31 resultados para wide gain bandwidth


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This report describes our attempt to add animation as another data type to be used on the World Wide Web. Our current network infrastructure, the Internet, is incapable of carrying video and audio streams for them to be used on the web for presentation purposes. In contrast, object-oriented animation proves to be efficient in terms of network resource requirements. We defined an animation model to support drawing-based and frame-based animation. We also extended the HyperText Markup Language in order to include this animation mode. BU-NCSA Mosanim, a modified version of the NCSA Mosaic for X(v2.5), is available to demonstrate the concept and potentials of animation in presentations an interactive game playing over the web.

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Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to self-similar network traffic. We present an explanation for traffic self-similarity by using a particular subset of wide area traffic: traffic due to the World Wide Web (WWW). Using an extensive set of traces of actual user executions of NCSA Mosaic, reflecting over half a million requests for WWW documents, we show evidence that WWW traffic is self-similar. Then we show that the self-similarity in such traffic can be explained based on the underlying distributions of WWW document sizes, the effects of caching and user preference in file transfer, the effect of user "think time", and the superimposition of many such transfers in a local area network. To do this we rely on empirically measured distributions both from our traces and from data independently collected at over thirty WWW sites.

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We propose the development of a world wide web image search engine that crawls the web collecting information about the images it finds, computes the appropriate image decompositions and indices, and stores this extracted information for searches based on image content. Indexing and searching images need not require solving the image understanding problem. Instead, the general approach should be to provide an arsenal of image decompositions and discriminants that can be precomputed for images. At search time, users can select a weighted subset of these decompositions to be used for computing image similarity measurements. While this approach avoids the search-time-dependent problem of labeling what is important in images, it still holds several important problems that require further research in the area of query by image content. We briefly explore some of these problems as they pertain to shape.

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The quality of available network connections can often have a large impact on the performance of distributed applications. For example, document transfer applications such as FTP, Gopher and the World Wide Web suffer increased response times as a result of network congestion. For these applications, the document transfer time is directly related to the available bandwidth of the connection. Available bandwidth depends on two things: 1) the underlying capacity of the path from client to server, which is limited by the bottleneck link; and 2) the amount of other traffic competing for links on the path. If measurements of these quantities were available to the application, the current utilization of connections could be calculated. Network utilization could then be used as a basis for selection from a set of alternative connections or servers, thus providing reduced response time. Such a dynamic server selection scheme would be especially important in a mobile computing environment in which the set of available servers is frequently changing. In order to provide these measurements at the application level, we introduce two tools: bprobe, which provides an estimate of the uncongested bandwidth of a path; and cprobe, which gives an estimate of the current congestion along a path. These two measures may be used in combination to provide the application with an estimate of available bandwidth between server and client thereby enabling application-level congestion avoidance. In this paper we discuss the design and implementation of our probe tools, specifically illustrating the techniques used to achieve accuracy and robustness. We present validation studies for both tools which demonstrate their reliability in the face of actual Internet conditions; and we give results of a survey of available bandwidth to a random set of WWW servers as a sample application of our probe technique. We conclude with descriptions of other applications of our measurement tools, several of which are currently under development.

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The exploding demand for services like the World Wide Web reflects the potential that is presented by globally distributed information systems. The number of WWW servers world-wide has doubled every 3 to 5 months since 1993, outstripping even the growth of the Internet. At each of these self-managed sites, the Common Gateway Interface (CGI) and Hypertext Transfer Protocol (HTTP) already constitute a rudimentary basis for contributing local resources to remote collaborations. However, the Web has serious deficiencies that make it unsuited for use as a true medium for metacomputing --- the process of bringing hardware, software, and expertise from many geographically dispersed sources to bear on large scale problems. These deficiencies are, paradoxically, the direct result of the very simple design principles that enabled its exponential growth. There are many symptoms of the problems exhibited by the Web: disk and network resources are consumed extravagantly; information search and discovery are difficult; protocols are aimed at data movement rather than task migration, and ignore the potential for distributing computation. However, all of these can be seen as aspects of a single problem: as a distributed system for metacomputing, the Web offers unpredictable performance and unreliable results. The goal of our project is to use the Web as a medium (within either the global Internet or an enterprise intranet) for metacomputing in a reliable way with performance guarantees. We attack this problem one four levels: (1) Resource Management Services: Globally distributed computing allows novel approaches to the old problems of performance guarantees and reliability. Our first set of ideas involve setting up a family of real-time resource management models organized by the Web Computing Framework with a standard Resource Management Interface (RMI), a Resource Registry, a Task Registry, and resource management protocols to allow resource needs and availability information be collected and disseminated so that a family of algorithms with varying computational precision and accuracy of representations can be chosen to meet realtime and reliability constraints. (2) Middleware Services: Complementary to techniques for allocating and scheduling available resources to serve application needs under realtime and reliability constraints, the second set of ideas aim at reduce communication latency, traffic congestion, server work load, etc. We develop customizable middleware services to exploit application characteristics in traffic analysis to drive new server/browser design strategies (e.g., exploit self-similarity of Web traffic), derive document access patterns via multiserver cooperation, and use them in speculative prefetching, document caching, and aggressive replication to reduce server load and bandwidth requirements. (3) Communication Infrastructure: Finally, to achieve any guarantee of quality of service or performance, one must get at the network layer that can provide the basic guarantees of bandwidth, latency, and reliability. Therefore, the third area is a set of new techniques in network service and protocol designs. (4) Object-Oriented Web Computing Framework A useful resource management system must deal with job priority, fault-tolerance, quality of service, complex resources such as ATM channels, probabilistic models, etc., and models must be tailored to represent the best tradeoff for a particular setting. This requires a family of models, organized within an object-oriented framework, because no one-size-fits-all approach is appropriate. This presents a software engineering challenge requiring integration of solutions at all levels: algorithms, models, protocols, and profiling and monitoring tools. The framework captures the abstract class interfaces of the collection of cooperating components, but allows the concretization of each component to be driven by the requirements of a specific approach and environment.

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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.

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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.

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World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Techniques like pre-fetching are likely to help users to personalize their needs, reducing their waiting times. However, pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Otherwise, pre-fetching will only waste bandwidth. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determining user's next move. One model uses Random Walk approximation and the other is based on Digital Signal Processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing.

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ImageRover is a search by image content navigation tool for the world wide web. To gather images expediently, the image collection subsystem utilizes a distributed fleet of WWW robots running on different computers. The image robots gather information about the images they find, computing the appropriate image decompositions and indices, and store this extracted information in vector form for searches based on image content. At search time, users can iteratively guide the search through the selection of relevant examples. Search performance is made efficient through the use of an approximate, optimized k-d tree algorithm. The system employs a novel relevance feedback algorithm that selects the distance metrics appropriate for a particular query.

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To support the diverse Quality of Service (QoS) requirements of real-time (e.g. audio/video) applications in integrated services networks, several routing algorithms that allow for the reservation of the needed bandwidth over a Virtual Circuit (VC) established on one of several candidate routes have been proposed. Traditionally, such routing is done using the least-loaded concept, and thus results in balancing the load across the set of candidate routes. In a recent study, we have established the inadequacy of this load balancing practice and proposed the use of load profiling as an alternative. Load profiling techniques allow the distribution of "available" bandwidth across a set of candidate routes to match the characteristics of incoming VC QoS requests. In this paper we thoroughly characterize the performance of VC routing using load profiling and contrast it to routing using load balancing and load packing. We do so both analytically and via extensive simulations of multi-class traffic routing in Virtual Path (VP) based networks. Our findings confirm that for routing guaranteed bandwidth flows in VP networks, load balancing is not desirable as it results in VP bandwidth fragmentation, which adversely affects the likelihood of accepting new VC requests. This fragmentation is more pronounced when the granularity of VC requests is large. Typically, this occurs when a common VC is established to carry the aggregate traffic flow of many high-bandwidth real-time sources. For VP-based networks, our simulation results show that our load-profiling VC routing scheme performs better or as well as the traditional load-balancing VC routing in terms of revenue under both skewed and uniform workloads. Furthermore, load-profiling routing improves routing fairness by proactively increasing the chances of admitting high-bandwidth connections.

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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.

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The increased diversity of Internet application requirements has spurred recent interests in transport protocols with flexible transmission controls. In window-based congestion control schemes, increase rules determine how to probe available bandwidth, whereas decrease rules determine how to back off when losses due to congestion are detected. The parameterization of these control rules is done so as to ensure that the resulting protocol is TCP-friendly in terms of the relationship between throughput and loss rate. In this paper, we define a new spectrum of window-based congestion control algorithms that are TCP-friendly as well as TCP-compatible under RED. Contrary to previous memory-less controls, our algorithms utilize history information in their control rules. Our proposed algorithms have two salient features: (1) They enable a wider region of TCP-friendliness, and thus more flexibility in trading off among smoothness, aggressiveness, and responsiveness; and (2) they ensure a faster convergence to fairness under a wide range of system conditions. We demonstrate analytically and through extensive ns simulations the steady-state and transient behaviors of several instances of this new spectrum of algorithms. In particular, SIMD is one instance in which the congestion window is increased super-linearly with time since the detection of the last loss. Compared to recently proposed TCP-friendly AIMD and binomial algorithms, we demonstrate the superiority of SIMD in: (1) adapting to sudden increases in available bandwidth, while maintaining competitive smoothness and responsiveness; and (2) rapidly converging to fairness and efficiency.

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Accurate measurement of network bandwidth is crucial for flexible Internet applications and protocols which actively manage and dynamically adapt to changing utilization of network resources. These applications must do so to perform tasks such as distributing and delivering high-bandwidth media, scheduling service requests and performing admission control. Extensive work has focused on two approaches to measuring bandwidth: measuring it hop-by-hop, and measuring it end-to-end along a path. Unfortunately, best-practice techniques for the former are inefficient and techniques for the latter are only able to observe bottlenecks visible at end-to-end scope. In this paper, we develop and simulate end-to-end probing methods which can measure bottleneck bandwidth along arbitrary, targeted subpaths of a path in the network, including subpaths shared by a set of flows. As another important contribution, we describe a number of practical applications which we foresee as standing to benefit from solutions to this problem, especially in emerging, flexible network architectures such as overlay networks, ad-hoc networks, peer-to-peer architectures and massively accessed content servers.

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The advent of virtualization and cloud computing technologies necessitates the development of effective mechanisms for the estimation and reservation of resources needed by content providers to deliver large numbers of video-on-demand (VOD) streams through the cloud. Unfortunately, capacity planning for the QoS-constrained delivery of a large number of VOD streams is inherently difficult as VBR encoding schemes exhibit significant bandwidth variability. In this paper, we present a novel resource management scheme to make such allocation decisions using a mixture of per-stream reservations and an aggregate reservation, shared across all streams to accommodate peak demands. The shared reservation provides capacity slack that enables statistical multiplexing of peak rates, while assuring analytically bounded frame-drop probabilities, which can be adjusted by trading off buffer space (and consequently delay) and bandwidth. Our two-tiered bandwidth allocation scheme enables the delivery of any set of streams with less bandwidth (or equivalently with higher link utilization) than state-of-the-art deterministic smoothing approaches. The algorithm underlying our proposed frame-work uses three per-stream parameters and is linear in the number of servers, making it particularly well suited for use in an on-line setting. We present results from extensive trace-driven simulations, which confirm the efficiency of our scheme especially for small buffer sizes and delay bounds, and which underscore the significant realizable bandwidth savings, typically yielding losses that are an order of magnitude or more below our analytically derived bounds.

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We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" – both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.