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检索条件"任意字段=Proceedings of the 1994 ACM Sigmetrics Conference on Measurement and Modeling of Computer Systems"

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A case study in power substation network dynamics

A case study in power substation network dynamics

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2017 acm sigmetrics / International conference on measurement and modeling of computer systems, sigmetrics 2017

作者： Formby, David Walid, Anwar Beyah, Raheem Georgia Institute of Technology United States Bell Laboratories United States

ISBN: (纸本)9781450350327

The modern world is becoming increasingly dependent on computing and communication technology to function, but unfortunately its application and impact on areas such as critical infrastructure and industrial control system (ICS) networks remains to be thoroughly studied. Significant research has been conducted to address the myriad security concerns in these areas, but they are virtually all based on artificial testbeds or simulations designed on assumptions about their behavior either from knowledge of traditional IT networking or from basic principles of ICS operation. In this work, we provide the most detailed characterization of an example ICS to date in order to determine if these common assumptions hold true. A live power distribution substation is observed over the course of two and a half years to measure its behavior and evolution over time. Then, a horizontal study is conducted that compared this behavior with three other substations from the same company. Although most predictions were found to be correct, some unexpected behavior was observed that highlights the fundamental differences between ICS and IT networks including round trip times dominated by processing speed as opposed to network delay, several well known TCP features being largely irrelevant, and surprisingly large jitter from devices running real-time operating systems. The impact of these observations is discussed in terms of generality to other embedded networks, network security applications, and the suitability of the TCP protocol for this environment.

关键词： characterization ICS networks measurement power grid SCADA

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Accurate Deep Direct Geo-Localization from Ground Imagery and Phone-Grade GPS 31

Accurate Deep Direct Geo-Localization from Ground Imagery an...

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IEEE/CVF conference on computer Vision and Pattern Recognition (CVPR)

作者： Sun, Shaohui Sarukkai, Ramesh Kwok, Jack Shet, Vinay Lyft Inc Engn Ctr Level5 Palo Alto CA 94304 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

One of the most critical topics in autonomous driving or ride-sharing technology is to accurately localize vehicles in the world frame. In addition to common multiview camera systems, it usually also relies on industrial grade sensors, such as LiDAR, differential GPS, high precision IMU, and etc. In this paper, we develop an approach to provide an effective solution to this problem. We propose a method to train a geo-spatial deep neural network (CNN+LSTM) to predict accurate geo-locations (latitude and longitude) using only ordinary ground imagery and low accuracy phone-grade GPS. We evaluate our approach on the open dataset released during acm Multimedia 2017 Grand Challenge. Having ground truth locations for training, we are able to reach nearly lane-level accuracy. We also evaluate the proposed method on our own collected images in San Francisco downtown area often described as "downtown canyon" where consumer GPS signals are extremely inaccurate. The results show the model can predict quality locations that suffice in real business applications, such as ride-sharing, only using phone-grade GPS. Unlike classic visual localization or recent PoseNet-like methods that may work well in indoor environments or small-scale outdoor environments, we avoid using a map or an SFM (structure-from-motion) model at all. More importantly, the proposed method can be scaled up without concerns over the potential failure of 3D reconstruction.

关键词： Global Positioning System Three-dimensional displays Visualization Noise measurement Task analysis Cameras Solid modeling

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Stein's method for mean-field approximations in light and heavy traffic regimes

Stein's method for mean-field approximations in light and he...

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2017 acm sigmetrics / International conference on measurement and modeling of computer systems, sigmetrics 2017

作者： Ying, Lei School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

ISBN: (纸本)9781450350327

Mean-field analysis is an analytical method for understanding large-scale stochastic systems such as large-scale data centers and communication networks. The idea is to approximate the stationary distribution of a large-scale stochastic system using the equilibrium point (called the mean-field limit) of a dynamical system (called the mean-field model). This approximation is often justified by proving the weak convergence of stationary distributions to its mean-field limit. Most existing mean-field models concerned the light-traffic regime where the load of the system, denote by ρ, is strictly less than one and is independent of the size of the system. This is because a traditional mean-field model represents the limit of the corresponding stochastic system. Therefore, the load of the mean-field model is ρ=limN-> ∞ ρ(N), where ρ(N) is the load of the stochastic system of size N. Now if ρ(N)-> 1 as N -> ∞ (i.e., in the heavy-traffic regime), then ρ=1. For most systems, the mean-field limits when ρ=1 are trivial and meaningless. To overcome this difficulty of traditional mean-field models, this paper takes a different point of view on mean-field models. Instead of regarding a mean-field model as the limiting system of large-scale stochastic system, it views the equilibrium point of the mean-field model, called a mean-field solution, simply as an approximation of the stationary distribution of the finite-size system. Therefore both mean-field models and solutions can be functions of N. The proposed method focuses on quantifying the approximation error. If the approximation error is small (as we will show in two applications), then we can conclude that the mean-field solution is a good approximation of the stationary distribution.

关键词： Stein's method the-power-of-two-choices large-scale stochastic systems mean-field approximations heavy traffic analysis

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An Open-Source Verification Framework for Open-Source Cores: A RISC-V Case Study 26

An Open-Source Verification Framework for Open-Source Cores:...

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26th IFIP/IEEE International conference on Very Large Scale Integration (VLSI-SoC)

作者： Schiavone, Pasquale Davide Sanchez, Ernesto Ruospo, Annachiara Minervini, Francesco Zaruba, Florian Haugou, Germain Benini, Luca Swiss Fed Inst Technol Zurich Switzerland Politecn Torino Turin Italy

ISBN: (纸本)9781538647561

The complexity and heterogeneity of digital devices used in embedded systems is increasing everyday and delivering a bug-free design is still a very complex task. The interest for open-source hardware in real products is demanding for tools and advanced methodologies for verification to provide high reliability to open and free IPs. In this work, an open-source evolutionary optimizer has been used to create functional test programs that improve the verification test set for an open-source microprocessor, enhancing in this way, the verification level of the device. The verification programs are generated to optimize code coverage metrics and are tested against a high-level model to find device incorrectnesses during the generation time. A perturbation mechanism has been included in the verification framework to cover parts of the device under verification not reachable with only software stimuli such as interrupts or memory stalls. The proposed methodology uncovered 10 bugs still present in the RTL description of the analyzed device and demonstrated the effectiveness of open-source verification tools for the next generation of open-source RISC-V microprocessors.

关键词： Open source software measurement Program processors Microprocessors computer bugs Computational modeling Hardware

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On moving averages, histograms and time-dependent rates for online measurement 17

On moving averages, histograms and time-dependent rates for ...

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8th acm/SPEC International conference on Performance Engineering, ICPE 2017

作者： Menth, Michael Hauser, Frederik Department of Computer Science University of Tuebingen Germany

ISBN: (纸本)9781450344043

Moving averages (MAs) are often used in adaptive systems to monitor the state during operation. Their output is used as input for control purposes. There are multiple methods with different ability, complexity, and parameters. We propose a framework for the definition of MAs and develop performance criteria, e.g., the concept of memory, that allow to parameterize different methods in a comparable way. Moreover, we identify deficiencies of frequently used methods and propose corrections. We extend MAs to moving histograms which facilitate the approximation of timedependent quantiles. We further extend the framework to rate measurement, discuss various approaches, and propose a novel method which reveals excellent properties. The proposed concepts help to visualize time-dependent data and to simplify design, parametrization, and evaluation of technical control systems. © 2017 acm.

关键词： Graphic methods

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Deriving parameters for open and closed QN models of operational systems through black box optimization 17

Deriving parameters for open and closed QN models of operati...

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8th acm/SPEC International conference on Performance Engineering, ICPE 2017

作者： Awad, Mahmoud Menascé, Daniel A. Computer Science Department George Mason University FairfaxVA22030 United States

ISBN: (纸本)9781450344043

Black-box modeling techniques are used when modeling computer systems with unknown internal structure or behavior and/or when it is not feasible or too time consuming to monitor a running computer system. The main challenge in these situations lies in estimating values for the parameters of these models, especially the values of service demands at the various devices for each transaction class. These estimates have to be compliant with the input-output relationships observed through measurements. This means that solving a model of the system with the estimated parameters should yield the same outputs (e.g., response times) for the same inputs (e.g., arrival rates or concurrency level). This paper presents a method for automatically estimating service demands for open, closed, single and multiclass queuing networks (QN). The method is based on casting the estimation problem as a non-linear optimization problem. However, because the solution of closed QNs does not have a closed form, we need to resort to black-box optimization techniques. The parameter estimation method presented here is part of iModel, a framework for automatically deriving performance models of systems whose detailed characteristics (structure and behavior) are unknown. Other portions of the framework were discussed in detail in previous publications by the authors. This paper illustrates the ideas through several numerical examples and then applies them to a multi-tiered operational system running OFBiz. The estimated service demands closely satisfy the input-output relationships at various workload intensity levels and can be used for prediction purposes. © 2017 acm.

关键词： Parameter estimation

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PhO₂: Smartphone based Blood Oxygen Level measurement systems using Near-IR and RED Wave-guided Light 17

PhO<sub>2</sub>: Smartphone based Blood Oxygen Level Measure...

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15th acm conference on Embedded Networked Sensor systems (SenSys)

作者： Nam Bui Anh Nguyen Phuc Nguyen Hoang Truong Ashok, Ashwin Thang Dinh Deterding, Robin Tam Vu Univ Colorado Boulder CO 80309 USA Georgia State Univ Atlanta GA 30303 USA Virginia Commonwealth Univ Richmond VA 23284 USA Childrens Hosp Colorado Aurora CO USA

ISBN: (纸本)9781450354592

Accurately measuring and monitoring patient's blood oxygen level plays a critical role in today's clinical diagnosis and healthcare practices. Existing techniques however either require a dedicated hardware or produce inaccurate measurements. To fill in this gap, we propose a phone-based oxygen level estimation system, called PhO2, using camera and flashlight functions that are readily available on today's off-the-shelf smart phones. Since phone's camera and flashlight are not made for this purpose, utilizing them for oxygen level estimation poses many challenges. We introduce a cost-effective add-on together with a set of algorithms for spatial and spectral optical signal modulation to amplify the optical signal of interest while minimizing noise. A light-based pressure detection algorithm and feedback mechanism are also proposed to mitigate the negative impacts of user's behavior during the measurement. We also derive a non-linear referencing model that allows PhO2 to estimate the oxygen level from color intensity ratios produced by smartphone's camera. An evaluation using a custom-built optical element on COTS smartphone with 6 subjects shows that PhO2 can estimate the oxygen saturation within 3.5% error rate comparing to FDA-approved gold standard pulse oximetry. A user study to gauge the reception of PhO2 shows that users are comfortable self-operating the device, and willing to carry the device when going out.

关键词： oxygen saturation optical divider near-infrared sensing phone's add-on phone camera

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Session details: Session 9: Accurate and Efficient Performance measurement

Session details: Session 9: Accurate and Efficient Performan...

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proceedings of the 2017 acm sigmetrics / International conference on measurement and modeling of computer systems

作者： Giuliano Casale Imperial College

No abstract available.

ISBN: (纸本)9781450350327

No abstract available.

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Text Retrieval based on Least Information measurement 17

Text Retrieval based on Least Information Measurement

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7th acm SIGIR International conference Theory of Information Retrieval (ICTIR)

作者： Ke, Weimao Drexel Univ 3141 Chestnut St Philadelphia PA 19104 USA

ISBN: (纸本)9781450344906

We developed a new information retrieval framework based on the Least Information (LI) metric. We derived multiple term weighting schemes and combined them with a vector space representation for ad hoc retrieval. Given probability distributions in a collection as prior knowledge, LI Binary (LIB) quantifies least information due to the binary occurrence of a term in a document whereas LI Frequency (LIF) measures least information based on the probability of drawing a term from a bag of words. Experiments on four benchmark TREC collections for ad hoc retrieval showed that LIT-based methods achieved superior performances compared to classic TF*IDF and BM25, especially for verbose queries and hard search topics. The least information theory is a method for entropy-based information measurement and offers a novel approach for IR modeling.

关键词： information measure metric information retrieval probability distribution entropy term weighting relevance ranking effectiveness

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sigmetrics 2014 - proceedings of the 2014 acm sigmetrics International conference on measurement and modeling of computer systems

SIGMETRICS 2014 - Proceedings of the 2014 ACM SIGMETRICS Int...

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2014 acm sigmetrics International conference on measurement and modeling of computer systems, sigmetrics 2014

ISBN: (纸本)9781450327893

The proceedings contain 67 papers. The topics discussed include: rumor source detection with multiple observations: fundamental limits and algorithms;collecting, organizing, and sharing pins in Pinterest: interest-driven or social-driven?;jointly clustering rows and columns of binary matrices: algorithms and trade-offs;an online auction framework for dynamic resource provisioning in cloud computing;energy procurement strategies in the presence of intermittent sources;randomized auction design for electricity markets between grids and microgrids;pricing data center demand response;index policies for a multi-class queue with convex holding cost and abandonments;concave switching in single and multihop networks;the power of online learning in stochastic network optimization;and non-work-conserving effects in MapReduce: diffusion limit and criticality.

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