Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content.In light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of location.If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of resources.Hence,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate prediction.The findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 s.Within a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G networks.These improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving congestion.By improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

A Hybrid Heuristic Service Caching and Task Offloading Method for Mobile Edge Computing

Computing-intensive and latency-sensitive user requests pose significant challenges to traditional cloud computing.In response to these challenges,mobile edge computing(MEC)has emerged as a new paradigm that extends the computational,caching,and communication capabilities of cloud computing.By caching certain services on edge nodes,computational support can be provided for requests that are offloaded to the edges.However,previous studies on task offloading have generally not considered the impact of caching mechanisms and the cache space occupied by services.This oversight can lead to problems,such as high delays in task executions and invalidation of offloading decisions.To optimize task response time and ensure the availability of task offloading decisions,we investigate a task offloading method that considers caching mechanism.First,we incorporate the cache information of MEC into the model of task offloading and reduce the task offloading problem as a mixed integer nonlinear programming(MINLP)problem.Then,we propose an integer particle swarm optimization and improved genetic algorithm(IPSO_IGA)to solve the MINLP.IPSO_IGA exploits the evolutionary framework of particle swarm optimization.And it uses a crossover operator to update the positions of particles and an improved mutation operator to maintain the diversity of particles.Finally,extensive simulation experiments are conducted to evaluate the performance of the proposed algorithm.The experimental results demonstrate that IPSO_IGA can save 20%to 82%of the task completion time,compared with state-of-theart and classical algorithms.Moreover,IPSO_IGA is suitable for scenarios with complex network structures and computing-intensive tasks.

Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems

There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.

基于内容的Web Caching

提出一个新的 Web Caching结构模型—基于内容的 Web Caching.模型综合考虑了 Proxy的操作信息和 Web文档的内容特性 ,界定了虚拟用户团体和 Proxy个性 ,并利用 Ontology技术来刻画 Proxy的个性 ,模拟实验表明 ,结合内容属性可以使得 Web

Mobile Edge Communications, Computing, and Caching(MEC3) Technology in the Maritime Communication Network

With the increasing maritime activities and the rapidly developing maritime economy, the fifth-generation(5G) mobile communication system is expected to be deployed at the ocean. New technologies need to be explored to meet the requirements of ultra-reliable and low latency communications(URLLC) in the maritime communication network(MCN). Mobile edge computing(MEC) can achieve high energy efficiency in MCN at the cost of suffering from high control plane latency and low reliability. In terms of this issue, the mobile edge communications, computing, and caching(MEC3) technology is proposed to sink mobile computing, network control, and storage to the edge of the network. New methods that enable resource-efficient configurations and reduce redundant data transmissions can enable the reliable implementation of computing-intension and latency-sensitive applications. The key technologies of MEC3 to enable URLLC are analyzed and optimized in MCN. The best response-based offloading algorithm(BROA) is adopted to optimize task offloading. The simulation results show that the task latency can be decreased by 26.5’ ms, and the energy consumption in terminal users can be reduced to 66.6%.

Energy-Efficient Joint Content Caching and Small Base Station Activation Mechanism Design in Heterogeneous Cellular Networks

Heterogeneous cellular networks(HCNs), by introducing caching capability, has been considered as a promising technique in 5 G era, which can bring contents closer to users to reduce the transmission delay, save scarce bandwidth resource. Although many works have been done for caching in HCNs, from an energy perspective, there still exists much space to develop a more energy-efficient system when considering the fact that the majority of base stations are under-utilized in the most of the time. Therefore, in this paper, by taking the activation mechanism for the base stations into account, we study a joint caching and activation mechanism design to further improve the energy efficiency, then we formulate the optimization problem as an Integer Linear Programming problem(ILP) to maximize the system energy saving. Due to the enormous computation complexity for finding the optimal solution, we introduced a Quantum-inspired Evolutionary Algorithm(QEA) to iteratively provide the global best solution. Numerical results show that our proposed algorithm presents an excellent performance, which is far better than the strategy of only considering caching without deactivation mechanism in the actual, normal situation. We also provide performance comparison amongour QEA, random sleeping algorithm and greedy algorithm, numerical results illustrate our introduced QEA performs best in accuracy and global optimality.

Architecture of Multimedia Proxy Caching over the Internet

Streaming media data have strict delay and loss requirements, which cannot be adequately supported by the current Internet. Proxy caching technology is introduced to alleviate the effect of the bottleneck bandwidth on the transporting quality. A new architecture of multimedia proxy caching is given to solve the problem of the traditional Web caching technology for the multimedia streaming. The mixed media management module and the (resource) management module are added to this architecture, the prefetching and replacement method is studied considering the characteristics of streaming media data, the concept of weighed popularity is given to enhance the (exactness) of the replacement algorithm.

The Configuration Strategies on Caching for Web Servers

The Web cluster has been a popular solution of network server system because of its scalability and cost effective ness. The cache configured in servers can result in increasing significantly performance, In this paper, we discuss the suitable configuration strategies for caching dynamic content by our experimental results. Considering the system itself can provide support for caching static Web page, such as computer memory cache and disk＇s own cache, we adopt a special pattern that only caches dynamic Web page in some experiments to enlarge cache space. The paper is introduced three different replacement algorithms in our cache proxy module to test the practical effects of caching dynamic pages under different conditions. The paper is chiefly analyzed the influences of generated time and accessed frequency on caching dynamic Web pages. The paper is also provided the detailed experiment results and main conclusions in the paper.

Shared Cache Based on Content Addressable Memory in a Multi-Core Architecture

Modern shared-memory multi-core processors typically have shared Level 2(L2)or Level 3(L3)caches.Cache bottlenecks and replacement strategies are the main problems of such architectures,where multiple cores try to access the shared cache simultaneously.The main problem in improving memory performance is the shared cache architecture and cache replacement.This paper documents the implementation of a Dual-Port Content Addressable Memory(DPCAM)and a modified Near-Far Access Replacement Algorithm(NFRA),which was previously proposed as a shared L2 cache layer in a multi-core processor.Standard Performance Evaluation Corporation(SPEC)Central Processing Unit(CPU)2006 benchmark workloads are used to evaluate the benefit of the shared L2 cache layer.Results show improved performance of the multicore processor’s DPCAM and NFRA algorithms,corresponding to a higher number of concurrent accesses to shared memory.The new architecture significantly increases system throughput and records performance improvements of up to 8.7%on various types of SPEC 2006 benchmarks.The miss rate is also improved by about 13%,with some exceptions in the sphinx3 and bzip2 benchmarks.These results could open a new window for solving the long-standing problems with shared cache in multi-core processors.

MSs-MEC中基于DRL的服务缓存和任务迁移联合优化算法

多服务移动边缘计算(multiple-services mobile edge computing,MSs-MEC)能根据需求自适应调整服务缓存决策,使得部署在用户侧的边缘服务器能够灵活处理不同服务类型的任务。但在实际应用中,特定类型任务的成功迁移依赖于服务环境的提前安装。此外,同时进行任务迁移和服务缓存可能会因时间冲突而导致计算延时。因此,针对上述相关问题,首先将任务迁移和服务缓存决策进行解耦,针对深度强化学习(deep reinforcement learning,DRL)在具有高维的混合决策空间的性能提升不明显的缺点(例如资源分配时利用率不高),将DRL与Transformer结合,通过在历史数据中学习,输出当前时隙的任务迁移决策和下一时隙的任务决策,保证任务到达边缘服务器时能立即执行。其次,为了提高资源分配问题中的资源利用率,将问题分解为连续资源分配问题和离散的任务迁移与服务缓存问题,利用凸优化技术求解资源分配最优决策。广泛的数值结果表明,与其他基线算法相比,提出的算法能有效地减少任务的平均完成时延,同时在资源利用率和稳定性方面也有优异的表现。

P2P流媒体Cache的置换算法

P2P流媒体cache是一种有效减少带宽开销、提高对象利用率的技术,通常采用FIFO,LRU等算法置换内容.然而,流媒体不同于Web对象,P2P网络也有别于客户/服务器模式.在分布式应用中这些算法可能影响系统的性能,为此,分析了FIFO和LRU置换算法,提出了基于供求关系的SD算法,以及基于分片副本数量的REP算法,并对其进行评估和比较.针对不同的节点到达间隔,将SD和REP同FIFO,LRU进行比较,发现在启动延迟、媒体副本数量和根节点依赖度方面SD和REP几乎均优于FIFO和LRU.同LSB(least sent bytes)算法相比,某些场景中SD的启动延迟减少了约40%,而REP在副本数量方面远远超过LSB的结果,说明在P2P网络流媒体服务中使用SD和REP缓存置换算法有助于提高系统性能.

针对RSA算法的踪迹驱动数据Cache计时攻击研究

Cache计时攻击是旁路攻击领域的研究热点.针对滑动窗口算法实现模幂运算的RSA算法,分析了RSA算法访问驱动Cache计时攻击的难点,建立了踪迹驱动数据Cache计时攻击模型.在攻击模型与原有踪迹驱动计时攻击算法的基础上,利用幂指数与操作序列的相关性、窗口大小特征和预计算表索引值与窗口值的映射关系,提出了一种改进的幂指数分析算法,并给出了利用幂指数dp和dq的部分离散位恢复出私钥d的格攻击过程.利用处理器的同步多线程能力实现了间谍进程与密码进程的同步执行,针对OpenSSL v0.9.8b中的RSA算法,在真实环境下执行攻击实验.实验结果表明:新的分析算法大约能够获取512位幂指数中的340位,比原有算法进一步降低了密钥恢复的复杂度;同时对实际攻击中的关键技术以及可能遇到的困难进行分析,给出相应的解决方案,进一步提高了攻击的可行性.

基于Cache优化的大点数FFT在TS201上的实现

该文针对现有大点数快速傅里叶变换(FFT)在TS201处理器上的实现没有充分考虑Cache丢失对执行效率影响的问题,提出了改进型Winograd算法的实现方法。该改进型方法通过优化行列读取方法,最大程度利用Cache的读写特点,避免了三次显性转置;并通过重构蝶形运算,隐藏了乘铰链因子。实例测试与现有处理方法对比结果表明,Cache优化的大点数FFT执行速度有了明显提高,可用于雷达处理系统中的脉冲压缩的快速实现。

存储系统的集中式Cache替换算法

为了最大限度地优化存储系统的I/O性能,通过对存储系统性能的分析,提出一种Cache替换算法———最小访问时间算法(LAT).该算法为Cache中数据对象定义一个排队函数,该函数不仅与对象的Cache命中率有关,还与对象的设备访问速度有关.按照此函数,Cache替换访问次数少、设备访问时间短的对象,从而使得存储系统的平均I/O时间最短.实验结果表明,随着设备访问速度差的增加,LAT算法的平均I/O性能远远优于LRU和LFU.

大规模视频点播磁盘cache替换算法

大规模视频点播（ＬＳＶＯＤ）中ｃａｃｈｅ机制是提高系统效率的有效手段，是支持ＶＯＤ实用化的关键技术之一．由于连续媒体的数据量大，使用周期长等特点，传统的ｃａｃｈｅ替换算法不能直接应用于ＬＳＶＯＤ．文中根据ＶＯＤ的特点开发了两种基于访问频率的替换算法：ＬＦＲＵ（ｌｅａｓｔｆｒｅｑｕｅｎｃｙ ａｎｄ ｒｅｃｅｎｔｌｙ ｕｓｅｄ）和ＰＬＦＵ（ｐｅｒｉｏｄ ｌｅａｓｔｆｒｅ－ｑｕｅｎｃｙ ｕｓｅｄ）算法，它们都试图将访问频率大的视频数据保留在ｃａｃｈｅ中．ＬＦＲＵ 算法结合了数据的访问频率和访问时间信息，对访问模式的变化具有一定的适应性．ＰＬＦＵ 算法用周期法和预测法解决了ＬＦＵ 算法中的ｃａｃｈｅ“污染”问题．实验数据显示，新的替换算法比传统的替换算法效率高，更适合大规模的ＶＯＤ系统．

面向多线程程序基于效用的Cache优化策略

为了提供高速的数据访问,多核处理器常使用Cache划分机制来分配二级Cache资源,但传统的共享Cache划分算法大多是面向多道程序的,忽略了多线程负载中共享和私有数据访问模式的差别,使得共享数据的使用效率降低.提出了一种面向多线程程序的Cache管理机制UPP,它通过监控Cache中共享、私有数据的效用信息,为每个线程以及共享数据分配Cache空间,使得各个线程以及共享数据的边际效用最大化,从而提高负载的整体性能.另外,UPP还考虑了程序中数据的使用频率以及临近性信息,通过提升、动态插入策略过滤低重用数据,从而使得高频数据块留在Cache中.通过实验表明,其性能相对于基于LRU的纯共享Cache结构和基于公平的静态Cache划分结构均有提升.

基于Memcached内存对象缓存技术应用研究

内存对象缓存技术近年来受到业界和学界的广泛关注,Memcached既是一种分布式缓存服务器,也是分布式内存对象缓存系统的典型代表。其以最小的资源消耗获得高效的服务性能优势,广泛应用于Web应用系统中。Memcached自身的内存管理机制、分布式算法并非完美,对此,文中以提升Web应用系统性能为目标,利用分布式算法,基于Memcached对内存对象缓存技术进行深入研究,通过一致性Consistent Hashing算法减轻因添加服务器节点而造成缓存命中率降低的代价,提高增加服务器节点后的缓存命中率,并将优化后的Memcached应用于某电子商务平台之中。测试表明,此电子商务应用系统的请求数、流量、TCP连接数以及CPU利用率等技术指标改善明显,利用Memcached能够有效减轻数据库服务器负载压力,提高Web应用系统响应速度,增强用户体验效果。

面向能耗优化的自适应可重构指令Cache

可重构Cache架构可根据程序的存储资源需求自动调整Cache结构,对系统能耗优化具有重要意义。设计了一种容量和组关联度可重构的指令Cache架构以及与之对应的高效自适应可重构算法。通过选取MiBench和MediaBench中的8个测试例程进行测试验证,提出的自适应可重构Cache与16kB四路组关联配置固定的指令Cache相比,在性能平均仅下降0.34%的情况下,系统总能耗平均降低10.51%。

支持Cache库的语义Web服务匹配算法

为了提高匹配算法在大量服务请求时的执行效率,提出了一种支持服务Cache库的服务发现算法。将已匹配成功的服务放在专门的Cache库中,服务匹配时首先与Cache库中的服务进行匹配,匹配成功即可输出服务,否则再与注册库中的服务进行匹配,匹配成功后需及时更新Cache库中的服务以保持与注册库中的一致。为了筛选出符合要求的服务,提出在匹配过程中进行分阶匹配的策略,分不同阶段逐次进行匹配。实验结果表明,该方法可以有效地提高服务匹配的效率。

多核系统中共享Cache的冒泡替换算法

在多核环境下,对共享L2 Cache的优化显得尤为重要,因为当被访问的数据块不在L2 Cache中时(发生L2缺失),CPU需要花费几百个周期访问主存的代价是相当大的.在设计Cache时,替换算法是考虑的一个重要因素,替换算法的好坏直接影响Cache的性能和计算机的整体性能.虽然LRU替换算法已经被广泛应用在片上Cache中,但是也存在着一些不足:当Cache容量小于程序工作集时,容易产生冲突缺失;且LRU替换算法不考虑数据块被访问的频率.文中把冒泡替换算法应用到多核共享Cache中,同时考虑数据块被访问的频率和最近访问的信息.通过分析实验数据,与LRU替换算法相比,采用冒泡替换算法可以使MPKI(Misses per Kilo instructions)和L2 Cache命中率均有所改善.