面向ICN切片的视频缓存与传输服务

随着视频流量爆炸式地增长,为了降低密集区域用户的视频检索时延和网络负载,利用网络功能虚拟化技术提出了一种将5G切片与信息中心网络(Information Center Network,ICN)相结合的内容分发服务系统集成的架构,并改进基于ICN的缓存策略.该缓存策略依据特定区域用户一个月与一周内的历史访问记录构建视频主...     

基于非合作博弈的联合功率与速率控制算法

在多媒体CDMA网络中,需要对用户的功率进行控制,既保证每个用户的QoS要求,又不增加对其它用户的干扰,同时还要对用户的数据速率进行控制,以避免拥塞。将功率和速率控制等效为一个具有N个用户的非合作博弈,用效用函数表征用户对系统服务质量的满意程度,用代价函数描述达到通信要求所消耗的无线资源,从而将联合功率与速率控制算法描述为最大化净效用函数（效用函数和代价函数之差）的过程,最终得到系统中各用户全局最佳数据传输速率和达到服务质量所需的最小发射功率组合,并证明了纳什均衡的存在性。     

基于节点社团重要度的ICN缓存策略

全网内置缓存是ICN(信息中心网络)架构中最重要的特性之一。为使被缓存的内容对象在空间和时间上分布更合理,提出了一种基于节点社团重要度的缓存策略（CSNIC）。该策略以社团为单位,不仅把内容缓存到社团内用户容易获取的节点处,而且使不同流行度的内容对象在各社团内节点处的时间分布上更合理。在多种实验条件下对CSNIC策略进行了仿真验证,结果表明该策略与CEE-LRU、Betw-LFU、Opportunistic相比,能更好地提升包括缓存命中率、跳数减少率、内容差异性及替换数量等在内的网络缓存性能指标,而且,CSNIC策略的额外开销较小。     

基于ICN的未来媒体网络缓存放置策略

随着媒体用户规模的增大和数字媒体内容指数式的增长,现有的互联网、广播网和电信网已无法同时满足如此庞大数据量的高效传输和用户随时随地低成本消费的需求,这严重影响了网络性能和服务质量,并在一定程度上推动了对以信息中心网络(ICN)为代表的未来网络体系架构的研究。在信息中心网络中,缓存放置策略的优劣在一定程度上决定了网络性能的优劣。文章结合奇异值分解算法(SVD)提出基于ICN的未来媒体网络缓存放置策略,通过分析不同网络中请求内容的相似性决定每个网络的缓存内容;一方面,利用ICN数据与位置分离的思想,降低链路负载,另一方面,通过SVD算法提高ICN中的数据响应速率和网络缓存命中率,减小了网络传输开销和数据的传输时延,对于提升媒体网络性能和用户体验具有重要意义。     

基于概率的启发式ICN缓存内容放置方法

提出一种基于概率存储的启发式住处中心网络内容缓存方法（PCP）。主要思想是请求消息和数据消息在传输过程中统计必要信息,当数据消息返回时,沿途各缓存节点按照一定概率决策是否在本地缓存该内容。设计缓存概率时综合考虑内容热度和缓存放置收益,即内容热度越高,放置收益越大的内容被缓存的概率越高。实验结果表明,PCP在缓存服务率、缓存命中率、平均访问延迟率等方面,与现有方法相比具有显著优势,同时PCP开销较小。     

面向ICN的动态自适应流媒体算法

信息中心网络(information-centric networking,ICN)与传统IP网络的重要区别在于,前者的路由器节点具备缓存能力,能将热门内容推送到更靠近客户的网络边缘,从而降低客户获取内容的时延。然而ICN中的节点缓存特性会导致传统的自适应流媒体协议出现视频抖动甚至播放中断,降低客户的观看体验。提出了ICN中的动态自适应流媒体算法,在保证客户端播放流畅的同时,尽可能地提升视频片段的码率,提升客户的观看体验。通过在现有的ICN平台中进行仿真实验,证明了该自适应算法在性能上优于传统的算法。     

多主多从Stackelberg博弈下的边缘缓存资源分配算法

为鼓励视频服务提供商参与到缓存过程中,本文提出一种基于Stackelberg博弈的激励缓存资源分配算法。与传统激励缓存资源分配方案不同,本文考虑同时存在多个网络运营商和多个视频服务提供商,视频服务提供商从网络运营商处购买存储空间以缓存热门视频。针对该场景,本文将该激励缓存模型建模为多主多从Stackelberg博弈问题,分别构建主方和从方的效用函数,证明了在网络运营商价格确定的情况下,视频服务提供商之间的非合作博弈存在纳什均衡。文章利用分布式迭代算法对该博弈模型进行求解,获得了视频服务提供商的最优缓存策略和网络运营商的最优价格策略。仿真结果表明,本文提出的激励缓存机制可使视频服务提供商获得比其他缓存分配算法更高的单位成本收益。      

面向5G-ICN切片的分层缓存策略

多接入边缘计算(Multiple Access Edge Computing,MEC)和网络切片在5G网络中扮演了重要角色。网络切片的灵活可编程性和MEC的去中心化促进了信息中心网络(Information Centric Network,ICN)的部署。但是,ICN中缓存资源分配的位置和数量严重影响了运营商的收益。为此,首先将移动虚拟网络运营商(Mobile Virtual Network Operator,MVNO)和多个内容提供商(Content Provider,CP)建模为一主多从的Stackelberg博弈;其次,将MVNO内部的缓存资源分配建模为一个联合缓存成本和传输能耗的混合整数规划问题,并利用改进的精英遗传算法得到最佳位置;最后,通过博弈迭代算法得到运营商的最优定价和CP的最优放置数量。仿真结果表明,该算法具有较高的有效性以及较好的缓存资源分配能力,能够降低传输能耗和缓存成本,与贪婪搜索(Iteration Greedy Search,IGS)算法、联合缓存分配和延时控制(Joint Cache Allocation and Delay Control,JCADC)算法相比传输能耗分别节省了5%、11%,运营商的收益分别提高了32%、44%。     

基于混合高斯模型的移动ICN缓存机制研究

针对移动互联网环境下信息中心网络的缓存放置问题,提出一种基于混合高斯模型的缓存优化机制(Gaussian Mixture Cache,GMC)。该策略通过网内的核心感知节点,周期性请求其余路由节点信息,依据混合高斯模型生成节点边缘度,最后将节点边缘度分发至路由节点。基于边缘优先的原则,路由节点考查数据内容的流行度和自身的边缘度得到细粒度的缓存概率,以实现节点移动条件下的高效缓存。仿真结果表明,GMC机制能够在移动ICN环境下有效发挥缓存的作用,降低了平均路由跳数,减少了数据请求时延,提高了缓存命中率。     

面向分域信息中心网络的协作混合缓存和路由策略

网内缓存技术一直是信息中心网络(Information-Centric Networking, ICN)研究中的核心问题。传统缓存方案通常为网络内的单一全局协作策略,然而不同网络区域的缓存目标不同,导致传统方案的性能优化程度有限,可扩展性不强。同时协同缓存放置和请求路由,相较于纯缓存方案有效性更高。该文提出并评估了一种新型面向分域的协作混合缓存放置和路由请求机制,该机制将缓存网络区分核心网络和边缘网络,在核心网络中采用非沿路的HASH协作机制,边缘网络采用沿路的回退协作机制,创建二元组标签保存缓存放置的信息并作用于后续的请求转发。通过仿真对比表明,该文提出的协作混合缓存机制相较于传统策略可以更好地平衡网络资源利用和用户体验,并在大型ISPs中拓展性更好。     

A game theoretical distributed approach for opportunistic caching strategy

Wireless Networks - Wireless network virtualization (WNV) has been a hot topic recently, which can provide the customized service to construct virtual networks for various requirements quickly and...     

Non-cooperative power control game for adaptive modulation and coding

Adaptive modulation and coding (AMC) provides the flexibility to match modulation and coding scheme (MCS) to signal to interference plus noise ratio (SINR) of users. To reduce the transmission power and maintain the transmission quality, power control is normally combined with AMC. While the target SINR of power control is fixed, therefore non-cooperative power control game for AMC (NPGA) algorithm was proposed to adapt to the dynamic target SINR changes according to MCS. In NPGA, we formulate system transmission efficiency via utility, where the utility function is constructed based on the modulation and coding efficiency with non-cooperative game theory. It is demonstrated theoretically that NPGA can satisfy the conditions of the supermodular games, and its solution is optimal. The simulation results show that NPGA can improve system transmission efficiency and signal quality with low transmission power, and the convergence performance of NPGA is more fast-effectiveness compared with geometric programming algorithms.     

无人机蜂群网络非合作博弈的功率控制

无人机蜂群网络是一种由大量节点组成的分层、多簇结构的无线通信网络。重点研究了多信道条件下功率优化控制问题及措施，提出了一种基于非合作博弈的分布式功率控制方法。该博弈问题的价格因子设计考虑了网络节点重要度因子的影响，每个节点根据连接关系评估得到全网节点的重要度因子。给出了分布式价格功率控制算法。对所提出的算法进行典型场景下的仿真分析，结果表明该算法能够快速收敛，保证簇首、核心节点等高重要度节点的干扰容限，提高网络的可靠性，达到系统总体效用最优。     

基于移动场景下的边缘缓存策略综述

随着移动流量需求的爆炸式增长,传统的流量缓存策略已经满足不了现代通信网络的要求,文章提出一种边缘缓存策略,该策略力图通过在网络边缘进行缓存的方法,来降低核心网络的压力。本策略建立了移动边缘计算网络模型,文章采用协同缓存策略,以最小化中传输开销为目标建立最优化模型,以获得在MEC架构中的内容缓存部署方案。     

Cooperative caching game based on social trust for D2D communication networks

Content sharing via device‐to‐device (D2D) communications has become a promising method to increase system throughput and reduce traffic load. Due to the characteristic of spectrum sharing in D2D network, confidentiality is becoming a key issue in content transmission. Secure communication in D2D networks is generally guaranteed by a physical‐layer security mechanism. However, this method sacrifices the system transmission rate while ensuring security. Since mobile devices are carried by humans, we can leverage their trust relations to enhance the security of communications. As much, considering the psychology structure and social attributes of mobile users, we build a multidimensional trust evaluation mechanism to evaluate the trust relationship between users, and we pick out the trusted users based on the decision‐theoretic rough sets. By sharing content only between trust users, we can enhance the security of content transmissions without relying on physical‐layer security measures. Meanwhile, content caching is now widely used to improve accessing efficiency and reduce traffic load on cellular networks. However, caching content for other users incurs additional cost, which results in selfish and noncooperative behavior in users. Considering such selfishness, we introduce a cooperative caching game based on multidimensional trust relations to motivate users to cache contents for other devices. In this game, the trust relations and physical distance between two users are considered to formulate the cost function. Furthermore, we introduce an incentive caching algorithm based on social trust to minimize the total cost in the D2D network.     

Content forwarding strategy based on ICN architecture in VANET

Combining VANET with ICN,a routing building and selecting strategy-SRBS based on vehicular dynamic parameters was proposed.After locating the content nodes through content discovery process,several unicast forwarding paths would be built,which reduces useless traffic compared with a flooding way.By introducing dynamic metrics and LET to routing building and selecting process,SRBS improved the link stability and reliability,which ensured the Data’s successful return.Simulation results show the scheme also improves the time tolerance of routings and makes full use of network cache and reduces delay and routing hops.     

Edge-first-based cooperative caching strategy in information centric networking

In order to optimize the replica placement in information centric networking,an edge-first-based cooperative caching strategy (ECCS) was proposed.According to the strategy,cache decision was made during the interest forwarding stage.The decision result and statistic information would been forwarded to upstream routers step by step.Utilizing the information,upstream nodes could update their cache information table immediately to achieve cooperative caching.The experimental results indicate ECCS can achieve salient performance gain in terms of server load reduction ratio,average hop reduction ratio,average cache hit ratio,compared with current strategies.