基于Internet的机器人遥操作系统QoS策略与同步问题研究

基于Internet的机器人遥操作系统提供了进行网络控制系统(NCS和多媒体通信等学科交叉领域研究的良好平台和契机。服务质量(QoS)的概念起源于多媒体和远程通信领域，大量的文献表明，将NCS和QOS结合起来的研究和应用还很少。本文分析、研究了基于Internet的机器人遥操作系统作为NCS, Internet上的多媒体应用和实时系统等多学科的交叉领域所具有的特点，对该系统同步和协调问题及具有QOS意识的网络机器人遥操作系统体系结构进行了深入、广泛的研究和探讨。就现有的基于Internet的机器人遥操作系统存在的缺乏对网络可用带宽的适应、缺乏多数据流协调等问题，提出了一种针对网络机器人遥操作系统的端到端QOS自适应体系结构AeQTA o在Internet QoS整体工程尚未完全启动的情况下，AeQTA的目的是将QOS的方法和策略尽量移植到端系统上，在端系统上提供QOS配置接口，实施QOS驱动的控制和管理策略，实现最大的网络效率、最可能好的应用性能和合理的业务流间资源分配的和谐统一。从时钟同步、速率控制、拥塞控制、多传感器信息同步和端到端的调度等几个方面剖析了基于Internet的机器人遥操作系统的协调和同步问题。针对NC S系统的同步容限的量化问题，提出了NCS多传感器反馈中的同步距离的概念和定义。然后，根据基于公式的、TCP－友好的速率控制的基本思路，结合使用应用需求QOS和网络QOS两种尺度调节的基于主媒体流的表象同步方法，将多传感器信息同步和速率控制统一起来，提出了一种速率控制方法TTFRC，提高了系统的实时性和TCP－友好性。为了给基于Internet的机器人遥操作系统研究提供一个真实的实验环境，为相关的策略和算法提供验证平台，我们建立了一个开放的、灵活的、可移植的、可裁减的且成本低的MOMR原型系统。目前，该原型系统已经为基于Internet的机器人遥操作系统深入的理论研究和实际经验积累做出了很大贡献。并且，在此基础上，由中国科学院沈阳自动化研究所和香港中文大学合作，己于2402年1月通过Internet实现了沈阳—香港—密西根三地的MONM远程协作。力求控制工程和计算机网络工程等多学科的结合是本论文工作的努力方向。

基于以太网技术的ARCNET数据采集系统设计

为了解决ARCNET网络与以太网不兼容的问题,针对目前ARCNET网络设备监控管理系统存在的缺陷,提出了一种基于嵌入式TCP/IP协议的ARCNET数据采集与传输系统。分析了该数据采集系统的原理与结构,给出了系统的硬件设计方案,完成了数据采集与传输的软件结构设计和嵌入式TCP/IP协议栈的建立。对系统的实时性、可靠性和应用效果等进行了测试,结果证明,系统使用方便,性能稳定,具有良好的实时性和可靠性,综合性能优于现有的ARCNET数据采集系统。

An application of a multiple agent system for flexible assemble tasks

C.H. Orgill, N.W. Hardy, M.H. Lee, and K.A.I. Sharpe. An application of a multiple agent system for flexible assemble tasks. In Knowledge based envirnments for industrial applications including cooperating expert systems in control. IEE London, 1989.

On the Efficiency and Fairness of Transmission Control Loops: A Case for Exogenous Losses

We postulate that exogenous losses-which are typically regarded as introducing undesirable "noise" that needs to be filtered out or hidden from end points-can be surprisingly beneficial. In this paper we evaluate the effects of exogenous losses on transmission control loops, focusing primarily on efficiency and convergence to fairness properties. By analytically capturing the effects of exogenous losses, we are able to characterize the transient behavior of TCP. Our numerical results suggest that "noise" resulting from exogenous losses should not be filtered out blindly, and that a careful examination of the parameter space leads to better strategies regarding the treatment of exogenous losses inside the network. Specifically, we show that while low levels of exogenous losses do help connections converge to their fair share, higher levels of losses lead to inefficient network utilization. We draw the line between these two cases by determining whether or not it is advantageous to hide, or more interestingly introduce, exogenous losses. Our proposed approach is based on classifying the effects of exogenous losses into long-term and short-term effects. Such classification informs the extent to which we control exogenous losses, so as to operate in an efficient and fair region. We validate our results through simulations.

Exogenous-Loss Awareness in Queue Management: Toward Global Fairness

For a given TCP flow, exogenous losses are those occurring on links other than the flow's bottleneck link. Exogenous losses are typically viewed as introducing undesirable "noise" into TCP's feedback control loop, leading to inefficient network utilization and potentially severe global unfairness. This has prompted much research on mechanisms for hiding such losses from end-points. In this paper, we show through analysis and simulations that low levels of exogenous losses are surprisingly beneficial in that they improve stability and convergence, without sacrificing efficiency. Based on this, we argue that exogenous loss awareness should be taken into account in any AQM design that aims to achieve global fairness. To that end, we propose an exogenous-loss aware Queue Management (XQM) that actively accounts for and leverages exogenous losses. We use an equation based approach to derive the quiescent loss rate for a connection based on the connection's profile and its global fair share. In contrast to other queue management techniques, XQM ensures that a connection sees its quiescent loss rate, not only by complementing already existing exogenous losses, but also by actively hiding exogenous losses, if necessary, to achieve global fairness. We establish the advantages of exogenous-loss awareness using extensive simulations in which, we contrast the performance of XQM to that of a host of traditional exogenous-loss unaware AQM techniques.

Efficiently and Fairly Allocating Bandwidth at a Highly Congested Link

We consider the problem of efficiently and fairly allocating bandwidth at a highly congested link to a diverse set of flows, including TCP flows with various Round Trip Times (RTT), non-TCP-friendly flows such as Constant-Bit-Rate (CBR) applications using UDP, misbehaving, or malicious flows. Though simple, a FIFO queue management is vulnerable. Fair Queueing (FQ) can guarantee max-min fairness but fails at efficiency. RED-PD exploits the history of RED's actions in preferentially dropping packets from higher-rate flows. Thus, RED-PD attempts to achieve fairness at low cost. By relying on RED's actions, RED-PD turns out not to be effective in dealing with non-adaptive flows in settings with a highly heterogeneous mix of flows. In this paper, we propose a new approach we call RED-NB (RED with No Bias). RED-NB does not rely on RED's actions. Rather it explicitly maintains its own history for the few high-rate flows. RED-NB then adaptively adjusts flow dropping probabilities to achieve max-min fairness. In addition, RED-NB helps RED itself at very high loads by tuning RED's dropping behavior to the flow characteristics (restricted in this paper to RTTs) to eliminate its bias against long-RTT TCP flows while still taking advantage of RED's features at low loads. Through extensive simulations, we confirm the fairness of RED-NB and show that it outperforms RED, RED-PD, and CHOKe in all scenarios.

Exploiting the Transients of Adaptation for RoQ Attacks on Internet Resources

In this paper, we expose an unorthodox adversarial attack that exploits the transients of a system's adaptive behavior, as opposed to its limited steady-state capacity. We show that a well orchestrated attack could introduce significant inefficiencies that could potentially deprive a network element from much of its capacity, or significantly reduce its service quality, while evading detection by consuming an unsuspicious, small fraction of that element's hijacked capacity. This type of attack stands in sharp contrast to traditional brute-force, sustained high-rate DoS attacks, as well as recently proposed attacks that exploit specific protocol settings such as TCP timeouts. We exemplify what we term as Reduction of Quality (RoQ) attacks by exposing the vulnerabilities of common adaptation mechanisms. We develop control-theoretic models and associated metrics to quantify these vulnerabilities. We present numerical and simulation results, which we validate with observations from real Internet experiments. Our findings motivate the need for the development of adaptation mechanisms that are resilient to these new forms of attacks.

Real-Time Databases: Issues and Applications (RTDB'96 Workshop Report)

This report summarizes the technical presentations and discussions that took place during RTDB'96: the First International Workshop on Real-Time Databases, which was held on March 7 and 8, 1996 in Newport Beach, California. The main goals of this project were to (1) review recent advances in real-time database systems research, (2) to promote interaction among real-time database researchers and practitioners, and (3) to evaluate the maturity and directions of real-time database technology.

On the Relationship Between File Sizes, Transport Protocols, and Self-Similar Network Traffic

Recent measurements of local-area and wide-area traffic have shown that network traffic exhibits variability at a wide range of scales self-similarity. In this paper, we examine a mechanism that gives rise to self-similar network traffic and present some of its performance implications. The mechanism we study is the transfer of files or messages whose size is drawn from a heavy-tailed distribution. We examine its effects through detailed transport-level simulations of multiple TCP streams in an internetwork. First, we show that in a "realistic" client/server network environment i.e., one with bounded resources and coupling among traffic sources competing for resources the degree to which file sizes are heavy-tailed can directly determine the degree of traffic self-similarity at the link level. We show that this causal relationship is not significantly affected by changes in network resources (bottleneck bandwidth and buffer capacity), network topology, the influence of cross-traffic, or the distribution of interarrival times. Second, we show that properties of the transport layer play an important role in preserving and modulating this relationship. In particular, the reliable transmission and flow control mechanisms of TCP (Reno, Tahoe, or Vegas) serve to maintain the long-range dependency structure induced by heavy-tailed file size distributions. In contrast, if a non-flow-controlled and unreliable (UDP-based) transport protocol is used, the resulting traffic shows little self-similar characteristics: although still bursty at short time scales, it has little long-range dependence. If flow-controlled, unreliable transport is employed, the degree of traffic self-similarity is positively correlated with the degree of throttling at the source. Third, in exploring the relationship between file sizes, transport protocols, and self-similarity, we are also able to show some of the performance implications of self-similarity. We present data on the relationship between traffic self-similarity and network performance as captured by performance measures including packet loss rate, retransmission rate, and queueing delay. Increased self-similarity, as expected, results in degradation of performance. Queueing delay, in particular, exhibits a drastic increase with increasing self-similarity. Throughput-related measures such as packet loss and retransmission rate, however, increase only gradually with increasing traffic self-similarity as long as reliable, flow-controlled transport protocol is used.

Measuring the Behavior of a World-Wide Web Server

Server performance has become a crucial issue for improving the overall performance of the World-Wide Web. This paper describes Webmonitor, a tool for evaluating and understanding server performance, and presents new results for a realistic workload. Webmonitor measures activity and resource consumption, both within the kernel and in HTTP processes running in user space. Webmonitor is implemented using an efficient combination of sampling and event-driven techniques that exhibit low overhead. Our initial implementation is for the Apache World-Wide Web server running on the Linux operating system. We demonstrate the utility of Webmonitor by measuring and understanding the performance of a Pentium-based PC acting as a dedicated WWW server. Our workload uses a file size distribution with a heavy tail. This captures the fact that Web servers must concurrently handle some requests for large audio and video files, and a large number of requests for small documents, containing text or images. Our results show that in a Web server saturated by client requests, over 90% of the time spent handling HTTP requests is spent in the kernel. Furthermore, keeping TCP connections open, as required by TCP, causes a factor of 2-9 increase in the elapsed time required to service an HTTP request. Data gathered from Webmonitor provide insight into the causes of this performance penalty. Specifically, we observe a significant increase in resource consumption along three dimensions: the number of HTTP processes running at the same time, CPU utilization, and memory utilization. These results emphasize the important role of operating system and network protocol implementation in determining Web server performance.

On the Interaction Between an Operating System and Web Server

This paper examines how and why web server performance changes as the workload at the server varies. We measure the performance of a PC acting as a standalone web server, running Apache on top of Linux. We use two important tools to understand what aspects of software architecture and implementation determine performance at the server. The first is a tool that we developed, called WebMonitor, which measures activity and resource consumption, both in the operating system and in the web server. The second is the kernel profiling facility distributed as part of Linux. We vary the workload at the server along two important dimensions: the number of clients concurrently accessing the server, and the size of the documents stored on the server. Our results quantify and show how more clients and larger files stress the web server and operating system in different and surprising ways. Our results also show the importance of fixed costs (i.e., opening and closing TCP connections, and updating the server log) in determining web server performance.

Admission Control and Scheduling for High-Performance WWW Servers

In this paper we examine a number of admission control and scheduling protocols for high-performance web servers based on a 2-phase policy for serving HTTP requests. The first "registration" phase involves establishing the TCP connection for the HTTP request and parsing/interpreting its arguments, whereas the second "service" phase involves the service/transmission of data in response to the HTTP request. By introducing a delay between these two phases, we show that the performance of a web server could be potentially improved through the adoption of a number of scheduling policies that optimize the utilization of various system components (e.g. memory cache and I/O). In addition, to its premise for improving the performance of a single web server, the delineation between the registration and service phases of an HTTP request may be useful for load balancing purposes on clusters of web servers. We are investigating the use of such a mechanism as part of the Commonwealth testbed being developed at Boston University.

The War Between Mice and Elephants

Recent measurement based studies reveal that most of the Internet connections are short in terms of the amount of traffic they carry (mice), while a small fraction of the connections are carrying a large portion of the traffic (elephants). A careful study of the TCP protocol shows that without help from an Active Queue Management (AQM) policy, short connections tend to lose to long connections in their competition for bandwidth. This is because short connections do not gain detailed knowledge of the network state, and therefore they are doomed to be less competitive due to the conservative nature of the TCP congestion control algorithm. Inspired by the Differentiated Services (Diffserv) architecture, we propose to give preferential treatment to short connections inside the bottleneck queue, so that short connections experience less packet drop rate than long connections. This is done by employing the RIO (RED with In and Out) queue management policy which uses different drop functions for different classes of traffic. Our simulation results show that: (1) in a highly loaded network, preferential treatment is necessary to provide short TCP connections with better response time and fairness without hurting the performance of long TCP connections; (2) the proposed scheme still delivers packets in FIFO manner at each link, thus it maintains statistical multiplexing gain and does not misorder packets; (3) choosing a smaller default initial timeout value for TCP can help enhance the performance of short TCP flows, however not as effectively as our scheme and at the risk of congestion collapse; (4) in the worst case, our proposal works as well as a regular RED scheme, in terms of response time and goodput.

Inference and Labeling of Metric-Induced Network Topologies

The development and deployment of distributed network-aware applications and services over the Internet require the ability to compile and maintain a model of the underlying network resources with respect to (one or more) characteristic properties of interest. To be manageable, such models must be compact, and must enable a representation of properties along temporal, spatial, and measurement resolution dimensions. In this paper, we propose a general framework for the construction of such metric-induced models using end-to-end measurements. We instantiate our approach using one such property, packet loss rates, and present an analytical framework for the characterization of Internet loss topologies. From the perspective of a server the loss topology is a logical tree rooted at the server with clients at its leaves, in which edges represent lossy paths between a pair of internal network nodes. We show how end-to-end unicast packet probing techniques could b e used to (1) infer a loss topology and (2) identify the loss rates of links in an existing loss topology. Correct, efficient inference of loss topology information enables new techniques for aggregate congestion control, QoS admission control, connection scheduling and mirror site selection. We report on simulation, implementation, and Internet deployment results that show the effectiveness of our approach and its robustness in terms of its accuracy and convergence over a wide range of network conditions.

STAIR: Practical AIMD Multirate Congestion Control

Existing approaches for multirate multicast congestion control are either friendly to TCP only over large time scales or introduce unfortunate side effects, such as significant control traffic, wasted bandwidth, or the need for modifications to existing routers. We advocate a layered multicast approach in which steady-state receiver reception rates emulate the classical TCP sawtooth derived from additive-increase, multiplicative decrease (AIMD) principles. Our approach introduces the concept of dynamic stair layers to simulate various rates of additive increase for receivers with heterogeneous round-trip times (RTTs), facilitated by a minimal amount of IGMP control traffic. We employ a mix of cumulative and non-cumulative layering to minimize the amount of excess bandwidth consumed by receivers operating asynchronously behind a shared bottleneck. We integrate these techniques together into a congestion control scheme called STAIR which is amenable to those multicast applications which can make effective use of arbitrary and time-varying subscription levels.