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共 983 条记录，以下是121-130 订阅

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Data Predictive Control for Building Energy Management: Poster Abstract 16

Data Predictive Control for Building Energy Management: Post...

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Proceedings of the 3rd acm international conference on systems for Energy-Efficient Built Environments

作者： Achin Jain Madhur Behl Rahul Mangharam Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA Computer Science University of Virginia Charlottesville VA USA

ISBN: (纸本)9781450342643

Decisions on how best to optimize today's energy systems operations are becoming ever so complex and conflicting such that model-based predictive control algorithms must play a key role. However, learning dynamical models of energy consuming systems such as buildings, using grey/white box approaches is very cost and time prohibitive due to its complexity. This paper presents data-driven methods for making control-oriented model for peak power reduction in buildings. Specifically, a data predictive control with regression trees (DPCRT) algorithm, is presented. DPCRT is a finite receding horizon method, using which the building operator can optimally trade off peak power reduction against thermal comfort without having to learn white/grey box models of the systems dynamics. We evaluate the performance of our method using a DoE commercial reference virtual test-bed and show how it can be used for learning predictive models with 90% accuracy, and for achieving 8.6% reduction in peak power and costs.

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Detecting sponsored recommendations

Detecting sponsored recommendations

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acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Krishnasamy, Subhashini Sen, Rajat Shakkottai, Sanjay Oh, Sewoong Dept. of Electrical and Computer Engineering UT Austin United States Dept. of Industrial and Enterprise Systems Engineering UIUC United States

ISBN: (纸本)9781450334860

Personalized recommender systems provide great opportunities for targeted advertisements, by displaying ads alongside genuine recommendations. We consider a biased recommendation system where such ads are displayed without any tags (disguised as genuine recommendations), rendering them indistinguishable to users. We consider the problem of detecting such a bias and propose an algorithm that uses statistical analysis based on binary feedback data from a subset of users. We prove that the proposed algorithm detects bias with high probability for a broad class of recommendation systems with sufficient number of feedback samples. © Copyright 2015 acm.

关键词： Recommender systems

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Understanding parallel performance under interferences in multi-tenant clouds

Understanding parallel performance under interferences in mu...

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acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Zhao, Yong Rao, Jia Zhou, Xiaobo Yi, Qing Dept. of Computer Science University of Colorado Colorado Springs United States

ISBN: (纸本)9781450334860

The performance of parallel programs is notoriously difficult to reason in virtualized environments. Although performance degradations caused by virtualization and interferences have been well studied, there is little understanding why *** parallel programs have unpredictable slowdowns. We find that unpredictable performance is the result of complex interplays between the design of the program, the memory hierarchy of the hosting system, and the CPU scheduling in the hypervisor. We develop a profiling tool, vProfile, to decompose parallel runtime into three parts: compute, steal and synchronization. With the help of time breakdown, we devise two optimizations at the hypervisor to reduce slowdowns. © Copyright 2015 acm.

关键词： Scheduling

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Swarm Gateway: Demo Abstract 16

Swarm Gateway: Demo Abstract

引用

Proceedings of the 3rd acm international conference on systems for Energy-Efficient Built Environments

作者： Bradford Campbell Branden Ghena Ye-Sheng Kuo Prabal Dutta Electrical Engineering and Computer Science Department University of Michigan Ann Arbor MI

ISBN: (纸本)9781450342643

The gateway is a key component for sensor network deployments and the Internet of Things. Sensor deployments often tend towards low-power communication protocols such as Bluetooth Low Energy or IEEE 802.15.4. Gateways are essential to connect these devices to the Internet at large. Over time though, gateways have gained additional responsibilities as well. Sensors expect gateways to handle device-specific data translation and local processing while also providing services, such as time synchronization, to the low-power device. As a centralized computing resource, the gateway is also an obvious location for running local applications which interact with sensor data and control nearby actuators. Today, vendors and researchers often create their own device-specific gateways to handle these *** propose a generic gateway platform capable of supporting the needs of many devices. In our architecture, devices provide a pointer, such as a URL, to descriptions of their interfaces. The gateway can download the interface descriptions and use them to determine how to interact with the device, translating its data to a usable format and enabling local services to communicate with it. The translated data is provided to services including user applications, local logging, device status monitoring, and cloud applications. By simultaneously supporting communication with many sensors, our gateway architecture can simplify future sensor network deployments and enable intelligent building applications.

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Deltatree: A locality-aware concurrent search tree 15

Deltatree: A locality-aware concurrent search tree

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acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Umar, Ibrahim Anshus, Otto J. Ha, Phuong Hoai Department of Computer Science University of Tromsø Norway

ISBN: (纸本)9781450334860

Like other fundamental abstractions for high-performance computing, search trees need to support both high concurrency and data locality. However, existing locality-aware search trees based on the van Emde Boas layout (vEB-based trees), poorly support concurrent (update) operations. We present DeltaTree, a practical locality-aware concurrent search tree that integrates both locality-optimization techniques from vEB-based trees, and concurrency-optimization techniques from highly-concurrent search trees. As a result, DeltaTree minimizes data transfer from memory to CPU and supports high concurrency. Our experimental evaluation shows that DeltaTree is up to 50% faster than highly concurrent B-trees on a commodity Intel high performance computing (HPC) platform and up to 65% faster on a commodity ARM embedded platform. © Copyright 2015 acm.

关键词： Data transfer

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Deterministic near-optimal P2P streaming 15

Deterministic near-optimal P2P streaming

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acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Venkatakrishnan, Shaileshh Bojja Viswanath, Pramod Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign United States

ISBN: (纸本)9781450334860

We consider live-streaming over a peer-to-peer network in which peers are allowed to enter or leave the system adversarially and arbitrarily. Previous approaches for streaming have either used randomized distribution graphs or structured trees with randomized maintenance algorithms. Randomized graphs handle peer churn well but have only probabilistic connectivity guarantees, while structured trees have good connectivity but have proven hard to maintain under peer churn. We improve upon both approaches by presenting a novel distribution structure with a deterministic and distributed algorithm for maintenance under peer churn. The algorithm has a constant repair time for connectivity, and near optimal delay. As opposed to order results, the guarantees provided by our algorithm are exact and hold for any network size. © Copyright 2015 acm.

关键词： Peer to peer networks

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Model-based design of resource-efficient automotive control software

Model-based design of resource-efficient automotive control ...

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IEEE international conference on computer-Aided Design

作者： Wanli Chang Debayan Roy Licong Zhang Samarjit Chakraborty TUM CREATE Singapore Singapore Institute of Technology Institute for Real-Time Computer Systems TU Munich Germany Technische Universitat Munchen Munchen Bayern DE

ISBN: (纸本)9781509034215

Automotive platforms today run hundreds of millions of lines of software code implementing a large number of different control applications spanning across safety-critical functionality to driver assistance and comfort-related functions. While such control software today is largely designed following model-based approaches, the underlying models do not take into account the details of the implementation platforms, on which the software would eventually run. Following the state-of-the-art in control theory, the focus in such design is restricted to ensuring the stability of the designed controllers and meeting control performance objectives, such as settling time or peak overshoot. However, automotive platforms are highly cost-sensitive and the issue of designing “resource-efficient” controllers has largely been ignored so far and is addressed using very ad hoc techniques. In this paper, we will illustrate how, following traditional embedded systems design oriented thinking, computation, communication and memory issues can be incorporated in the controller design stage, thereby resulting in control software not only satisfying the usual control performance metrics but also making efficient utilization of the resources on distributed automotive architectures.

关键词： Automotive engineering Actuators computer architecture measurement Computational modeling Embedded systems

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Flexible transformations for learning big data

Flexible transformations for learning big data

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acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Mirhoseini, Azalia Songhori, Ebrahim M. Rouhani, Bita Darvish Koushanfar, Farinaz Electrical and Computer Engineering Rice University HoustonTX77005 United States

ISBN: (纸本)9781450334860

This paper proposes a domain-specific solution for iterative learning of big and dense (non-sparse) datasets. A large host of learning algorithms, including linear and regularized regression techniques, rely on iterative updates on the data connectivity matrix in order to converge to a solution. The performance of such algorithms often severely degrade when it comes to large and dense data. Massive dense datasets not only induce obligatory large number of arithmetics, but they also incur unwanted message passing cost across the processing nodes. Our key observation is that despite the seemingly dense structures, in many applications, data can be transformed into a new space where sparse structures become revealed. We propose a scalable data transformation scheme that enables creating versatile sparse representations of the data. The transformation can be tuned to benefit the underlying platform's cost and constraints. Our evaluations demonstrate significant improvement in energy usage, runtime, and memory footprint, within guaranteed user-defined error bounds. © Copyright 2015 acm.

关键词： Iterative methods

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Making neural encoding robust and energy efficient: An advanced analog temporal encoder for brain-inspired computing systems

Making neural encoding robust and energy efficient: An advan...

引用

IEEE international conference on computer-Aided Design

作者： Chenyuan Zhao Jialing Li Yang Yi Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

ISBN: (纸本)9781509034215

Neural encoder is one of the key components in neuromorphic computing systems, whereby sensory information is transformed into spike coded trains. The design of temporal encoder has attracted a widespread attention in the field of neuromorphic computing in the past few years. The information in the temporal encoding scheme with inter-spike intervals can arise from correlations between spike times, which could not be incorporated in the traditional rate encoding scheme. In this paper, we propose a robust and energy efficient analog implementation of the spiking temporal encoder. We pattern the neural activities across multiple timescales and encode the sensory information using time dependent temporal scales. The concept of iteration structure is introduced to construct a neural encoder that greatly increases the information process ability of the proposed temporal encoder. Integrated with iteration technique and operational-amplifier-free design, the error rate of the output temporal codes is reduced to an extremely low level. A lower sampling rate accompanied by additional verification spikes is introduced in the schemes, which significantly reduces the power consumption of the encoding system. To the best of our knowledge, our proposed neuron circuit is the first analog hardware implementation of the neural encoder that could present the sensory data using inter-spike interval temporal encoding scheme. The simulation and measurement results show the proposed temporal encoder exhibits not only energy efficiency but also high accuracy.

关键词： Encoding Neurons Biological system modeling Semiconductor device modeling Neuromorphics Biomembranes Power demand

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Detecting and localizing end-to-end performance degradation for cellular data services

Detecting and localizing end-to-end performance degradation ...

引用

acm sigmetrics international conference on measurement and modeling of computer systems, sigmetrics 2015

作者： Ahmed, Faraz Erman, Jeffrey Ge, Zihui Liu, Alex X. Wang, Jia Yan, He Department of Computer Science and Engineering Michigan State University East LansingMI United States AT and T Labs - Research BedminsterNJ United States

ISBN: (纸本)9781450334860

Nowadays mobile device (e.g., smartphone) users not only have a high expectation on the availability of the cellular data service, but also increasingly depend on the high end-to-end (E2E) performance of their applications. Since the E2E performance of individual application sessions may vary greatly, depending on factors such as the cellular network condition, the content provider, the type/model of the mobile devices, and the application software, detecting and localizing service performance degradations in a timely manner at large scale is of great value to cellular service providers. In this paper, we build a holistic measurement system that tracks session-level E2E performance metrics along with the service attributes for these factors. Using data collected from a major cellular service provider, we first model the expected E2E service performance with a regression based approach, detect performance degradation conditions based on the time series of fine-grained measurement data, and finally localize the service degradation using association-rule-mining techniques. Our deployment experience reveals that in 80% of the detected problem instances, performance degradation can be attributed to non-networklocation specific factors, such as a common content provider, or a set of applications running on certain models of devices. © Copyright 2015 acm.

关键词： Application programs

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