到的信号,创新使用调度数据网双向传输信息,减少移动装置带来的网络安全风险。利用变电站内现有专用调度数据网从主站安全获取厂站传输的三遥数据,通过调度数据网进行双向传输,建立信号比对机制,从而实现变电站信号自动闭环核对。在信号验收过程中,无需监控人员配合,现场工作人员利用后台即可实现信号的闭环核对。现场测试和应用表明,利用调度数据网双向传输和信号比对机制进行信号验收,现场作业人员可从五人减少到三人,单个信号的平均核对时间缩短2/3,工作效率明显地提高。

城市污水主干排水系统优化调度分析——以华东某市污水主干管为研究案例

排水系统智能化调度是实现污水系统安全平稳运行的重要举措,尤其针对一些工程措施无法或尚未实施的区域。通过对污水主干管实现智能化调度的关键因素分析,并以华东某市污水主干管为研究案例,结合排水模型和大数据挖掘优化污水主干管系统运行,将末端污水厂旱天溢流天数降低了15%,从而优化污水干线系统运行工况。

多星联合任务规划方法

针对多星对地观测系统联合任务规划问题,考虑卫星载荷具备连续侧摆能力和多种数据压缩模式的新特点,构建了多星联合任务规划模型,在此基础上设计多星联合任务规划和数传调度算法框架,实现了卫星连续侧摆成像规划算法和基于任务优先级的数传任务调度算法,最后采用实际算例进行试验,结果表明文章提出的多星联合任务规划方法能在提高完成任务数量的同时降低卫星资源消耗,满足实际应用需求。