53,574 research outputs found
Smarter grid through collective intelligence: user awareness for enhanced performance
This paper examines the scenario of a university campus, and the impact on energy consumption of the awareness of building managers and users (lecturers, students and administrative staff).Peer ReviewedPostprint (published version
Inefficiencies in Digital Advertising Markets
Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research
W-NINE: a two-stage emulation platform for mobile and wireless systems
More and more applications and protocols are now running on wireless networks. Testing the implementation of such applications and protocols is a real challenge as the position of the mobile terminals and environmental effects strongly affect the overall performance. Network emulation is often perceived as a good trade-off between experiments on operational wireless networks and discrete-event simulations on Opnet or ns-2. However, ensuring repeatability and realism in network emulation while taking into account mobility in a wireless environment is very difficult. This paper proposes a network emulation platform, called W-NINE, based on off-line computations preceding online pattern-based traffic shaping. The underlying concepts of repeatability, dynamicity, accuracy and realism are defined in the emulation context. Two different simple case studies illustrate the validity of our approach with respect to these concepts
Shrinkage Estimators in Online Experiments
We develop and analyze empirical Bayes Stein-type estimators for use in the
estimation of causal effects in large-scale online experiments. While online
experiments are generally thought to be distinguished by their large sample
size, we focus on the multiplicity of treatment groups. The typical analysis
practice is to use simple differences-in-means (perhaps with covariate
adjustment) as if all treatment arms were independent. In this work we develop
consistent, small bias, shrinkage estimators for this setting. In addition to
achieving lower mean squared error these estimators retain important
frequentist properties such as coverage under most reasonable scenarios. Modern
sequential methods of experimentation and optimization such as multi-armed
bandit optimization (where treatment allocations adapt over time to prior
responses) benefit from the use of our shrinkage estimators. Exploration under
empirical Bayes focuses more efficiently on near-optimal arms, improving the
resulting decisions made under uncertainty. We demonstrate these properties by
examining seventeen large-scale experiments conducted on Facebook from April to
June 2017
Position Estimation of Robotic Mobile Nodes in Wireless Testbed using GENI
We present a low complexity experimental RF-based indoor localization system
based on the collection and processing of WiFi RSSI signals and processing
using a RSS-based multi-lateration algorithm to determine a robotic mobile
node's location. We use a real indoor wireless testbed called w-iLab.t that is
deployed in Zwijnaarde, Ghent, Belgium. One of the unique attributes of this
testbed is that it provides tools and interfaces using Global Environment for
Network Innovations (GENI) project to easily create reproducible wireless
network experiments in a controlled environment. We provide a low complexity
algorithm to estimate the location of the mobile robots in the indoor
environment. In addition, we provide a comparison between some of our collected
measurements with their corresponding location estimation and the actual robot
location. The comparison shows an accuracy between 0.65 and 5 meters.Comment: (c) 2016 IEEE. Personal use of this material is permitted. Permission
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