信息中心网络中基于节点缓存命中贡献率的缓存替换方案

信息中心网络(CCN)是一种全新的网络架构,其显著的特点是处处缓存,合理的内容缓存部署能够显著提高网络传输效率.缓存替换策略是缓存管理中的重要组成部分,合理地进行缓存内容的替换,成为影响网络整体性能的关键.考虑到内容自身的特性,设计了一种基于节点缓存命中贡献率的贪婪双倍命中(GDH)缓存替换方案.该方案综合考虑了内容的请求次数、传输代价、缓存代价,设计全新的多目标价值函数,用于评估内容的缓存价值,当缓存空间不足时,替换掉价值最小的内容,实现节点缓存内容价值的最大化.仿真结果表明,该替换算法提高了节点的命中率,降低了获取内容的平均跳数.     

基于内容预期价值的内容中心网络缓存替换策略

缓存替换技术是内容中心网络的研究内容之一。相对于海量的内容数据,缓存空间总是有限的,良好的缓存替换策略可以提高缓存收益。考虑到内容在将来被请求的概率越大,预期访问时间距离当前时刻越近,其留存价值就越大,提出了一种基于内容预期价值的替换策略。该方案通过考虑内容流行度和预期访问时间到当前时刻的时间距离,构建内容预期价值函数,并据此将价值最小的内容替换出去。仿真实验证明,该策略相对于传统的缓存替换策略,可以有效提高缓存命中率、降低请求跳数,提高网络性能。     

一种基于内容流行度的内容中心网络缓存概率置换策略

内容中心网络是下一代互联网架构的研究热点,该架构通过分布式内容缓存机制实现以内容为核心的数据传输,改变了传统基于主机的网络通信模式.缓存置换策略是内容中心网络的核心研究问题之一,缓存置换策略的设计优劣直接制约内容中心网络的数据传输性能.该文针对内容的流行度分布特征,提出一种基于流行度的缓存概率置换策略,并针对 L 层级联的内容中心网络(CCN),推导了该策略下的网络分层缓存请求失败概率近似计算公式.该文策略根据请求数据块的流行度而选择数据块在缓存队列中的置换位置,尽可能平衡不同流行度内容在网络中的分布.数值计算结果表明:该策略适用于内容请求集中的网络应用,相比较传统的最近最少使用(LRU)策略,该文策略可以明显改善流行度较低的网络访问性能.     

一种基于SDN的CCN集中控制缓存决策方法

在软件定义网络(SDN)和内容中心网络(CCN)融合架构下,为了充分利用控制层对网络拓扑和缓存资源的全局感知,在全网中实现缓存资源的优化使用,提出了一种集中控制的缓存决策优化方案.在该方案中,应用粒子群优化算法(PSO)并且根据节点边缘度、节点重要度以及内容流行度对缓存资源和内容进行集中缓存决策,使得内容在不同的节点进行合理的缓存.仿真结果表明,通过评估缓存大小对缓存性能的影响,PSO缓存决策方法取得了比LCE、PROB缓存决策策略更优的缓存命中率和路径延展率,明显降低了缓存节点的缓存替换数,使得缓存达到了整体缓存优化.     

内容中心网络中能耗优化的隐式协作缓存机制

综合考虑内容中心网络(CCN)的能耗优化及性能提升,该文提出一种内容中心网络中能耗优化的隐式协作缓存机制。缓存决策时,利用缓存节能量作为判决条件优先在用户远端节点缓存,并利用数据包携带最近上游缓存跳数信息进行隐式协作,减轻用户近端节点缓存空间的竞争压力,提高邻近节点缓存的差异性。缓存替换时,选取缓存节能量最小的缓存内容加以替换,达到最优的能耗优化效果。仿真结果表明,该缓存机制在性能上获得较优的缓存命中率及平均路由跳数,同时有效降低了网络能耗。     

基于P2P的CDN新型网络及缓存替换算法

对内容分发网络和P2P网络的特点进行了分析,给出了一种基于P2P的CDN新型网络自治缓存系统的体系结构,提出了自治缓存区域中智能缓存替换问题并给出了智能缓存替换方法和双关键字缓存替换算法.通过仿真实验,可以找到以运算复杂度低命中率高的关键字来实现缓存替换.     

内容中心网络中基于内容迁移的协作缓存机制

内容中心网络(CCN)是为了适应未来网络通信模式的转变,提供对可扩展和高效内容获取的原生支持而提出一种新型的网络体系架构,内容缓存机制是其研究的关键问题之一。现有机制在缓存节点的选择时往往过于集中,缓存负载分布严重不均,大大降低了网络资源利用率以及系统的缓存性能。该文提出一种基于缓存迁移的协作缓存机制,首先在缓存节点选择时考虑节点的中心性保证内容尽可能缓存在位置更重要的节点。同时,在缓存压力过大时,通过可用缓存空间大小、缓存替换率以及网络连接的稳定性等信息选择合适的邻居节点进行缓存内容的转移,充分利用邻居资源实现负载分担。仿真结果表明该机制能有效地改善缓存负载在节点上分布的均衡性,提高缓存命中率和缓存资源利用率并降低平均接入代价。     

基于内容流行度和节点中心度匹配的信息中心网络缓存策略

在信息中心网络(Information-Centric Network, ICN)中,利用网络内置缓存提高内容获取及传输效率是该网络构架最重要的特性。然而,网络内置的缓存存在应对大量的需要转发的内容时能力相对弱小,对内容放置缺乏均衡分布的问题。该文提出基于内容流行度和节点中心度匹配的缓存策略(Popularity and Centrality Based Caching Scheme, PCBCS),通过对经过的内容进行选择性缓存来提高内容分发沿路节点的缓存空间使用效率,减少缓存冗余。仿真结果表明,该文提出的算法和全局沿路缓存决策方案,LCD(Leave Copy Down)以及参数为0.7及0.3的Prob(copy with Probability)相比较,在服务器命中率上平均减少30%,在命中缓存内容所需的跳数上平均减少20%,最重要的是,和全局沿路缓存决策方案相比总体缓存替换数量平均减少了40%。     

NDN中基于蚁群替换算法的邻居协作缓存管理策略

为提高NDN(命名数据网络)中的缓存利用率,提出了一种基于蚁群替换算法的邻居协作缓存管理(ACNCM)策略。首先将单节点的缓存替换问题,建模为0/1背包问题,并根据缓存数据的大小、使用频率以及邻居副本深度等信息定义本地存储内容的缓存价值,提出基于蚁群算法的缓存替换算法。然后利用邻域协作的思想,通过路由节点之间定期交换自身节点的缓存信息,对单个节点替换出去的缓存内容,选择邻居节点完成协作式缓存管理。实验结果表明,ACNCM策略在缓存命中率、网络开销和平均响应时延方面均优于现有方法。     

带有特征感知的D2D内容缓存策略

设备到设备通信(D2D)可以有效地卸载基站流量,在D2D网络中不仅需要共享大众化内容还需要个性化内容缓存。该文对缓存内容选择问题进行了深入研究,提出一种结合特征感知的内容社交价值预测(CSVP)方法。价值预测不仅可以降低时延也可以减少缓存替换次数降低缓存成本。首先结合用户特征和内容特征计算内容当前价值,然后通过用户社交关系计算未来价值。微基站根据内容的价值为用户提供个性化内容缓存服务,宏基站则在每个微基站的缓存内容中选择价值较大部分的内容。仿真结果表明,该文提出的缓存策略可以有效缓解基站流量,与其他方法相比降低时延约20%～40%。     

Fast convergence caching replacement algorithm based on dynamic classification for content-centric networks

One of the key research fields of content-centric networking （CCN） is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used （LRU） and recent usage frequency （RUF） in cache hit rate and resiliency when content popularity in the network varies.     

Coordinated caching scheme based on popular content awareness and tracking

To overcome the problems of the on-path caching schemes in the content centric networking,a coordinated caching scheme based on the node with the max betweenness value and edge node was designed.According to the topol-ogy characteristics,the popular content was identified at the node with the max betweenness value and tracked at the edge node.The on-path caching location was given by the popularity and the cache size.Simulation results show that,com-pared with the classical schemes,this scheme promotes the cache hit ratio and decreases the average hop ratio,thus en-hancing the efficiency of the cache system.     

Analytical characterization of cache replacement policy impact on content delivery time in information‐centric networks

Information‐centric networking (ICN) has emerged as a promising candidate for designing content‐based future Internet paradigms. ICN increases the utilization of a network through location‐independent content naming and in‐network content caching. In routers, cache replacement policy determines which content to be replaced in the case of cache free space shortage. Thus, it has a direct influence on user experience, especially content delivery time. Meanwhile, content can be provided from different locations simultaneously because of the multi‐source property of the content in ICN. To the best of our knowledge, no work has yet studied the impact of cache replacement policy on the content delivery time considering multi‐source content delivery in ICN, an issue addressed in this paper. As our contribution, we analytically quantify the average content delivery time when different cache replacement policies, namely, least recently used (LRU) and random replacement (RR) policy, are employed. As an impressive result, we report the superiority of these policies in term of the popularity distribution of contents. The expected content delivery time in a supposed network topology was studied by both theoretical and experimental method. On the basis of the obtained results, some interesting findings of the performance of used cache replacement policies are provided.     

CCN中基于替换率的缓存空间动态借调机制

针对内容中心网络(CCN, content centric networking)节点存储资源的有效利用和优化配给问题,在同质化缓存分配的基础上,提出了一种基于替换率的缓存空间动态借调机制。该机制从节点存储空间使用状态的动态差异性出发,首先对于缓存资源借调的合理性给予证明,进而,依据节点对于存储资源的需求程度,动态地执行缓存借调,将相对空闲的存储资源分配给需求程度更大的节点支配,换取过载节点缓存性能的提升。该机制减小了内容请求跳数,提高了缓存命中率,以少量额外的代价换取了内容请求开销的显著下降,提升了存储资源整体利用率,仿真结果验证了其有效性。     

移动边缘计算中基于内容流行度的深度强化学习缓存机制

随着5G商用的推进,涌现出大量依赖高速率、低时延的新应用,混合现实(Mixed Reality,MR)就是其中之一.考虑到从中心云传输服务内容到MR设备会带来很大时延和能耗问题,引入移动边缘计算(Mobile Edge Compu?ting,MEC)技术,通过在MEC服务器上缓存用户的预渲染环境帧,以减少延迟和能耗.针...     

Design of in-network caching scheme in CCN based on grey relational analysis

In-network caching is one of the most important issues in content centric networking （CCN）, which may extremely influence the performance of the caching system. Although much work has been done for in-network caching scheme design in CCN, most of them have not addressed the multiple network attribute parameters jointly during caching algorithm design. Hence, to fill this gap, a new in-network caching based on grey relational analysis （GRA） is proposed. The authors firstly define two newly metric parameters named request influence degree （RID） and cache replacement rate, respectively. The RID indicates the importance of one node along the content delivery path from the view of the interest packets arriving The cache replacement rate is used to denote the caching load of the node. Then combining hops a request traveling from the users and the node traffic, four network attribute parameters are considered during the in-network caching algorithm design. Based on these four network parameters, a GRA based in-network caching algorithm is proposed, which can significantly improve the performance of CCN. Finally, extensive simulation based on ndnSIM is demonstrated that the GRA-based caching scheme can achieve the lower load in the source server and the less average hops than the existing the betweeness （Betw） scheme and the ALWAYS scheme.     

Cooperative caching for content dissemination in vehicular networks

The explosive growth of mobile data traffic has made cellular operators to seek low‐cost alternatives for cellular traffic off‐loading. In this paper, we consider a content delivery network where a vehicular communication network composed of roadside units (RSUs) is integrated into a cellular network to serve as an off‐loading platform. Each RSU subjecting to its storage capacity caches a subset of the contents of the central content server. Allocating the suitable subset of contents in each RSU cache such that maximizes the hit ratio of vehicles requests is a problem of paramount value that is targeted in this study. First, we propose a centralized solution in which, we model the cache content placement problem as a submodular maximization problem and show that it is NP‐hard. Second, we propose a distributed cooperative caching scheme, in which RSUs in an area periodically share information about their contents locally and thus update their cache. To this end, we model the distributed caching problem as a strategic resource allocation game that achieves at least 50% of the optimal solution. Finally, we evaluate our scheme using simulation for urban mobility simulator under realistic conditions. On average, the results show an improvement of 8% in the hit ratio of the proposed method compared with other well‐known cache content placement approaches.