基于LTE下行多业务传输QoS保证的跨层调度算法

众多资源分配的调度算法中, 有区别地实现不同业务QoS要求的调度策略研究不多。针对此问题, 通过将不同QoS等级和要求加入到调度策略的影响因素中, 提出了一种适用于LTE下行多业务传输的多目标跨层分组调度算法, 并设计了一个用户满意度函数, 用来评价分组调度算法的综合性能。对该算法性能进行了仿真验证, 并同PF算法仿真结果进行比较与分析, 表明该算法能够满足不同业务的QoS要求, 综合性能优于PF算法。     

网络传输控制的综合性能评价标准

在网络传输控制策略和算法的设计中，性能评价的标准是一个关键问题，不同的评价标准将导致不同的控制策略和算法设计。由于网络传输控制策略有着多方面性能的要求，如何同时满足多个性能目标是当前的研究难点，该文基于网络传输控制模型提出了一套对网络传输控制进行综合性能评价的有效标准，该标准综合考虑了网络整体性能、用户QoS要求和系统公平性等多维目标，作者对该标准进行了详细的讨论和分析，文中的综合性能标准可以广泛用于网络传输控制策略的性能评价和改进。     

多性能目标分组调度策略

在高速分组交换网络中,分组调度策略和算法的设计是一个关键问题.由于网络分组调度策略有着多方面性能的要求,如何同时满足多个性能目标是当前的研究难点.基于比例公平性原则,提出了一种分组网络中的比例公平调度策略(proportional fairness scheduling,简称PFS),该调度策略综合考虑了网络效率、用户QoS要求和系统公平性等多维目标,对该策略进行了详细的分析和论证.比例公平调度策略可以广泛应用于分组网络调度策略的设计研究和改进.     

基于FAHP的网络性能综合评价的研究*

针对工业现场对有线/无线异构网络的性能要求,提出了一种基于模糊层次分析法( FAHP)的网络性能综合评价方法,着重分析了网络的综合性能指标参数的获取和利用FAHP算法确定各指标权重的过程。通过对不同业务和参数的多媒体仿真网络的性能评价验证算法的准确性,最后针对一个具体的有线/无线异构仿真网络进行评价,比较了不同用户要求下得到的网络性能综合评价值。实验结果表明,采用基于FAHP的网络性能评价算法对于工业异构网络的性能评价是准确有效的。     

基于模糊多目标决策的两跳中继蜂窝网络切换算法

简要介绍了在集成两跳Ad Hoc和蜂窝网络的结构下,触发网络进行切换的一些因素和两种路由代理发现算法,并且提出了一种新的基于模糊多目标决策方法的切换决定算法。算法从层次分析和模糊综合评价理论的思想出发,结合用户、终端、业务和网络信息,对网络链路的性能进行综合评价,选择出最适合用户业务请求的路径。仿真显示在用户可感知业务QoS下降的情况下,算法可以通过增加QoS的权重而切换到更好的网络链路上,从而为用户提供了“总是最好连接”的服务。     

基于改进蚁群算法的多约束QoS路由方法

高速多媒体网络路由问题是一个多QoS约束的NP一完全问题,提出一种改进蚁群路由算法对该问题进行求解。该算法采取了带记忆的后继节点选择方式,利用蚂蚁已走过的路径启发后继节点的选取;引入了基于目标函数的信息素更新机制,依据目标函数评价蚂蚁路径搜索行为,并根据蚂蚁的表现采取不同的信息素更新策略,提高了算法的寻优能力和收敛速度。仿真实验表明,该算法能快速得到较大程度满足业务QoS要求的路径。     

DiffServ/MPLS网络中最小化抢占的路由算法

在支持具有不同优先级和不同QoS需求的多业务网络中,抢占是带宽分配和管理的有效策略,但同时也对网络造成了振荡。在路径选择策略中引入抢占信息可最小化重路由,提高网络的稳定性。论文给出了最小化抢占的路由问题的数学规划模型。在此基础上提出了简单的启发式算法以运用于大型实际网络。策略是将路径选择和连接建立过程有效地结合起来,对现有的MPLS信令协议仅做了少许扩展。仿真证明该算法能达到抢占最小化的优化目标,有效地提高网络性能。     

基于Dijkstra策略的QoS路由多目标算法

对网络拓扑结构和QoS路由指标进行了形式化分析，提出了一种QoS路由数学模型．通过建立QoS路由综合评价指标，基于Dijkstra策略，给出了一种QoS路由多目标算法(Multi—object QOS Routing Algorithm Based on Dijk—stra Strategy：MOQRAD)．仿真研究表明该算法在满足业务连接QoS需求的同时，网络负载分布均衡，提高了网络的吞吐量，较好地改善了网络的性能．     

满足QoS约束的自适应Ad Hoc网络路由算法

自组网是由一组带有无线收发装置移动节点组成的一个能够支持多跳的临时性计算机通信网络,其拓扑的动态变化是该类网络的一个重要特征,文章提出了一种满足QoS约束的自适应路由算法,将业务的多个QoS参数进行综合评判,对比各条路径综合路由状态,选择出最适合业务请求的路径。仿真显示该算法在支持QoS的同时,对移动Ad Hoc网络因拓扑动态变化而引起的信息不精确性有很好的适应度。     

面向业务流设计的TPRAR算法研究

通过对网络业务进行分析来达到对网络性能进行评价和优化变得日益重要.提出了一种新的基于业务流分析方法,采用关联规则挖掘的算法对全网业务进行关联关系分析.该方法在Apriori算法的基础上,引入时态约束和路径约束,使之更加体现网络业务的特性.使用该方法,可以充分利用已有数据,分析已有业务的行为,且可以预测未来业务的行为.并指出该分析方法是以业务为分析单位的,运用该方法可以从业务角度对网络状况和网络行为进行分析.     

Web集群服务器的分离式调度策略

主要用排队论方法讨论了Web集群整体性能与请求调度策略之间的关系，所获得的结论是：在Web集群非过载情况下，一部分后端服务器仅处理静态请求而另一部分后端服务器仅处理动态请求的分离式调度策略要好于所有后端服务器既处理静态请求又处理动态请求的混合式调度策略。用SPECweb99测试工具所做的实际测试更进一步证明：当负载参数为120个连接时，采用分离式调度策略的Web集群服务器可完成63个连接，而采用混合式调度策略的Web集群服务器仅能完成36个连接，性能提高了22.5%。     

Web-log mining for predictive Web caching

Caching is a well-known strategy for improving the performance of Web-based systems. The heart of a caching system is its page replacement policy, which selects the pages to be replaced in a cache when a request arrives. In this paper, we present a Web-log mining method for caching Web objects and use this algorithm to enhance the performance of Web caching systems. In our approach, we develop an n-gram-based prediction algorithm that can predict future Web requests. The prediction model is then used to extend the well-known GDSF caching policy. We empirically show that the system performance is improved using the predictive-caching approach.     

Replica Placement and Access Policies in Tree Networks

In this paper, we discuss and compare several policies to place replicas in tree networks, subject to server capacity and Quality of Service (QoS) constraints. The client requests are known beforehand, while the number and location of the servers are to be determined. The standard approach in the literature is to enforce that all requests of a client be served by the closest server in the tree. We introduce and study two new policies. In the first policy, all requests from a given client are still processed by the same server, but this server can be located anywhere in the path from the client to the root. In the second policy, the requests of a given client can be processed by multiple servers. One major contribution of this paper is to assess the impact of these new policies on the total replication cost. Another important goal is to assess the impact of server heterogeneity. In this paper, we establish several new complexity results, and provide several efficient polynomial heuristics for NP-complete instances of the problem. The absolute performance of these heuristics is assessed by comparison with the optimal solution provided by the formulation of the problem in terms of the solution of an integer linear program.     

Storage System for Supporting More Video Streams in Video Server

Video server needs a storage system with large bandwidth in order to provide concurrently more users with the real time retrieval requests for video streams. So, the storage system generally has the structure of disk array, which consists of multiple disks. When the storage system serves multiple video stream requests, it's bottlenecks come from the seeking delay caused by the random movement of disk head and from unbalanced disk access due to disk load unbalance among multiple disks.This paper presents a novel placement and retrieval policy. The new policy retrieves the requested data through sequential movement of disk heads and maintaining disk load balance so that it can diminish the bottlenecks on retrieving and can provide the concurrent real time retrieval services for more users simultaneously. In addition, the novel policy reduces the startup latency for the requests. The correctness of the novel placement and retrieval policy is analyzed with theoretical views. Performance analysis of the novel placement and retrieval policy is provided with simulations.     

Towards high performance security policy evaluation

The Enterprise Privacy Authorization Language (EPAL) is a formal language for specifying fine-grained enterprise privacy policies. With the adoption of EPAL, especially in web applications, the performance of EPAL policy evaluation engines becomes a critical issue. In this paper, we propose Eengine, an engine for efficient EPAL policy evaluation. Eengine first converts all string values in an EPAL policy to numerical values. Second, it converts a numericalized EPAL policy specified as a list of rules following the first-match semantics to a tree structure for efficient processing of numericalized requests.     

Resolution and parameters estimations for multiple maneuvering targets

Resolution and parameters estimations for multiple maneuvering targets in the same range cell is addressed in this work. The low-resolution radar cannot distinguish multiple targets in both distance and angle, but the detection of Doppler frequency variation of the multiple maneuvering targets can be used to resolve this problem. At present, most of researches on detection of Doppler frequency variation are carried out with time-frequency analysis methods, such as Fractional Fourier transformation （FRFT）, Adaptive Chirplet transformation （ACT）, and Wigner-Ville distribution （WVD） and so on, which need satisfy enough time duration and sampling theorem. This paper proposes a new method of resolution and parameters estimation for multiple maneuvering targets based on Compressive Sensing （CS） and clustering technique, which samples at low rate and short time duration without sacrificing estimation performance. Simulation results validate the effectiveness of the proposed algorithm, and also show that the performance of the proposed method is superior to that of FRFT in the condition of multiple targets.     

Dynamic batching policies for an on-demand video server

In a video-on-demand environment, continuous delivery of video streams to the clients is guaranteed by sufficient reserved network and server resources. This leads to a hard limit on the number of streams that a video server can deliver. Multiple client requests for the same video can be served with a single disk I/O stream by sending (multicasting) the same data blocks to multiple clients (with the multicast facility, if present in the system). This is achieved by batching (grouping) requests for the same video that arrive within a short time. We explore the role of customer-waiting time and reneging behavior in selecting the video to be multicast. We show that a first come, first served (FCFS) policy that schedules the video with the longest outstanding request can perform better than the maximum queue length (MQL) policy that chooses the video with the maximum number of outstanding requests. Additionally, multicasting is better exploited by scheduling playback of the most popular videos at predetermined, regular intervals (hence, termed FCFS-). If user reneging can be reduced by guaranteeing that a maximum waiting time will not be exceeded, then performance of FCFS- is further improved by selecting the regular playback intervals as this maximum waiting time. For an empirical workload, we demonstrate a substantial reduction (of the order of 60%) in the required server capacity by batching.     

Pinpointing and scheduling access conflicts to improve internal resource utilization in solid-state drives

Modern solid-state drives (SSDs) are integrating more internal resources to achieve higher capacity. Parallelizing accesses across internal resources can potentially enhance the performance of SSDs. However, exploiting parallelism inside SSDs is challenging owing to real-time access conflicts. In this paper, we propose a highly parallelizable I/O scheduler (PIOS) to improve internal resource utilization in SSDs from the perspective of I/O scheduling. Specifically, we first pinpoint the conflicting flash requests with precision during the address translation in the Flash Translation Layer (FTL). Then, we introduce conflict eliminated requests (CERs) to reorganize the I/O requests in the device-level queue by dispatching conflicting flash requests to different CERs. Owing to the significant performance discrepancy between flash read and write operations, PIOS employs differentiated scheduling schemes for read and write CER queues to always allocate internal resources to the conflicting CERs that are more valuable. The small dominant size prioritized scheduling policy for the write queue significantly decreases the average write latency. The high parallelism density prioritized scheduling policy for the read queue better utilizes resources by exploiting internal parallelism aggressively. Our evaluation results show that the parallelizable I/O scheduler (PIOS) can accomplish better SSD performance than existing I/O schedulers implemented in both SSD devices and operating systems.     

Multi-bank闪存文件系统的一种I/O调度机制

闪存以其体积小、抗震性强、能耗低、读取速度快等特点,被广泛应用于存储系统中。NOOP是闪存上传统的调度方法,但是NOOP的I/O性能较低,不能满足很多应用程序的要求。根据闪存读取速度快、多个banks(chips)可以并行运行等特点,提出了一种基于闪存文件系统YAFFS的Multi-bank闪存调度方法(简称MBS)。MBS并行地执行请求,且给予读请求更高的优先级。MBS根据AVL-based-tree机制识别出的写请求属性动态地将其分配到合适的bank中。实验结果表明,相比NOOP,MBS调度具有更高的I/O吞吐率、更短的请求响应时间并具有均匀的bank擦除次数和利用率。     

基于证据推理的多指标评价系统设计与实现

针对具有不确定性的混合多指标评价问题,介绍了定性指标和定量指标的数据提取方法,结合证据推理法的基本理论,采用混合编程技术,开发了证据推理评价系统。系统设计了指标体系管理、数据管理、评价分析三大模块,实现了定性指标与定量指标相结合的多指标综合评价。最后,以船舶保障性为示例验证了系统具有稳定性和实用性,该系统能够多角度分析评价结果,为决策者提供辅助决策。