一种面向随机计算卸载的两层无人机能耗优化方法

当物联网设备(Internet of Things Device,IoTD)面临随机到达且复杂度高的计算任务时,因自身计算资源和能力所限,无法进行实时高效的处理。为了应对此类问题,设计了一种两层无人机辅助的移动边缘计算(Mobile Edge Computing,MEC)模型。在该模型中,考虑到IoTD处理随机计算任务时的局限性,引入多架配备MEC服务器的下层无人机和单架上层无人机进行协同处理。为了实现系统能耗最优化,提出了一种资源优化和多无人机位置部署方案,根据计算任务到达的随机性,应用李雅普诺夫优化方法将能耗最小化问题转化为一个确定性问题,应用差分进化(Differential Evolution,DE)算法进行多次变异、交叉和选择取得无人机的优化部署方案;采用深度确定性策略梯度(Depth Deterministic policy Gradient,DDPG)算法对带宽分配、计算资源分配、传输功率分配和任务卸载分配进行联合优化。实验结果表明,该算法相较于对比算法系统能耗降低35%,充分验证了其可行性和有效性。     

软件定义无人机自组网快速一致性更新机制

为了解决软件定义无人机自组网(Software-defined Unmanned Aerial Vehicle Ad Hoc Network, SDUANET)中转发黑洞和更新轮次问题,提出了一种软件定义无人机自组网快速一致性更新机制(Software-defined Unmanned Aerial Vehicle Ad Hoc Network Fast Consistent Update Mechanism, SDUANET-FCU)。新机制首先对节点进行分类操作,对可能会导致转发黑洞的发送操作进行约束;其次,针对含有两个规则的节点提出一种基于混合规则的两轮一致性更新策略;最后,将计算得出的Flow-mod发送顺序整合到两轮更新顺序中。仿真结果表明,在软件定义无人机自组网场景下,相比于现有的软件定义网络(Software Defined Network, SDN)更新方法,SDUANET-FCU降低了转发黑洞的概率和控制消息的数量,减少了平均更新轮次。     

一种软件定义的信息中心网络架构北大核心

现有SDICN(软件定义信息中心网络)技术方案难以支持海量内容分发、交换和缓存组件的分别升级。文章提出一种基于覆盖网络的SDICN系统架构,由网络边缘的缓存节点转发内容请求和缓存内容数据,缓存与交换不再耦合,克服了现有技术方案的上述局限;基于SDN(软件定义网络)的集中式控制,避免了覆盖网络系统的次优控制问题。原型系统实验分析表明,所提系统可直接运行于通常的SDN中,少量的边缘节点即可有效减少内容分发响应时间。研究结果有利于SDN和ICN(信息中心网络)技术的扩展及应用。     

车联网中一种基于软件定义网络与移动边缘计算的卸载策略

在新兴的车联网络中,汽车终端请求卸载的任务对网络带宽、卸载时延等有着更加严苛的需求,而新型通信网络研究中移动边缘计算(MEC)的提出更好地解决了这一挑战。该文着重解决的是汽车终端进行任务卸载时卸载对象的匹配问题。文中引入了软件定义车载网络(SDN-V)对全局变量统一调度,实现了资源控制管理、设备信息采集以及任务信息分析。基于用户任务的差异化性质,定义了重要度的模型,在此基础上,通过设计任务卸载优先级机制算法,实现任务优先级划分。针对多目标优化模型,采用乘子法对非凸优化模型进行求解。仿真结果表明,与其他卸载策略相比,该文所提卸载机制对时延和能耗优化效果明显,能够最大程度地保证用户的效益。

     

基于软件定义网络架构的多接入边缘计算+工业互联网策略研究

工业互联网是一种新的产业和应用形态,往往存在海量相互连接交互的设备,且对计算资源和时延有极高的要求.引入多接入边缘计算和软件定义网络架构,提出了一种基于SDN的工业互联网多接入边缘计算(SDN-IIOT-MEC)集成架构,将计算任务下沉到边缘云服务器,在计算、管控、编排等方面的能力上有了很大提升,并设计了该集成架构下的...     

软件定义网络架构研究与实践

通过分析SDN的研究背景,阐述了SDN由应用层、控制层、基础设施层组成的3平面架构；基于OpenFlow的实现方案和以Juniper、思科等公司解决方案为代表的其他实现方案,对SDN架构的实现进行了探讨；从科研和商业化的角度出发,展示了最新的基于SDN架构的实践与应用.     

超密集网络中基于MEC的动态任务卸载方案

超密集网络(Ultra-dense Network,UDN)中集成移动边缘计算(Mobile Edge Computing,MEC),是5G中为用户提供计算资源的可靠方式,在多种因素影响下进行MEC任务卸载决策一直都是一个研究热点。目前已存在大量任务卸载相关的方案,但是这些方案中很少将重心放在用户在不同条件下的能耗需求差异上,无法有效提升用户体验质量(Quality of Experience,QoE)。在动态MEC系统中提出了一个考虑用户能耗需求的多用户任务卸载问题,通过最大化满意度的方式提升用户QoE,并将现有的深度强化学习算法进行了改进,使其更加适合求解所提优化问题。仿真结果表明,所提算法较现有算法在算法收敛性以及稳定性上具有一定提升。     

软件定义网络技术及发展趋势综述

软件定义网络是继云计算、移动互联网、大数据之后,信息通信领域又一热议的对象,被称作下一次网络革命,对下一代互联网发展有着重要的影响。首先介绍了软件定义网络的发展背景、原理、架构与内涵,然后阐述了SDN的关键技术,最后分析了SDN的优缺点及应用领域。     

软件定义无人机自组网高效自适应路由维护机制

为解决软件定义无人机自组网路由维护存在的控制开销和数据包延迟偏大的问题,基于现有的OpenFlow协议提出了一种高效自适应的软件定义无人机自组网路由维护机制( Efficient and Adaptive Software-defined Unmanned Aerial Vehicle Ad Hoc Network R...     

面向SDN的数据中心网络更新研究综述

近年来,由于软件定义网络(SDN)的控制平面与数据平面分离、集中式控制的特点,被广泛应用于数据中心网络(DCN).分四个部分对DCN更新的相关研究进行了综述.首先,介绍了DCN和SDN的基本概念及研究现状;随后,详细说明了传统DCN在更新方面遇到的缺陷;其次,重点讨论了基于SDN的数据中心网络(SD-DCN)更新场景的研究现状与存在的不足,同时指出了一些方案存在的缺点;最后,对基于SDN的数据中心网络未来研究方向进行了展望,以期为SD-DCN的研究与应用提供一定的参考.     

V2X offloading and resource allocation under SDN and MEC architecture

To address the serious problem of delay and energy consumption increase and service quality degradation caused by complex network status and huge amounts of computing data in the scenario of vehicle-to-everything (V2X),a vehicular network architecture combining mobile edge computing (MEC) and software defined network (SDN) was constructed.MEC sinks cloud serviced to the edge of the wireless network to compensate for the delay fluctuation caused by remote cloud computing.The SDN controller could sense network information from a global perspective,flexibly schedule resources,and control offload traffic.To further reduce the system overhead,a joint task offloading and resource allocation scheme was proposed.By modeling the MEC-based V2X offloading and resource allocation,the optimal offloading decision,communication and computing resource allocation scheme were derived.Considering the NP-hard attribute of the problem,Agglomerative Clustering was used to select the initial offloading node,and Q-learning was used for resource allocation.The offloading decision was modeled as an exact potential game,and the existence of Nash equilibrium was proved by the potential function structure.The simulation results show that,as compared to other mechanisms,the proposed mechanism can effectively reduce the system overhead.     

基于SDN和MEC的5G VANET架构及其性能分析

为了在大规模的车载自组织网络（Vehicular Ad-hoc Network,VANET）中提供灵活的网络管理、控制和提高资源利用率,结合软件定义网络（Software Defined Network,SDN）、云无线接入网络（Cloud Radio Access Network,C-RAN）和移动边缘计算（Mobile Edge Computing,MEC）,提出了一种分层的5G VANET架构（5G MEC VANET）,能够支持智能交通系统各种功能和应用的动态特性,同时降低网络管理成本。此外,位于网络边缘的MEC框架避免了车辆与路边基站的频繁交互,减少了数据传播延时。仿真结果表明,与传统VANET和5G VANET架构相比,所提出的架构降低了传播时延,提高了网络带宽吞吐量,同时减少了控制器开销。     

Local replacement for route recovery on a collaborative mobile ad hoc network

This paper presents an efficient route recovery approach for a collaborative mobile ad hoc network (MANET). In the collaborative MANET, the movement of a node can be controlled by other nodes. Based on the property of the controllable movement, each active node (each node on a route) can be protected by its neighboring nodes. When the movement of an active node causes a link breakage on a route, its neighboring nodes compete with each other to move to the original location of the moving active node. Using the movements of neighboring nodes, the proposed approach can achieve route recovery without pre‐establishing or dynamically finding backup routes. The proposed approach also has much less recovery overhead than previous approaches because of the local recovery. Finally, we perform extensive simulations to compare the proposed approach with previous approaches. The simulation results show that the proposed approach has better recovery performance under dense and sparse MANET architectures. Copyright © 2010 John Wiley & Sons, Ltd.     

移动自组织网络可用带宽估计方法研究进展

首先分析了有线网络和无线网络带宽估计机制的区别,然后,在此基础卜给出了MANET可用带宽定义,并且从原理上分析了数据帧碰撞概率、回退时间以及信道空闲比例等对MANET中的可用带宽造成影响的因素,同时对各种参数的测量以及估计方法进行了详细介绍,最后展望了带宽估计的应用前景和研究趋势.     

移动自组网在灾后营救中的应用研究

介绍移动自组网的特点、发展与现状,并与现有通信手段进行分析对比,指明移动自组网在各类灾后营救中的相比传统通信手段所更能发挥的积极作用,展望移动自组网在各个领域中的应用前景。     

Mobility Management UAV-based Grouping routing protocol in flying ad hoc networks for biomedical applications

Wireless body area networks play a vital role in the medical field by saving human lives. It senses the human body condition and transmits it to the respective doctors. The faster the communication, the sensed data can be transmitted faster and the patients in emergency can be treated on time. Therefore, to increase the speed of communication, Unmanned Aerial Vehicles (UAV) are used in biomedical applications. In this flying ad hoc network, there is a possibility of link failure due to the high mobility of UAV. To overcome this issue, a new routing protocol, Mobility Management UAV-based Grouping (MMUG), for biomedical data transmission from one ground station to another via UAV is suggested in this research. The UAV creates the grouping system based on the coverage range of the group head. Group head selects the node that lies closer to the ground station. Group head continuously monitors the mobility of the unmanned aerial vehicles that lie in the coverage range and thus helps to maintain the link stability. The mobility issue will be overcome by using this proposed scheme, and it manages the mobility. The mobility management helps to increase the network performance by increasing the delivery rate and throughput and reducing the drop rate and overhead. Simulation results show that this routing protocol achieves 86% delivery rate and 1.95 Mbps throughput and reduces the drop rate by 14%, control overhead by 23%, and routing overhead by 20%. Moreover, this model achieves higher network performance compared to the existing techniques.     

基于博弈理论的移动自组网激励机制研究

摘 要：针对移动自组网中节点在报文转发过程中的表现出的自私行为,利用博弈理论,从静态和动态2个方面对其进行了完整的建模与分析。首先,提出了一种严厉针锋相对策略,并建立了一个无限重复报文转发博弈模型,求得了激励一致性条件。然后,利用演化博弈理论对节点由自私向协作转变的动态过程进行了分析,并证明了严厉针锋相对策略的演化稳定性。仿真结果表明,即使在自私节点比率为1的条件下,只要合理选择惩罚参数,均可有效激励自私节点的协作转发行为,整体网络性能最多可提升80%。     

Network mobility protocol for vehicular ad hoc networks

The goal of the network mobility management is to effectively reduce the complexity of handoff procedure and keep mobile devices connecting to the Internet. When users are going to leave an old subnet and enter a new subnet, the handoff procedure is executed on the mobile device, and it may break off the real‐time service, such as VoIP or mobile TV, because of the mobility of mobile devices. Because a vehicle is moving so fast, it may cause the handoff and packet loss problems. Both of the problems will lower down the throughput of the network. To overcome these problems, we propose a novel network mobility protocol for vehicular ad hoc networks. In a highway, because every car is moving in a fixed direction at a high speed, a car adopting our protocol can acquire an IP address from the vehicular ad hoc network through the vehicle‐to‐vehicle communications. The vehicle can rely on the assistance of a front vehicle to execute the prehandoff procedure, or it may acquire a new IP address through multihop relays from the car on the lanes of the same or opposite direction and thus may reduce the handoff delay and maintain the connectivity to the Internet. Simulation results have shown that the proposed scheme is able to reduce both the handoff delay and packet loss rate. Copyright © 2013 John Wiley & Sons, Ltd.     

Misbehavior analysis of IEEE 802.11 MAC layer in mobile ad hoc network using stochastic reward nets

In this paper, we present a Petri net model for performance evaluation of IEEE 802.11 distributed coordination function as a popular media access control layer protocol in mobile ad hoc network. The goal of this evaluation is to examine this protocol under the existing of misbehavior nodes that selfishly try to grasp common channel in a neighbor area. The presented model consists of 2 separate models based on stochastic reward net (SRN), as a variation of stochastic Petri net. The first model, which is called one node operation model , is supposed for presenting all distributed coordination function operations in a single node such as collision avoidance, request to send/clear to send (RTS/CTS) handshake, and backoff mechanism. The next SRN model, all node operation model , is used for modeling nodes competition for occupying channel in a neighbor area. The models could be adjusted to a dynamic network with any number of nodes, dimension scale, and nodes' speed. For evaluation purpose, 4 distinct attack types implemented by modifying associated transitions in SRN models. The proposed SRN model has been quantified by deriving 2 performances metrics as Throughput and Delay . Both metrics are also compared to the value obtained from NS‐2 in terms of different number of nodes and 3 packet generation rates. Three additional metrics measuring the channel usage are also quantified in terms of different attack strategies using only presented SRN model.