5913277
OceanStore: an architecture for global-scale persistent storage
OceanStore is a utility infrastructure designed to span the globe and provide continuous access to persistent information. Since this infrastructure is comprised of untrusted servers, data is protected through redundancy and cryptographic techniques. To improve performance, data is allowed to be cached anywhere, anytime. Additionally, monitoring of usage patterns allows adaptation to regional outages and denial of service attacks; monitoring also enhances performance through pro-active movement of data. A prototype implementation is currently under development.
887532
A Suite of Schemes for User-Level Network Diagnosis without Infrastructure
It is highly desirable and important for end users, with no special privileges, identify and pinpoint faults inside the network that degrade the performance of their applications. However, existing tools are inaccurate to infer the link-level loss rates and have large diagnosis granularity (in terms of the number of hops). To address these problems, we propose a suite of user-level diagnosis approaches in two categories: (1) only need to be deployed at the source and (2) deployed at both source and destination. For the former, we propose two fragmentation aided diagnosis approaches (FAD), Algebraic FAD and Opportunistic FAD, which uses IP fragmentation to enable accurate link-level loss rate inference. For the latter category, we propose Striped Probe Analysis (SPA) which significantly improves the diagnosis granularity over those of the source-only approaches. Internet experiments are applied to evaluate each individual schemes (including an improved version of the state-of-the-art tool, Tulip [1]) and various hybrid approaches. The results indicate that our approaches dramatically outperform existing work (especially for diagnosis granularity) and provide not only the best performance but also smooth tradeoff among deployment requirement, diagnosis accuracy and granularity.
166109
End-to-End Inference of Router Packet Forwarding Priority
Packet forwarding prioritization (PFP) in routers is one of the mechanisms commonly available to network administrators. PFP can have a significant impact on the performance of applications, the accuracy of measurement tools' results and the effectiveness of network troubleshooting procedures. Despite their potential impact, no information on PFP settings is readily available to end users. In this paper, we present an end-to-end approach for packet forwarding priority inference and its associated tool, POPI. This is the first attempt to infer router packet-forwarding priority through end-to-end measurement. Our POPI tool enables users to discover such network policies through the monitoring and rank classification of loss rates for different packet types. We validated our approach via statistical analysis, simulation, and wide-area experimentation in PlanetLab. As part of our wide-area experiments, we employed POPI to analyze 156 random paths across 162 PlanetLab nodes. We discovered 15 paths flagged with multiple priorities, 13 of which were further validated through hop-by-hop loss rates measurements. In addition, we surveyed all related network operators and received responses for about half of them confirming our inferences.
61999607
Towards unbiased end-to-end network diagnosis
Internet fault diagnosis is extremely important for end users, overlay network service providers (like Akamai [1]) and even Internet service providers (ISPs). However, because link-level properties cannot be uniquely determined from end-to-end measurements, the accuracy of existing statistical diagnosis approaches is subject to uncertainty from statistical assumptions about the network. In this paper, we propose a novel Least-biased End-to-end Network Diagnosis (in short, LEND) system for inferring link-level properties like loss rate. We define a minimal identifiable link sequence (MILS) as a link sequence of minimal length whose properties can be uniquely identified from end-to-end measurements. We also design efficient algorithms to find all the MILSes and infer their loss rates for diagnosis. Our LEND system works for any network topology and for both directed and undirected properties, and incrementally adapts to network topology and property changes. It gives highly accurate estimates of the loss rates of MILSes, as indicated by both extensive simulations and Internet experiments. Furthermore, we demonstrate that such diagnosis can be achieved with fine granularity and in near real-time even for reasonably large overlay networks. Finally, LEND can supplement existing statistical inference approaches and provide smooth tradeoff between diagnosis accuracy and granularity.
10897641
Reversible sketches for efficient and accurate change detection over network data streams
Traffic anomalies such as failures and attacks are increasing in frequency and severity, and thus identifying them rapidly and accurately is critical for large network operators. The detection typically treats the traffic as a collection of flows and looks for heavy changes in traffic patterns (<i>e.g.</i>, volume, number of connections). However, as link speeds and the number of flows increase, keeping per-flow state is not scalable. The recently proposed sketch-based schemes [14] are among the very few that can detect heavy changes and anomalies over massive data streams at network traffic speeds. However, sketches do not preserve the key (<i>e.g.</i>, source IP address) of the flows. Hence, even if anomalies are detected, it is difficult to infer the culprit flows, making it a big practical hurdle for online deployment. Meanwhile, the number of keys is too large to record.
 To address this challenge, we propose efficient <i>reversible hashing</i> algorithms to infer the keys of culprit flows from sketches without storing any explicit key information. No extra memory or memory accesses are needed for recording the streaming data. Meanwhile, the heavy change detection daemon runs in the background with space complexity and computational time sublinear to the key space size. This short paper describes the conceptual framework of the reversible sketches, as well as some initial approaches for implementation. See [23] for the optimized algorithms in details. comment We further apply various emph IP-mangling algorithms and emph bucket classification methods to reduce the false positives and false negatives. Evaluated with netflow traffic traces of a large edge router, we demonstrate that the reverse hashing can quickly infer the keys of culprit flows even for many changes with high accuracy.
10399949
Quantifying Network Denial of Service: A Location Service Case Study
Network Denial of Service (DoS) attacks are increasing in frequency, severity and sophistication, making it desirable to measure the resilience of systems to DoS attacks. In this paper, we propose a simulation-based methodology and apply it to attacks on object location services such as DNS. Our results allow us to contrast the DoS resilience of three distinct architectures for object location.
10510843
A SOA Based Pipeline System to Deal with Astronomy Telescope Data
In order to deal with telescope data more systematically and flexibly, this paper proposes a grid middleware pipeline system PMGrid based on service-oriented architecture (SOA) for efficient telescope data processing. This system allows users to dynamically compose data process application as a pipeline virtual service (PVS) using existing services for their special purposes. Furthermore, the configured PVS has the standard interface as services and can be published in PMGrid system as a single unit of service shared and reused by other users. Grid technologies and Web service technologies are aligned with each other in this system through standard-based interface and protocols. Based on SOA, the PMGrid system can provide not only more telescope data process functions to satisfy users' special purposes, but also more shared public functions. Combing SOA and grid, the PMGrid system is portable and has advantages in reducing cost and increasing the services utilization. This paper presents the design, analysis, and implementation of the PVS subsystem in the telescope data processing system
26820236
3-D IFS fractals as real-time graphics model
Abstract Fractals have recently been attracting increasing research interest. Unlike conventional geometrical figures, fractals have unlimited details—a potentially useful feature for artistic images. One way to generate fractals is to use Iterated Function Systems (IFS). There have been significant research efforts on 2-D IFS. Programs for rendering 2-D IFS fractals are readily available. 3-D IFS appear to be a natural extension but remain an area to be investigated. This paper explores the use of 3-D IFS for creating fascinating fractal scenes. An efficient coloring, lighting and mist effects scheme is proposed. A program using the proposed scheme has been developed that can render delicate scenes consisting of multiple IFS fractals in real-time on the PC.
11444892
A prototype implementation of archival Intermemory
An Archival Intermemory solves the problem of highly survivable digital data storage in the spirit of the Internet. In this paper we describe a prototype implementation of Intermemory, including an overall system architecture and implementations of key system components. The result is a working Intermemory that tolerates up to 17 simultaneous node failures, and includes a Web gateway for browser-based access to data. Our work demonstrates the basic feasibility of Intermemory and represents signi cant progress towards a deployable system.
9845542
Back Propagation with Randomized Cost Function for Training Neural Networks
A novel method to improve both the generalization and convergence performance of the back propagation algorithm (BP) by using multiple cost functions with a randomizing scheme is proposed in this paper. Under certain conditions, the randomized technique will converge to the global minimum with probability one. Experimental results on benchmark Encoder-Decoder problems and the NC2 classification problem show that the method is effective in enhancing BP's convergence and generalization performance
13382597
Pi4SOA: A Policy Infrastructure for Verification and Control of Service Collaboration
This paper proposes a pattern-based service collaboration architecture using services as building blocks in a service-oriented architecture (SOA). In this architecture, service registry is used to obtain the metadata of services and collaboration patterns. Thus, not only services, but also collaboration patterns can be reused. However, dynamic collaboration requires a measure to verify and validate such a dynamic process at the meta-control level. This paper presents a policy-based infrastructure to dynamically verify and control the collaboration process in SOA