P2P视频点播内容分发策略

视频点播目前已成为对等(peer-to-peer,简称P2P)网络中一项重要的应用,引起了人们的不少研究兴趣.由于P2P网络能够为VoD(video-on-demand)应用的大规模实现提供底层网络的支持,许多正在出现的P2P VoD分发策略都能够提供在P2P网络中最基本的数据传输方式.对以往主要的P2P VoD内容分发策略进行了总结和概括.首先介绍了设计P2P VoD策略的相关重要问题,并把策略根据内容分发方式的不同分成4种类型.最后讨论了它们的应用层性能,并提出未来可以延续的工作.     

树形网络中的一种有效视频内容分发算法

随着互联网中视频内容比重的迅速增加,视频业务随之也在不断的增加,这些视频业务将占据大量的互联网带宽.如何节约带宽和提高视频服务质量已成为互联网研究中的重要研究课题,而提高视频业务服务质量的两个主要途径是增加网络带宽和增加网络中缓存视频服务器的容量.为了使得视频服务商对增加带宽和增加缓存容量的投入最小化,就要决定网络视频内容在网络服务器中如何放置和分发.在本文中,首先我们基于内容放置和内容传输代价对树形网络中的视频内容放置问题进行数学建模,其次我们根据该数学模型提出一种有效的动态规划算法.该算法不仅可以有效解决了我们提出模型中的整数规划问题,而且其时间复杂度为O(NP).     

VOVO: VCR-Oriented Video-on-Demand in Large-Scale Peer-to-Peer Networks

Most P2P Video-On-Demand (VOD) schemes mainly focus more on mending service architectures and optimizing overlays but do not carefully consider the user behavior and the benefit of prefetching strategies. As a result, they cannot better support VCR-oriented services in terms of substantive asynchronous clients, and free VCR controls for P2P VODs. In this paper, we propose VOVO, VCR-oriented VOD for large-scale P2P networks. By mining associations inside a video, the segments requested in VCR interactivities are accurately predicted based on the information collected through gossips. Together with a hybrid caching strategy, a collaborative prefetching scheme is proposed to optimize resource distribution among neighboring peers. We evaluate VOVO through extensive experiments. Results show that VOVO is scalable and effective, providing short startup latencies and good performance in VCR interactivities.     

Optimal Content Location in Multicast Based Overlay Networks with Content Updates

The architecture of overlay networks should support high-performance and high-scalability at low costs. This becomes more crucial when communication, storage costs as well as service latencies grow with the exploding amounts of data exchanged and with the size and span of the overlay network. For that end, multicast methodologies can be used to deliver content from regional servers to end users, as well as for the timely and economical synchronization of content among the distributed servers. Another important architectural problem is the efficient allocation of objects to servers to minimize storage, delivery and update costs. In this work, we suggest a multicast based architecture and address the optimal allocation and replication of dynamic objects that are both consumed and updated. Our model network includes consumers which are served using multicast or unicast transmissions and media sources (that may be also consumers) which update the objects using multicast communication. General costs are associated with distribution (download) and update traffic as well as the storage of objects in the servers. Optimal object allocation algorithms for tree networks are presented with complexities of O(N) and O(N ²) in case of multicast and unicast distribution respectively. To our knowledge, the model of multicast distribution combined with multicast updates has not been analytically dealt before, despite its popularity in the industry.     

内容分布网络基于策略的管理

采用内容分布的方法可以改善基于Web应用的性能,但网络中设备的管理很复杂,采用基于策略的技术可以简化其管理。本文论证了对内容分布网络(CDN: Content Dis-tribution Network)基于策略的管理的可行性,为CDN的控制和管理提出了一个基于策略的体系结构。     

基于机会网络的最优化动态合作树选择算法

结点的移动性、传递信息的随机性和无链路连接传递是机会网络的一些信息传递的重要特征,而这些特征与人类社会中人类传递信息的过程极为相似。传统的机会网络算法用于社会网络时会因为环境的变化、人类社会特有的关系属性等问题不能获得很好的效果。因此,本文将随机性、移动性、无连接性等特征作为连接机会网络与社会网络的桥梁,设计了一种选择最优化动态合作树的算法。该算法通过建立动态拓扑结构树的方式,并建立可靠性、可用性、衰减因子、权重因子等作为拓扑结构中的权值进行计算,从而得到最优合作对象和最优合作路径。仿真实验表明,与经典的机会网络算法相比,该算法取得了很好的效果。     

一种内容分发网络中的快速复制方案

由于在内容分发网络中．将大文件从一台服务器复制到其他服务器需要耗费大量的时间。本文首先对内容分发网络中的复制问题进行了形式化描述，然后提出了一种分布式的方案NCOM，用于减小复制时间。方案的创新性在于，NCOM在CDN中构建一个Mesh结构，利用多路径传输数据块，提高速率；同时也利用Network Coding技术来避免需要从不同路径调度不同数据块所带来的协调开销。实验结果表明，与现有方案相比，NCOM可以显著减小复制时间。     

An Equitable Bandwidth Allocation Model for Video-on-Demand Networks

Video-on-Demand (VOD) or near-VOD services are expected to grow significantly over time, providing diverse programs for home entertainment, learning and training, news-on-demand, and other applications. These services require large bandwidth resources. We present a model for bandwidth allocation in a tree network with limited link capacities, where a server at the root node repeatedly broadcasts copies of various programs. The time intervals between successive broadcasts of each program can be increased at subsequent nodes, or the video quality can be decreased, thus providing different service performance to different nodes while satisfying the capacity constraints. The model is formulated as an equitable resource allocation problem with a lexicographic minimax objective function and tree-like ordering constraints. We present a lexicographic minimax algorithm that allocates each link’s bandwidth among the programs carried on the link. The algorithm repeatedly solves minimax problems, and fixes some variables at their optimal value after the solution of each such problem. The algorithm for solving the minimax problems uses a bisection search to find the minimax solution with the minimal decision variable values. The model also provides an ordered list of links from the most critical link to the least critical link, a useful feature for capacity expansion planning decisions.     

内容分发网发展综述

随着互联网的高速发展,网络服务对于内容传榆的质量要求也越来越高,内容分发网(Content Delivery/Dis-tribution Networks,CDN)被证明是一种提高网络性能和加速网络业务的有效方式,在10年的时间内成为互联网不可或缺的核心技术之一.以CDN榘构的演变为标准,将CDN技术的演进过程分为缓存辅助CDN、光纤辅助CDN以及对等网辅助CDN三个阶段.阐述对于CDN关键技术在互联网需求推动下的研究与发展,并展望CDN未来的发展趋势.     

Optimal Tree Contraction and Term Matching on the Hypercube and Related Networks

An optimal tree contraction algorithm for the boolean hypercube and the constant-degree hypercubic networks, such as the shuffle exchange or the butterfly network, is presented. The algorithm is based on novel routing techniques and, for certain small subtrees, simulates optimal PRAM algorithms. For trees of size n, stored on a p processor hypercube in in-order, the running time of the algorithm is . The resulting speed-up of is optimal due to logarithmic communication overhead, as shown by a corresponding lower bound. The same algorithmic ingredients can also be used to solve the term matching problem, one of the fundamental problems in logic programming. Received August 10, 1994; revised May 2, 1995.     

Prefetching in Content Distribution Networks via Web Communities Identification and Outsourcing

Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the “edge” of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the “last mile” latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of “correlated” Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity.     

Bayes网络最优近似下边缘分布的不变性

删除Bayes网络中的弧以减小网络结构的复杂性,从而降低概率推理算法的复杂度是一种对Bayes网络进行近似的方法．该文讨论了在删除Bayes网络中的一条弧之后得到的最优近似概率分布和原概率分布之间的关系,证明了对满足一定条件的结点子集而言,其边缘概率分布在近似以后具有不变性．     

uCast: Unified Connectionless Multicast for Energy Efficient Content Distribution in Sensor Networks

In this paper, we present uCast, a novel multicast protocol for energy efficient content distribution in sensor networks. We design uCast to support a large number of multicast sessions, especially when the number of destinations in a session is small. In uCast, we do not keep any state information relevant to ongoing multicast deliveries at intermediate nodes. Rather, we directly encode the multicast information in the packet headers and parse these headers at intermediate nodes using a scoreboard algorithm proposed in this paper. We demonstrate that 1) uCast is powerful enough to support multiple addressing and unicast routing schemes and 2) uCast is robust, efficient, and scalable in the face of changes in network topology, such as those introduced by energy conservation protocols. We systematically evaluate the performance of uCast through simulations, compare it with other state-of-the-art protocols, and collect preliminary data from a running system based on the Berkeley motes platform     

Evolutionary Algorithms for Optimizing Cost and QoS on Cloud-based Content Distribution Networks

Programming and Computer Software - Content Distribution Networks (CDN) are key for providing worldwide services and content to end-users. In this work, we propose three multiobjective evolutionary...     

安全组播中的密钥树最优结构

组播常用来对一组用户发送数据．为了保障安全性，安全组播使用组内共享的加密密钥对组内通信进行加密．因为组成员关系的动态性，有效进行组密钥管理成为安全组播通信性能的关键．本文研究了组密钥管理的密钥树结构，并提出了一种新的基于组成员更新概率的最优密钥树结构．这种结构能够进一步减少系统开销．实验结果表明这种密钥树结构要优于其它基于组成员更新概率的密钥树结构，同时理论分析给出了这种结构的平均更新代价的取值范围．     

内容分发网络中带容量和能力约束的副本放置问题研究

副本放置问题是内容分发网络中的一项关键技术,已有的副本放置模型未考虑服务器的负载能力,本文研究考虑了基于内容分发网络服务器存储容量约束与服务能力约束的副本放置问题,建立了双约束的副本放置模型,设计了贪婪算法,把两阶段的模型求解转化成求解一系列的单服务器节点的最小费用流模型,获得了副本放置策略和用户请求重定向策略,并分析了算法的复杂性。     

Labeling Schemes for Dynamic Tree Networks

Distance labeling schemes are composed of a marker algorithm for labeling the vertices of a graph with short labels, coupled with a decoder algorithm allowing one to compute the distance between any two vertices directly from their labels (without using any additional information). As applications for distance labeling schemes concern mainly large and dynamically changing networks, it is of interest to study distributed dynamic labeling schemes. The current paper considers the problem on dynamic trees, and proposes efficient distributed schemes for it. The paper first presents a labeling scheme for distances in the dynamic tree model, with amortized message complexity O(log² n) per operation, where n is the size of the tree at the time the operation takes place. The protocol maintains O(log² n) bit labels. This label size is known to be optimal even in the static scenario. A more general labeling scheme is then introduced for the dynamic tree model, based on extending an existing static tree labeling scheme to the dynamic setting. The approach fits a number of natural tree functions, such as distance, separation level, and flow. The main resulting scheme incurs an overhead of an O(log n) multiplicative factor in both the label size and amortized message complexity in the case of dynamically growing trees (with no vertex deletions). If an upper bound on n is known in advance, this method yields a different tradeoff, with an O(log² n/log log n) multiplicative overhead on the label size but only an O(log n/log log n) overhead on the amortized message complexity. In the fully dynamic model the scheme also incurs an increased additive overhead in amortized communication, of O(log² n) messages per operation.     

Optimal Influence Strategies in Social Networks

This paper suggests a modeling framework to investigate the optimal strategy followed by a monopolistic firm aiming to manipulate the process of opinion formation in a social network. The monopolist and a set of consumers communicate to form their beliefs about the underlying product quality. Since the firm’s associated optimization problem can be analytically solved only under specific assumptions, we rely on the sequential quadratic programming computational approach to characterize the equilibrium. When consumers’ initial beliefs are uniform, the firm’s optimal influence strategy always involves targeting the most influential consumer. For the case of non-uniform initial beliefs, the monopolist might target the less influential consumer if the latter’s initial opinion is low enough. The probability of investing more in the consumer with the lower influence increases with the distance between consumers’ initial beliefs and with the degree of trust attributed on consumers by the firm. The firm’s profit is minimized when consumers’ influences become equal, implying that the firm benefits from the presence of consumers with divergent strategic locations in the network. In the absence of a binding constraint on total investment, the monopolist’s incentives to manipulate the network decrease with consumers’ initial beliefs and might either increase or decrease with the trust put in consumers’ opinion by the firm. Finally, the firm’s strategic motivation to communicate persistently high beliefs during the opinion formation process is positively associated with the market size, with the available budget and with the direct influence of the most influential consumer on the other but negatively associated with consumers’ initial valuation of the good.