Evaluation of performance enhancing proxies in internet over satellite

Performance enhancing proxies (PEPs) are widely used to improve the performance of TCP over high delay‐bandwidth product links and links with high error probability. In this paper we analyse the performance of using TCP connection splitting in combination with web caching via traces obtained from a commercial satellite system. We examine the resulting performance gain under different scenarios, including the effect of caching, congestion, random loss and file sizes. We show, via analysing our measurements, that the performance gain from using splitting is highly sensitive to random losses and the number of simultaneous connections, and that such sensitivity is alleviated by caching. On the other hand, the use of a splitting proxy enhances the value of web caching in that cache hits result in much more significant performance improvement over cache misses when TCP splitting is used. We also compare the performance of using different versions of HTTP in such a system. Copyright © 2003 John Wiley & Sons, Ltd.     

The Content Driven Mobile Internet

The development of future mobile networks will be driven, in large part, by content and web based services. In this paper, we examine several performance, scalability and architectural challenges faced by future mobile web applications and how advanced mobile content delivery techniques can address these challenges. We review existing content delivery using a taxonomy that consists of three categories: network scaling, end system acceleration, and content and protocol optimization. While wireline content delivery focuses on network and server scalability, mobile content delivery will likely benefit most from optimizing radio link usage. We also present our ongoing work in this area, which extends the functionality of edge caching to the terminal, uses user interest correlation information to maintain low terminal power consumption and adds a new dimension to radio resource management. This revised version was published online in August 2006 with corrections to the Cover Date.     

基于媒体用户访问行为偏好模型的代理缓存算法

目前,代理缓存技术广泛应用于改善流媒体传输的服务质量.文章从实际用户日志文件的分析出发,利用发现的用户浏览流媒体对象时的行为分布模型,提出了一种新的视频流媒体缓存算法.仿真结果证明,该算法可以通过记录很少的用户访问信息获取较高的性能表现.     

Examining the effects of caching,compression and popup filtering on internet surfing

Over the years the number of Web users has increased dramatically unfortunately leading to the inherent problem of congestion. This can affect each user's surfing experience. This paper investigates download times associated with a web request, identifies where delays occur, and provides guidelines which can be followed by web developers to enable a faster and more efficient download and service for their users. We conclude that delays in Internet traffic and congestion can often be attributed to poorly developed sites (e.g. excessive image size). Copyright © 2005 John Wiley & Sons, Ltd.     

A survey on deploying mobile deep learning applications: A systemic and technical perspective

With the rapid development of mobile devices and deep learning, mobile smart applications using deep learning technology have sprung up. It satisfies multiple needs of users, network operators and service providers, and rapidly becomes a main research focus. In recent years, deep learning has achieved tremendous success in image processing, natural language processing, language analysis and other research fields. Despite the task performance has been greatly improved, the resources required to run these models have increased significantly. This poses a major challenge for deploying such applications on resource-restricted mobile devices. Mobile intelligence needs faster mobile processors, more storage space, smaller but more accurate models, and even the assistance of other network nodes. To help the readers establish a global concept of the entire research direction concisely, we classify the latest works in this field into two categories, which are local optimization on mobile devices and distributed optimization based on the computational position of machine learning tasks. We also list a few typical scenarios to make readers realize the importance and indispensability of mobile deep learning applications. Finally, we conjecture what the future may hold for deploying deep learning applications on mobile devices research, which may help to stimulate new ideas.     

内容中心网络中能效感知的概率性缓存机制

内置缓存技术是内容中心网络(Content Centric Networking, CCN)的核心技术之一。现有的研究大多主要针对网络资源利用率的优化,而忽略了网络能耗的问题。该文首先建立了一个能耗模型对CCN的网络能耗进行分析,并设计了一个能效判决条件来优化缓存过程的能效性。进而,在此基础上综合考虑内容流行度和节点中心性等因素提出一种能效感知的概率性缓存机制(E2APC)。仿真结果表明,该机制能在保证较高的缓存命中率和较小的平均响应跳数的同时有效地降低网络的整体能耗。     

CCN网络中一种基于代理主动缓存的用户移动性支持方案

该文提出以内容为中心的网络(CCN)中一种基于代理的主动缓存方案。通过代理服务器主动请求与缓存移动切换过程中用户未能获取的内容,解决CCN网络中用户移动性支持问题。与现有CCN网络用户移动性支持方案相比,该文提出的基于代理的主动缓存方案,用户获取内容的时间成本与代理服务器获取内容的时间成本较低,用户的移动切换时延与内容获取的平均时间较短。该方案可有效利用CCN网络共享的内容资源,减缓用户移动对实时业务的不良影响。     

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。     

Impacts of user-selfishness on cooperative content caching in social wireless networks

Cooperative caching can be an effective mechanism for reducing electronic content provisioning cost in Social Wireless Networks (SWNETs). These networks are formed by a collection of mobile data enabled devices physically gathering in settings such as university campus, malls, airport and other public places. In this paper, we first propose an optimal collaborative object caching policy in order to minimize the object provisioning cost in SWNETs with homogenous user requests and a peer-rebate model for promoting collaboration. Then using an analytical model we study the impacts of user selfishness on the provisioning cost and the earned rebate when certain nodes in an SWNET selfishly deviate from the optimal policy. User selfishness is motivated in order to either increase individually earned rebate or to reduce content provisioning cost. The analytical model is validated by experimental results from simulated SWNETs using the network simulator ns2.     

An altruistic cross‐layer recovering mechanism for ad hoc wireless networks

Video streaming services have restrictive delay and bandwidth constraints. Ad hoc networks represent a hostile environment for this kind of real‐time data transmission. Emerging mesh networks, where a backbone provides more topological stability, do not even assure a high quality of experience. In such scenario, mobility of terminal nodes causes link breakages until a new route is calculated. In the meanwhile, lost packets cause annoying video interruptions to the receiver. This paper proposes a new mechanism of recovering lost packets by means of caching overheard packets in neighbor nodes and retransmit them to destination. Moreover, an optimization is shown, which involves a video‐aware cache in order to recover full frames and prioritize more significant frames. Results show the improvement in reception, increasing the throughput as well as video quality, whereas larger video interruptions are considerably reduced. Copyright © 2014 John Wiley & Sons, Ltd.