Caching video objects: layers vs versions?

Because Internet access rates are highly heterogeneous, many video content providers today make available different versions of the videos, with each version encoded at a different rate. Multiple video versions, however, require more server storage and may also dramatically impact cache performance in a traditional cache or in a CDN server. An alternative to versions is layered encoding, which can also provide multiple quality levels. Layered encoding requires less server storage capacity and may be more suitable for caching; but it typically increases transmission bandwidth due to encoding overhead. In this paper we compare video streaming of multiple versions with that of multiple layers in a caching environment. We examine caching and distribution strategies that use both versions and layers. We consider two cases: the request distribution for the videos is known a priori; and adaptive caching, for which the request distribution is unknown. Our analytical and simulation results indicate that mixed distribution/caching strategies provide the best overall performance.A shorter version of this work has appeared in Proc. of IEEE International Conference on Multimedia and Expo (ICME), Vol. 2, pages 45–48, Lausanne, Switzerland, August 2002     

A weighted segment-based caching algorithm for video streaming objects over heterogeneous networking environments

Traditional caching technology is not applicable to cache video streaming objects over heterogeneous networking environments. The popularity of mobile devices in the heterogeneous networking environments make the access of Internet content become a common phenomenon. To support different mobile devices in the heterogeneity networking environments, a transcoding proxy is used to transcode different versions of the streaming videos according to clients’ requests. In this paper, we propose a weighted caching replace strategy for video streaming objects over heterogeneous networking environments. A new caching algorithm with static weight transcoding graph and dynamic caching relation tree is introduced. The proposed algorithm is compared with LRU, LFU, CP and PF cache algorithms in three parts: hit ratio, byte hit ratio, and average transmission delay. Experimental results show that the proposed algorithm outperforms than traditional LRU, LFU, CP and PF cache algorithms.     

OCS: An effective caching scheme for video streaming on overlay networks

Video streaming is vital for many important applications such as distance learning, digital video libraries, and movie-on-demand. Since video streaming requires significant server and networking resources, caching has been used to reduce the demand on these resources. In this paper, we propose a novel collaboration scheme for video caching on overlay networks, called Overlay Caching Scheme (OCS), to further minimize service delays and loads placed on an overlay network for video streaming applications. OCS is not a centralized nor a hierarchical collaborative scheme. Despite its design simplicity, OCS effectively uses an aggregate storage space and capability of distributed overlay nodes to cache popular videos and serve nearby clients. Moreover, OCS is light-weight and adaptive to clients’ locations and request patterns. We also investigate other video caching techniques for overlay networks including both collaborative and non-collaborative ones. Compared with these techniques on topologies inspired from actual networks, OCS offers extremely low average service delays and approximately half the server load. OCS also offers smaller network load in most cases in our study.

交互式流媒体代理缓存

基于代理的流媒体应用中通常假设用户总是从媒体内容的起始部分请求播放.然而,在交互式场景下用户的焦点可能是媒体内容的任意部分.针对交互式流媒体应用,提出了一种基于分段的流行度敏锐(popularitywise)缓存算法,适用于缓存任意媒体内容流行度分布下的热点部分.仿真结果表明,现有的分段缓存算法的性能随着用户交互强度的增加而显著下降,而流行度敏锐算法在不同的用户请求模式和交互强度下都可以提供较低的用户响应时延和链路占用带宽.     

Performance analysis of a caching algorithm for a catch-up television service

The catch-up TV (CUTV) service allows users to watch video content that was previously broadcast live on TV channels and later placed on an on-line video store. Upon a request from a user to watch a recently missed episode of his/her favourite TV series, the content is streamed from the video server to the customer’s receiver device. This requires that an individual flow is set up for the duration of the video, and since it is hard to impossible to employ multicast streaming for this purpose (as users seldomly issue a request for the same episode at the same time), these flows are unicast. In this paper, we demonstrate that with the growing popularity of the CUTV service, the number of simultaneously running unicast flows on the aggregation parts of the network threaten to lead to an unwieldy increase in required bandwidth. Anticipating this problem and trying to alleviate it, the network operators deploy caches in strategic places in the network. We investigate the performance of such a caching strategy and the impact of its size and the cache update logic. We first analyse and model the evolution of video popularity over time based on traces we collected during 10 months. Through simulations we compare the performance of the traditional least-recently used and least-frequently used caching algorithms to our own algorithm. We also compare their performance with a “perfect” caching algorithm, which knows and hence does not have to estimate the video request rates. In the experimental data, we see that the video parameters from the popularity evolution law can be clustered. Therefore, we investigate theoretical models that can capture these clusters and we study the impact of clustering on the caching performance. Finally, some considerations on the optimal cache placement are presented.     

一种基于两级缓存的协同缓存机制

信息中心网络（information-centric networking,简称ICN）将网络通信模式从当前的以地址为中心转变为以信息为中心.泛在化缓存是ICN重要特性之一,它通过赋予网络任意节点缓存的能力来缓和服务器的压力,降低用户访问延迟.然而,由于缺少内容热度的分布感知,现有ICN缓存策略仍存在缓存利用率较低、缓存位置缺乏合理规划等问题.为了解决这些问题,提出一种基于两级缓存的协同缓存机制（a cache coordination scheme based on two-level cache,简称CSTC）.将每个节点的缓存空间分为热度感知和协作分配两部分,为不同热度的内容提供不同的缓存策略.同时,结合提出的热度筛选机制和路由策略,降低了缓存冗余,实现了缓存位置优化.最后,基于真实网络拓扑的仿真实验表明,CSTC在次热门内容缓存数量上提升了2倍,缓存命中率提升了将近50%,且平均往返跳数在多数情况下优于现有On-path缓存方式.     

Network-aware partial caching for Internet streaming media

The delivery of multimedia over the Internet is affected by adverse network conditions such as high packet loss rate and long delay. This paper aims at mitigating such effects by leveraging client-side caching proxies. We present a novel cache architecture and associated cache management algorithms that turn edge caches into accelerators of streaming media delivery. This architecture allows partial caching of media objects and joint delivery from caches and origin servers. Most importantly, the caching algorithms are both network-aware and stream-aware; they take into account the popularity of streaming media objects, their bit rate requirements, and the available bandwidth between clients and servers. Using Internet bandwidth models derived from proxy cache logs and measured over real Internet paths, we have conducted extensive simulations to evaluate the performance of various cache management algorithms. Our experiments demonstrate that network-aware caching algorithms can significantly reduce startup delay and improve stream quality. Our experiments also show that partial caching is particularly effective when bandwidth variability is not very high.Shudong Jin: Corespondence to This research was supported in part by NSF (awards ANI-9986397, ANI-0095988, ANI-0205294 and EJA-0202067) and by IBM. Part of this work was done while the first author was at IBM Research in 2001.     

Frequency-based cache management policies for collaborative and non-collaborative topologies of segment based video caching proxies

This paper examines a novel cache management policy applied to non-collaborative and collaborative environments of more than one proxy server that serve homogeneous or even heterogeneous client requests for video streaming over the Internet. This cache management policy, which we call LRLFU because of a combination between an LRU and an LFU policy, is capable of capturing the changing popularities of the various videos by attaching a caching value to every video according to how recently and how frequently the video was requested, and decides to cache the most ‘valuable’ videos. Our event-driven simulations have shown that LRLFU when applied to a simple non-collaborative topology of proxies and compared with previous work in this area (1) improve the byte-hit ratio (BHR), (2) significantly reduce the fraction of user requests with delayed starts and (3) require less CPU overhead. Furthermore, our simulation results have shown that the collaborative hierarchical tree topology of proxies that we examine achieves a much higher BHR when using the same overall cache capacity with the simple topology and in general provides better performance characteristics.This work was conducted while A. Satsiou was a MSc student in the Department of Electronic and Computer Engineering Technical University of Crete.     

基于媒体流行度和前缀缓存的缓存替换算法

针对流媒体用户访问偏好的情况,提出了一种基于前缀缓存与媒体流行度的缓存替换算法。该算法根据不同媒体外部、内部流行度给出预估的综合流行度,进而选择可用缓存中具有低流行度的片断进行替换,使得缓存中的所有片断的再利用价值之和最大。模拟实验结果表明,该算法能减少缓存的替换次数,提高缓存命中率,性能较好。     

基于动态内容流行度的NDN缓存决策和替换策略研究

命名数据网络(NDN)中的路由器节点具有缓存能力,这就极大地提高了网络中的数据发送与检索效率。然而,由于路由器的缓存能力是有限的,设计有效的缓存策略仍然是一项紧迫的任务。为了解决这个问题,提出了一种动态内容流行度缓存决策和替换策略(DPDR)。DPDR综合考虑内容流行度和缓存能力,利用一个和式增加、积式减少(AIMD)的算法动态调节流行度阈值,并将超过流行度阈值的内容存入缓存空间;同时提出了一个缓存替换算法,综合考虑了缓存空间中内容的流行度和内容最后被访问时间等因素,将替换值最小的内容移出内容缓存。大量仿真结果显示,与其他算法相比,本文所提的算法能够有效提高缓存命中率,缩短平均命中距离和网络吞吐量。     

网络相关媒体流缓存管理策略NRC

Internet网络上媒体流的应用受限于应用时的网络状况，如时延、包丢失率等．本文研究通过在网络边缘处设置缓存代理来减小这些影响，提出一种新的缓存管理算法NRC，即接入媒体流服务时，用户以两种方式获取媒体流对象：一部分对象内容从代理缓存中获取，而另一部分对象内容则直接从流媒体源服务器处传输而来；从而加速媒体流接入服务，提高媒体流服务质量,算法同网络特性和媒体流特性相关．最后仿真实验证实同网络和流媒体特性相关的缓存管理算法NRC可以很好地减少服务延迟和提高媒体流的总体服务质量．     

Design and analysis of a variable bit rate caching algorithm for continuous media data

In this paper, the problem of caching continuous media data in a (main) memory and disk caching system is addressed. Caching schemes can significantly reduce the load on the network as well as on the servers, also the retrieval of documents from the cache requires short response time. In interval-level caching algorithms, an interval of data between two adjacent streams is the basic caching entity. In this paper, we design a novel algorithm, referred to as variable bit rate caching (VBRC) algorithm, which belongs to the interval-level caching algorithms. The proposed VBRC algorithm can be used in the system for memory caching or disk caching. VBRC can handle variable retrieval bandwidth as well as constant retrieval bandwidth . In designing the VBRC algorithm, we propose the strategies of reducing the number of switching operation, which will probably cause discontinuity of retrieving data. Also, we propose a just-in-time scheme for resource allocation in our VBRC algorithm and show that the caching performance in comparison with the reservation scheme adopted in the resource-based caching (RBC) algorithm is significantly improved. Our simulation study compares the recent and most popular generalized interval caching, RBC, and VBRC, on several influencing factors such as cache space size, cache I/O bandwidth, request arrival rate, and percentage of requests for large documents, with respect to the byte hit ratio and the number of switching operations. The simulation result confirms our analysis.

MSC: a multi-version shared caching for multi-bitrate VoD services

Recently, many Video-on-Demand (VoD) service providers try to attract as many users as possible by offering multi-bitrate video streaming services with differentiated qualities. Many researches focus on video layered coding (e.g., scalable video coding, SVC). However, SVC is not widely used in VoD industry. Another solution, multi-version videos, can be classified into online transcoding and pre-stored multi-version videos. Online transcoding is a CPU-intensive and costly task, so it is not suitable for large-scale VoD applications. In this paper, we study how to improve caching efficiency based on pre-stored multi-version videos. We leverage the sharing probability among different versions of the same video and propose a multi-version shared caching (MSC) method to maximize the benefit of caching proxy. If the desired version is not in the cache while the higher neighbor version is in, MSC transmits the higher version streaming to user temporarily. In this case, MSC can make full use of the caching resources to improve the cache hit ratio and decrease users’ average waiting time. Simulation results show that MSC outperforms the others in the cache hit ratio and the average waiting time.     

Characteristics of YouTube network traffic at a campus network – Measurements,models, and implications

User-Generated Content has become very popular since new web services such as YouTube allow for the distribution of user-produced media content. YouTube-like services are different from existing traditional VoD services in that the service provider has only limited control over the creation of new content. We analyze how content distribution in YouTube is realized and then conduct a measurement study of YouTube traffic in a large university campus network. Based on these measurements, we analyzed the duration and the data rate of streaming sessions, the popularity of videos, and access patterns for video clips from the clients in the campus network. The analysis of the traffic shows that trace statistics are relatively stable over short-term periods while long-term trends can be observed. We demonstrate how synthetic traces can be generated from the measured traces and show how these synthetic traces can be used as inputs to trace-driven simulations. We also analyze the benefits of alternative distribution infrastructures to improve the performance of a YouTube-like VoD service. The results of these simulations show that P2P-based distribution and proxy caching can reduce network traffic significantly and allow for faster access to video clips.     

一种P2P流媒体系统中的缓存替换算法

针对视频节目受欢迎程度不同的特性,提出一种P2P流媒体系统中的缓存替换算法,通过将系统中的全部视频片段分类,为其赋予不同的优先级,并周期性地更新该值,同时考虑视频片段被访问次数和最近被访问的情况,使得被替换出存储空间的片段更加合理。实验表明,该算法能提高缓存命中率及系统的启动延时,性能较优。     

Peer Assisted Video Streaming With Supply-Demand-Based Cache Optimization

In this paper, we consider a hybrid P2P video on-demand architecture that utilizes both the server and the peer resources for efficient transmission of popular videos. In our system architecture, each peer dedicates some cache space to store a particular segment of a video file as well as some of its upload bandwidth to serve the cached segment to other peers. Peers join the system and issue a streaming request to a control server. Control server directs the peers to streaming servers or to other peers who have the desired video segments. Control server also decides which peer should cache which video segment. Our main contribution in this paper is to determine the proper caching strategies at peers such that we minimize the average load on the streaming servers.      

基于后缀动态多缓存协作的流媒体分发技术

在Internet上高效传输流媒体数据是推广诸如视频点播等应用的基础．现有方案仅考虑了采用单代理结构的前缀缓存和服务器调度来降低骨干网带宽消耗和服务器负载．在带前缀缓存的Batch patching基础上提出了后缀的动态缓存算法ICBR，并提出了基于ICBR缓存算法的多缓存协作体系结构及协作算法MCC，仿真结果表明，基于ICBR的多缓存协作显著地降低了获取补丁而导致的骨干网带宽的消耗，提高了客户端QoS同时也降低了服务器负载．     

Caching collaboration and cache allocation in peer-to-peer video systems

Providing scalable video services in a peer-to-peer (P2P) environment is challenging. Since videos are typically large and require high communication bandwidth for delivery, many peers may be unwilling to cache them in whole to serve others. In this paper, we address two fundamental research problems in providing scalable P2P video services: (1) how a host can find enough video pieces, which may scatter among the whole system, to assemble a complete video; and (2) given a limited buffer size, what part of a video a host should cache and what existing data should be expunged to make necessary space. We address these problems with two new ideas: Cell caching collaboration and Controlled Inverse Proportional (CIP) cache allocation. The Cell concept allows cost-effective caching collaboration in a fully distributed environment and can dramatically reduce video lookup cost. On the other hand, CIP cache allocation challenges the conventional caching wisdom by caching unpopular videos in higher priority. Our approach allows the system to retain many copies of popular videos to avoid creating hot spots and at the same time, prevent unpopular videos from being quickly evicted from the system. We have implemented a Gnutella-like simulation network and use it as a testbed to evaluate the proposed technique. Our extensive study shows convincingly the performance advantage of the new scheme.

基于联盟链的边缘缓存系统收益最大化的缓存策略

边缘缓存技术能够将热点内容提前放置在距离用户较近的网络边缘,可以显著降低传输时延、提高网络效率。然而,不同的运营商各自部署边缘设备,投入巨大且缓存内容相互隔离,无法共享。针对此问题,改进了一种基于联盟链的边缘缓存系统架构,运营商部署的边缘设备间能够打破内容隔离,实现更大范围的内容共享。此外,设计了基于智能合约的内容交易流程,使得不同运营商之间的合作变得可信、公平和可追踪。最后,考虑到热门内容的流行程度、文件大小以及传输时延等,对热点内容进行定价,并以收益最大化为目标,通过贪婪算法确定缓存内容放置的位置。仿真实验表明,基于该架构下的收益最大化缓存策略能够有效增加边缘缓存的收益。     

On-line Restricted Caching

We study the on-line caching problem in a restricted cache where each memory item can be placed in only a restricted subset of cache locations. Examples of restricted caches in practice include victim caches, assist caches, and skew caches. To the best of our knowledge, all previous on-line caching studies have considered on-line caching in identical or fully-associative caches where every memory item can be placed in any cache location.In this paper, we focus on companion caches, a simple restricted cache that includes victim caches and assist caches as special cases. Our results show that restricted caches are significantly more complex than identical caches. For example, we show that the commonly studied Least Recently Used algorithm is not competitive unless cache reorganization is allowed while the performance of the First In First Out algorithm is competitive but not optimal. We also present two near optimal algorithms for this problem as well as lower bound arguments.