Proactive content caching by exploiting transfer learning for mobile edge computing

To address the vast multimedia traffic volume and requirements of user quality of experience in the next‐generation mobile communication system (5G), it is imperative to develop efficient content caching strategy at mobile network edges, which is deemed as a key technique for 5G. Recent advances in edge/cloud computing and machine learning facilitate efficient content caching for 5G, where mobile edge computing can be exploited to reduce service latency by equipping computation and storage capacity at the edge network. In this paper, we propose a proactive caching mechanism named learning‐based cooperative caching (LECC) strategy based on mobile edge computing architecture to reduce transmission cost while improving user quality of experience for future mobile networks. In LECC, we exploit a transfer learning‐based approach for estimating content popularity and then formulate the proactive caching optimization model. As the optimization problem is NP‐hard, we resort to a greedy algorithm for solving the cache content placement problem. Performance evaluation reveals that LECC can apparently improve content cache hit rate and decrease content delivery latency and transmission cost in comparison with known existing caching strategies.     

智能终端发展关键技术探讨

智能终端产品(包括手机、平板和混合式的移动计算设备)在个人和商业应用场合大量使用,终端在高速计算能力方面更新迅猛,处理能力军备竞赛将陷入硬件瓶颈,同质现象成为现实,而人机交互技术、终端应用开发环境、终端安全云服务等将成为影响智能终端向纵深人群渗透和更商业化应用领域发展的决定要素。本文旨在探讨、分析和展示上述几个关键技术的新进展和演进趋势。     

基于谱线平移的低信噪比高动态信号多普勒频偏捕获算法

针对低信噪比高动态信号的载波频偏捕获提出了一种新的算法即谱线平移算法.首先,介绍了现有的大载波频偏捕获技术,分析了其不能适应高动态信号捕获的原因;其次,分析了载波频偏及其变化率对载波频偏捕获的影响,主要考虑多普勒频移变化率对信号捕获的影响,它将严重限制低信噪比情况下对载波频偏估计时非相干累加的次数,在此基础上,提出并研究了适应低信噪比高动态信号大载波频偏捕获的谱线平移算法,并对算法进行了性能仿真,表明其具有2 ～3dB的改善增益,与最大似然算法相比具有绝对优势.     

移动IP在无线局域网下的一种快速切换方法

针对移动IP在无线局域网下的应用,提出了一种新的基于链路层的移动IP快速切换方法,通过在无线局域网的无线接入点间加入特定的MAC网桥来减少移动节点在切换时产生的切换时延,进而减少移动节点上行和下行方向上的数据包的丢失,达到对移动IP切换进行优化的目的。此方法在无线局域网实际环境中进行了性能测试,结果证明优化后的时延较之原来普通移动IP切换时延有明显降低。     

基于WiFi技术的智能搜救机器人

为了实现对地震、泥石流等灾害现场的实时监控,依托WiFi网络和遥控机器人技术设计了一台智能搜救机器人,引入多种传感器设备,实现灾后现场的实时监控和救援。通过无线传输技术实现机器人上位机与下位机之间的通信,下位机软件将机器人采集到的视频信息传送到上位机,上位机根据所接收到的视频信息向下位机发送控制命令,实现远距离移动监控。通过在机器人车体上搭载机械臂拓展机器人的搬运功能,实现作业现场障碍物清除工作。重点阐明了基于WiFi技术的智能控制机器人系统的硬件和软件设计。实验结果表明,本次设计的智能搜救机器人能有效实现灾后现场的远程移动监控和救援,具有一定的可靠性和实用性。     

A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks

Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high‐profile organizations and can potentially have high economic and time costs. In this paper, several machine learning methods including ensemble models and autoencoder‐based deep learning classifiers are compared and tuned using Bayesian optimization. The autoencoder framework enables to extract new features by mapping the original input to a new space. The methods are trained and tested both for binary and multi‐class classification on Digiturk and Labris datasets, which were introduced recently for detecting various types of DDoS attacks. The best performing methods are found to be ensembles though deep learning classifiers achieved comparable level of accuracy.     

A lightweight authentication scheme based on self‐updating strategy for space information network

The security of space information network (SIN) is getting more and more important now. Because of the special features of SIN (e.g., the dynamic and unstable topology, the highly exposed links, the restricted computation power, the flexible networking methods, and so on), the security protocol for SIN should have a balance between security properties and computation/storage overhead. Although a lot of security protocols have been proposed recently, few can provide overall attacks resistance power with low computation and storage cost. To solve this problem, in this paper we propose a lightweight authentication scheme for space information network. It is mainly based on the self‐updating strategy for user's temporary identity. The scheme consists of two phases, namely, the registration phase and the authentication phase. All the computing operations involved are just hash function (h), the bit‐wise exclusive‐or operation (⊕), and the string concatenation operation (||), which are of low computation cost. The security properties discussion and the attacks–resistance power analysis show that the proposed authentication scheme can defend against various typical attacks, especially denial of service attacks. It is sufficiently secure with the lowest computation and storage costs. Furthermore, the formal security proof in SVO logic also demonstrates that the scheme can satisfy the security goals very well. Copyright © 2016 John Wiley & Sons, Ltd.     

SERVQUAL模型在医疗行业的应用设计研究

本文探讨了感知服务评价模型-SERvQuAL模型在医疗行业的适用性,结合医疗服务特点,建立了以沟通性为前导变量的SERVQUAL的医疗感知服务质世理论模型.     

位置业务技术研究及部署规划探讨

位置业务被誉为继短消息之后移动通信领域的又一杀手锏.为适应发展形势的需要,文中从多方面对不同类型的位置业务进行说明,然后给出位置业务平台实施方案,重点就现网部署及异地定位等关键问题进行探讨,最后给出了实际部署规划过程中的性能需求,所得结果具有理论意义及实用参考价值.     

基于Web Services数据抽取的研究与实践

通过对Web Services技术和数据抽取的研究,提出了基于Web Services技术的数据抽取解决方案。重点介绍了增量数据自动化产生方法,提出了基于Web Services技术的解决方案,该方案是建立在数据端到端安全传输规范和并行数据抽取的基础之上,通过使用简单的标准适配器和接口,来完成粗粒度数据交换服务和高效的数据传输,能够满足大型异构企业环境的数据交换需求。基于Web Services技术的数据抽取提高了数据抽取的安全性和执行效率,使企业数据交换更加方便、灵活、可靠,伸缩性也更强。