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.
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.
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.
6860435
On the stability of network distance estimation
Overlay network distance monitoring and estimation system can benefit many new applications and services, such as peer-to-peer overlay routing and location. However, there is a lack of such scalable system with small overhead, good usability, and good distance estimation accuracy and stability. Thus we propose a scalable overlay distance monitoring system, Internet Iso-bar, which clusters hosts based on the similarity of their perceived network distance, with no assumption about the underlying network topology. The centers of each cluster are then chosen as monitors to represent their clusters for probing and distance estimation. We compare it with other network distance estimation systems, such as Global Network Positioning (GNP) [1]. Internet Iso-bar is easy to implement and use, and has good scalability and small communication and computation cost for online monitoring. Preliminary evaluation on real Internet measurement data also shows that Internet Iso-bar has high prediction accuracy and stability. Finally, by adjusting the number of clusters, we can smoothly trade off the measurement and management cost for better distance estimation accuracy and stability.
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.
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.
1752675
Storing and Discovering Critical Workflows from Log in Scientific Exploration
This paper aims at effectively reproducing the results of previous scientific workflow executions. We first identify the information that needs to be recorded in a workflow execution log, based on which we then determine the data flow among experiments. To effectively record a workflow execution log in a relational database management system (RDBMS) when the workflow design is absent, we propose a generic relational storage schema. Then techniques have been designed to automatically discover the minimal set of experiments that must be performed in order to reproduce a scientific result by posing appropriate SQL queries. Although such SQL queries can be evaluated using an off-the-shelf database system, we investigate the unique characteristics of the workflow log data and optimization techniques for evaluating such SQL queries efficiently.
37811955
Progressive ranking and composition of Web services using covering arrays
Major computer companies and government agencies are adopting Web services (WS) technology. Web services must ensure interoperability and security, and be reliable and trustworthy. Consumers must make runtime decisions based on an intelligent and unbiased evaluation. We propose one component of a test suite generator to address this critical issue. The goal is to transform the labor-intensive software development process into a largely automated Web services development process. The method operates within a service-oriented architecture, with the models and tools implemented as services that can be added, removed and replaced at runtime. We propose a generic greedy algorithm based on covering arrays for application in this environment.
45017187
An Agent-Based Metric for Quality of Services over Wireless Networks
In a wireless LAN environment, wireless stations with the strongest received signal can not be guaranteed to have the best quality of service if the population sharing the network capacity was not considered. In other words, within the same access point, the more the population, the less the shared bandwidth, and the worse the quality of service will be. In this paper, we proposed an Anticipative Agent Assistance which is an agent-based metric for evaluating and managing the resource of the wireless access points, computing the potential AP list, and providing clients with resource information of APs. We also propose a novel QoS feedback mechanism which allows users to promptly adjust the service quality with AAA according to the throughput and delay requirements. We evaluate the performance of our proposed method using the ns-2 simulator. Numerical results show that AAA help reduce the transmission delay, increase the throughput, improve the network utilization, accommodate more users, and provide load-balancing.
18417913
IT induction in the food service industry
As part of the business strategy in a competitive environment, for an organization to induct information technology (IT) appropriately, business process reengineering (BPR) must be conducted. We propose a process that incorporates both management information systems and strategic management concepts for the IT induction. First, we develop a business competition strategy based on Porter’s five competitive forces; second, using concepts developed in the field of information systems the business processes are reengineered to improve effectiveness and efficiency; and finally, IT strategy is developed to achieve these goals. A real‐life case in the food service industry is used to illustrate this process.
832740
Constrained genetic algorithms and their applications in nonlinear constrained optimization
The paper presents a problem-independent framework that unifies various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not necessarily differentiable and continuous. The framework is based on the first-order necessary and sufficient conditions in the theory of discrete constrained optimization using Lagrange multipliers. It implements the search for discrete-neighborhood saddle points (SP/sub dn/) by performing ascents in the original-variable subspace and descents in the Lagrange-multiplier subspace. Our study on the various mechanisms shows that CSAGA, a combined constrained simulated annealing and genetic algorithm, performs well. Finally, we apply iterative deepening to determine the optimal number of generations in CSAGA.