Analyzing Service Rates for File Transfers in Peer-to-peer File Sharing Systems

When examining the file transfer performance in a peer-to-peer file sharing system, a fundamental problem is how to describe the service rate for a file transfer. In this paper, the problem is examined by analyzing the distribution of server-like nodes' upstream-bandwidth among their concurrent transfers. A sufficient condition for the service rate, what a receiver obtains for downloading a file, to asymptotically be uniform is presented. On the aggregate service rate for transferring a file in a system, a sufficient condition for it to asymptotically follow a Zipf distribution is presented. These asymptotic equalities are both in the mean square sense. These analyses and the sufficient conditions provide a mathematic base for modeling file transfer processes in peer-to-peer file sharing systems.

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological structures.MRI is particularly effective for detecting soft tissue anomalies.Traditionally,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of data.To address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI scans.This manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning methods.There are three stages for learning;in the first stage,the whole dataset is used to learn the features.In the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented dataset.This method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for analysis.Various hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning process.HWBA-dataset registers maximum classification performance.We evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

Transfer RNA-derived small RNA serves as potential non-invasive diagnostic marker and a novel therapeutic target for acute pancreatitis

Transfer RNA(tRNA)-derived fragments,a new type of tRNA-derived small RNA(tsRNA),can be cleaved from tRNA by enzymes to regulate target gene expression at the transcriptional and translational levels.tsRNAs are not only degradation fragments but also have biological functions,including those in immune inflammation,metabolic disorders,and cell death.tsRNA dysregulation is closely associated with multiple diseases,including various cancers and acute pancreatitis(AP).AP is a common gastrointestinal disease,and its incidence increases annually.AP development is associated with tsRNAs,which regulate cell injury and induce inflammation,especially pyroptosis and ferroptosis.Notably,serum tRF36 has the potential to serve as a non-invasive diagnostic biomarker and leads to pancreatic acinar cell ferroptosis causing inflammation to promote AP.We show the characteristics of tsRNAs and their diagnostic value and function in AP,and discuss the potential opportunities and challenges of using tsRNAs in clinical applications and research.

Brachioradialis tendon transfer and palmaris longus tendon graft for thumb avulsion:A case report and review of literature

BACKGROUND Thumb replantation following complete traumatic avulsion requires complex techniques to restore function,especially in cases of avulsion at the level of the metacarpophalangeal joint(MCP I)and avulsion of the flexor pollicis longus(FPL)at the musculotendinous junction.Possible treatments include direct tendon suture or tendon transfer,most commonly from the ring finger.To optimize function and avoid donor finger complications,we performed thumb replantation with flexion restoration using brachioradialis(BR)tendon transfer with palmaris longus(PL)tendon graft.CASE SUMMARY A 20-year-old left-handed male was admitted for a complete traumatic left thumb amputation following an accident while sliding from the top of a handrail.The patient presented with skin and bone avulsion at the MCP I,avulsion of the FPL tendon at the musculotendinous junction(zone 5),avulsion of the extensor pollicis longus tendon(zone T3),and avulsion of the thumb’s collateral arteries and nerves.The patient was treated with two stage thumb repair.The first intervention consisted of thumb replantation with MCP I arthrodesis,resection of avulsed FPL tendon and implantation of a silicone tendon prosthesis.The second intervention consisted of PL tendon graft and BR tendon transfer.Follow-up at 10 months showed good outcomes with active interphalangeal flexion of 70°,grip strength of 45 kg,key pinch strength of 15 kg and two-point discrimination threshold of 4 mm.CONCLUSION Flexion restoration after complete thumb amputation with FPL avulsion at the musculotendinous junction can be achieved using BR tendon transfer with PL tendon graft.

PeerIS:基于Peer-to-Peer的信息检索系统

介绍了对等计算(peer-to-peer,简称 P2P)的特征、潜在优势和应用范围,指出了当前 P2P 数据共享系统(甚至缺乏语义)和粗粒度(文件水平)共享等局限性.针对这种现状,提出了基于 P2P 的信息检索,既可充分发掘 P2P 技术的潜在优势,克服传统信息检索系统的可伸缩瓶颈等问题,又可实现 P2P 数据共享系统语义丰富和细粒度的信息检索与共享;并开发出 PeerIS:基于 P2P 的信息检索系统.描述了 PeerIS 的整体构架与节点的内部结构;重点阐述了 PeerIS 的通信机制、自配置机制、查询机制以及自适应路由机制等实现关键技术;并用实验证明了 PeerIS 的优异性.

应用于移动互联网的Peer-to-Peer关键技术

对现有的应用于移动互联网的P2P技术方面的研究进行了分析.首先介绍了P2P技术和移动互联网的概念,并提出将P2P技术应用在移动互联网所面临的挑战和应用模式.其次,分别针对集中式架构、超级节点体系架构和ad hoc架构对应用于互联网的P2P网络体系架构进行了阐述.再其次,针对移动终端的两种接入模式,分别在资源定位算法和跨层优化两个方面进行了介绍.对各关键技术的特点进行了详细的分析,指出其存在的不足.最后,对未来的工作进行了展望.

基于贝叶斯网络的Peer-to-Peer识别方法

网络业务分类与识别是网络管理、网络规划和安全的必要途径,而Peer-to-Peer(P2P)流量由于采用伪装端口、动态端口以及应用层加密,已成为业务分类与识别的主要难点.该文提出了P2P业务的精确识别方法,通过对流统计特性的分析,提取相关特征属性,应用遗传算法选取最优特征属性子集,并采用贝叶斯网络机器学习方法识别P2P流量.实验表明K2,TAN和BAN能有效快速地识别P2P业务,分类精度高达95%以上,很大程度上优于朴素贝叶斯分类和BP神经网络方法.同时该系统具有可扩展性,能够识别未知的P2P流量,并适用于实时分类识别环境.

分布式Peer-to-Peer网络Gnutella模型研究

计算机对等联网(peer-to-peernetwork,P2P)技术是目前新一代网络技术研究的活跃领域,而P2P网络模型研究是P2P网络技术研究的重要环节。该文着重介绍了Gnutella网络模型的体系结构及工作原理,分析了其优缺点。并对其未来发展改进前景进行了展望。

Internet中Peer-to-Peer应用流量测量与分析

Peer to Peer网络(简称p2p)作为一种新型的覆盖网络引起了越来越多研究者的兴趣。本文介绍了在我国进行的骨干互联网上p2p网络流量测量。与现有国外研究不同,本文的数据来源于核心路由器,因此克服了它们的缺陷。其研究集中在汇聚流中的3个周期性尖峰群、不同主机发送或接收流量的重尾分布、p2p流量的长相关特性以及提出了ADTE的估计方法来区分信令和数据流量。本文的研究也显示出Napster在p2p流中占大部分,这暗示着超级节点和阶层式拓扑较纯p2p结构潜在的优势。同时,观察到在我国p2p的流量仅占Internet总流量的1%弱,这个值跟国外的数据有很大区别。我们分析了其中的原因并希望该结论为我国p2p软件的发展提供参考。

主动peer-to-peer网络架构

针对当前peer-to-peer(P2P)网络只能通过固定的协议和服务有限地利用节点资源的弱点提出了主动P2P网络(APN)架构.结合P2P网络技术和主动网络技术,核心思想是把P2P网络的服务和协议代码封装在数据包中,随着数据包一起传送,并由需要的节点加载和执行,由此完成服务和协议的动态扩充和部署.通过在APN上部署自动代码理解和查询系统,验证了APN比现有P2P网络更能充分利用节点资源,更灵活,易于管理,同时,APN在安全性和性能方面的相对降低是可接受的.

基于Peer-to-Peer的单点登录服务研究和实现

使用Peer-to-Peer模型设计了一种新的单点登录服务模型,并在国家科技基础条件平台门户应用系统的身份认证系统中实际应用。该方案(NPSSO)把身份认证分配到多个身份认证服务器上,每个身份认证服务器均由一个单独的管理系统来管理,能够大大提高容错和抗攻击能力,并且能保证系统在用户和服务的数量上具有良好的可扩展性。最后,对该套单点登录方案进行了性能分析和相关工作的比较。

基于遗传算法的Peer-to-Peer路由算法R-GA

路由算法是制约Peer-to-Peer系统整体性能的关键因素之一。目前大多数路由算法无法保证全局收敛,而链路延迟、费用、网络带宽等现实制约因素往往在选路时被忽略。针对上述问题,提出了基于遗传算法的R-GA路由算法。通过适度函数和遗传因子,R-GA可以快速地实现全局收敛。同时将链路的延迟、费用、带宽等参数插入到适度函数中,避免了盲目路由。仿真试验的结果表明,R-GA路由算法在大规模Peer-to-Peer系统中是高效和可扩展的。

一种基于Peer-to-Peer的分布式文件共享框架

主要探讨了在基于非集中式Peer to Peer网络中实现分布式文件共享和传输管理需要考虑的主要因素，给出了基于Gnutella框架的改进之处以及实现细节，并提出了以通信自相似性和拓扑幂律分布相结合的特性模型。

基于分布式聚类的Peer-to-Peer路由算法

提出了分布式聚类算法,该算法自动对地理邻近的对等结点聚类,消除了集中式聚类算法的单点瓶颈问题,及分布式Binning算法的landmark放置问题;提出了一种基于该聚类的邻居路由算法,该算法消除了na?ve算法路由效率低、IP-snoop算法实现困难及处理开销大、directed算法需要处理超级节点失效时容错问题。实验结果表明,基于分布式聚类的Peer-to-Peer(P2P)路由算法比现有的结构化路由算法减少了近一倍的路由跳转和路由时延。

Peer-to-Peer网络中文件查询的研究

随着P2P网络应用研究的热化,文件查询即给出文件名后如何确定文件的存放位置,已经成为大规模分布式网络中最常遇到的问题之一。文件查询的效率直接影响到整个P2P网络的性能。本文从P2P网络的基本现状出发,给出了目前文件查询在非结构化,结构化和松散结构化P2P网络中的解决方案并进行了深入分析和比较。文章最后指出了目前P2P网络中文件查询算法的缺点和今后的研究方向。

基于Region的多层结构Peer-to-Peer网络模型与搜索算法研究

以小世界模型为理论基础,以 Region 为基本逻辑管理单位,按用户需求和共享目的组织 Region。提出了基于 Region 的多层结构 Peer-to-Peer 网络模型和构造规则,给出了 Region 的划分策略和数学模型,证明了模型的正确和合理性;对模型中的层和域、中心节点、普通节点和汇聚点进行了明确的定义,给出了节点加入、离开、中心节点选取策略和算法描述;使定位某种服务的工作量和查询范围从网络中的所有结点数降低到 Region 的节点数,有效地防止了恶意请求引发的洪,网络系统开销为常数。模拟分析表明,该模型可有效解决可扩展性、性能与效率不高问题,且网络规模越大,其综合性能的优越性越明显,因此,模型是合理有效的。

基于双层ID空间的Peer-to-Peer文件系统设计与实现

提出并实现了一种建立在Peer-to-Peer 搜索策略上的自组织、自适应、高效和可靠的文件系统DISPFS(Double ID Space basedPeer-to-peer File System)。它在双层ID 空间中构造虚拟存储节点,不仅有效地取得了文件系统内的负载均衡、提高系统利用率,而且保证了动态环境中文件的可靠、快速获取。试验数据表明,DISPFS 在系统接近满负荷运行和文件插入/删除操作频繁的双重压力下依然保持优良的性能。

Peer-to-Peer流媒体系统中容错机制的研究

基于分片策略和擦除纠错码技术的使用 ,提出和分析了一种面向P2P流媒体系统的新型容错机制 .通过马尔可夫链模型来模拟系统的可靠性 ,可以得出系统冗余开销与可靠的系统规模之间的关系 .结果表明 :在Honeycomb系统有 2 0 0个节点的情况下 (即使是在单个节点很不可靠的情况下 ) ,只需要 15 .5

Accelerated transmission in peer-to-peer network

The design and evaluation of accelerated transmission （AT） systems in peer-to-peer networks for data transmission are introduced. Based on transfer control protocol （TCP） and peer-to-peer （P2P） substrate networks, AT can select peers of high performance quality, monitor the transfer status of each peer, dynamically adjust the transmission velocity and react to connection degradation with high accuracy and low overhead. The system performance is evaluated by simulations, and the interrelationship between network flow, bandwidth utilities and network throughput is analyzed. Owing to the collaborative operation of neighboring peers, AT accelerates the process of data transmission and the collective network performance is much more satisfactory.

蜂窝网中使用Peer-to-Peer的网络模型

近年来,改善网络模型、提高网络性能逐渐受到人们的关注,在AdHoc无线网络中开始使用peer-to-peer网络模型来增加数据传输率,降低传输功率,增加网络容量和更好的负载平衡。然而,网络拓扑计算、路由选择、能量供应成为了瓶颈。在本文中,我们提供了一种混合的网络模型,既可以有效地节省能量,还可以很好的避免大量的路由搜索和计算,很好的解决负载平衡问题。同时,能够更好的和现有蜂窝网络融合,做到用户的平滑过渡。