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CHI Conference on Human Factors in computing Sytems (CHI)

作者： Harvey, Emma Sandhaus, Hauke Jacobs, Abigail Z. Moss, Emanuel Sloane, Mona Cornell Univ Ithaca NY USA Cornell Univ New York NY USA Univ Michigan Ann Arbor MI USA Intel New York NY USA Univ Virginia Charlottesville VA 22903 USA

ISBN: (纸本)9798400703300

Motion capture systems, used across various domains, make body representations concrete through technical processes. We argue that the measurement of bodies and the validation of measurements for motion capture systems can be understood as social practices. By analyzing the findings of a systematic literature review (N=278) through the lens of social practice theory, we show how these practices, and their varying attention to errors, become ingrained in motion capture design and innovation over time. Moreover, we show how contemporary motion capture systems perpetuate assumptions about human bodies and their movements. We suggest that social practices of measurement and validation are ubiquitous in the development of data- and sensor-driven systems more broadly, and provide this work as a basis for investigating hidden design assumptions and their potential negative consequences in human-computer interaction.

关键词： motion capture measurement validation social practices anthropometry

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Can OS Specialization give new life to old carbon in the cloud? 24

Can OS Specialization give new life to old carbon in the clo...

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17th International systems and Storage Conference (SYSTOR)

作者： Dong, Han Arora, Sanjay Krieger, Orran Appavoo, Jonathan Boston Univ Boston MA 02215 USA Red Hat Inc New York NY USA

ISBN: (纸本)9798400711817

Is there "fat" (overheads) in cloud computing infrastructure software that can be trimmed? Would doing so help ameliorate the need for frequent hardware refreshes and extend the life of existing hardware? In this paper, we demonstrate that, indeed, there is "fat" that can be trimmed by using specialized OS-based software stacks. Doing so can allow decade-old computers to be used for critical cloud infrastructure services, potentially yielding 3x improvements in efficiency compared to standard software stacks on newer hardware. The implications of these results raise the possibility of exploiting OS optimizations to reduce server hardware obsolescence. Further, it suggests the importance of addressing the key portability challenges of specialized OS stacks.

关键词： sustainability operating systems measurement

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proceedings of PDSW 2021: IEEE/acm 6th International Parallel Data systems Workshop, Held in conjunction with SC 2021: The International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of PDSW 2021: IEEE/ACM 6th International Paralle...

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6th IEEE/acm International Parallel Data systems Workshop, PDSW 2021

ISBN: (纸本)9781665418379

The proceedings contain 7 papers. The topics discussed include: new challenges of benchmarking all-flash storage for HPC;understanding the I/O impact on the performance of high-throughput molecular docking;I/O bottleneck detection and tuning: connecting the dots using interactive log analysis;data-aware storage tiering for deep learning;SCTuner: an autotuner addressing dynamic I/O needs on supercomputer I/O subsystems;user-centric system fault identification using IO500 benchmark;and verifying IO synchronization from MPI traces.

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LENS: A LEO Satellite Network measurement Dataset 24

LENS: A LEO Satellite Network Measurement Dataset

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15th acm Multimedia systems Conference (acm MMSys)

作者： Zhao, Jinwei Pan, Jianping Univ Victoria Victoria BC Canada

ISBN: (纸本)9798400704123

Low-Earth-Orbit (LEO) satellite constellations are narrowing the performance gap between satellite networks and the terrestrial Internet. Low-latency satellite Internet offered by Starlink enables functionalities that are otherwise unachievable with the traditional geosynchronous equatorial orbit (GEO) satellite networks, including low-latency live video streaming, cloud gaming and real-time video conferencing. The absence of a comprehensive and long-term network measurement dataset with a global perspective poses significant challenges for researchers to evaluate the application performance over Starlink networks. In this paper, we introduce LENS, which is a LEO satellite network measurement dataset, collected from 13 Starlink dishes, associated with 7 Point-of-Presence (PoP) locations across 3 continents. The dataset currently consists of network latency traces from Starlink dishes with different hardware revisions, various service subscriptions and distinct sky obstruction ratios. We provide a high-level overview and analysis of the latency performance using the dataset and discuss various use cases. This dataset is useful for researchers who wish to understand the long-term network performance of Starlink and to evaluate and optimize the performance of multimedia applications over satellite networks.

关键词： LEO Latency Network measurement Inter-Satellite Links Dataset

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Towards Ethical AI Moderation in Multiplayer Games

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proceedings of the acm on Human-Computer Interaction 2024年第CHI PLAY期8卷 1-30页

作者： Sparrow, Lucy A. Galwey, Ren Jovic, Dahlia Hardwick, Taylor Butt, Mahli-Ann School of Computing and Information Systems The University of Melbourne Australia

AI is increasingly being used to moderate player behaviour in online multiplayer games, working to identify and respond to toxic and problematic conduct with greater efficiency and accuracy than existing automated systems. However, little work has explored the application of AI moderation in the gaming ecosystem, despite growing ethical concerns about AI applications in other domains. In this study, we conducted 2 expert workshops and interviewed 26 players and industry professionals on their understandings, perceptions and experiences with AI moderation in multiplayer games. Applying a metaphorical frame via template analysis, we outline four metaphors that capture participants’ views on the roles of AI and automation in moderation: the Unreliable Police Force, the Unscrupulous Governor, the Uncaring Judge, and the Untiring Assistant. We discuss these roles as exacerbating a top-down, punitive online justice system and identify ethical concerns around transparency, fairness and inclusion, privacy, and human-AI collaboration. To address these concerns, we put forward a set of ethical design considerations and alternative roles for AI moderation in multiplayer games. © 2024 Copyright is held by the owner/author(s).

关键词： Game design

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Beyond Data Points: Regionalizing Crowdsourced Latency measurements

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proceedings of the acm on measurement and analysis of computing systems 2024年第3期8卷 1-24页

作者： Sharma, Taveesh Schmitt, Paul Bronzino, Francesco Feamster, Nick Marwell, Nicole P. Univ Chicago Chicago IL 60637 USA Univ Hawaii Honolulu HI USA Ecole Normale Super Lyon Lyon France

Despite significant investments in access network infrastructure, universal access to high-quality Internet connectivity remains a challenge. Policymakers often rely on large-scale, crowdsourced measurement datasets to assess the distribution of access network performance across geographic areas. These decisions typically rest on the assumption that Internet performance is uniformly distributed within predefined social boundaries, such as zip codes, census tracts, or neighborhood units. However, this assumption may not be valid for two reasons: (1) crowdsourced measurements often exhibit non-uniform sampling densities within geographic areas;and (2) predefined social boundaries may not align with the actual boundaries of Internet infrastructure. In this paper, we present a spatial analysis on crowdsourced datasets for constructing stable boundaries for sampling Internet performance. We hypothesize that greater stability in sampling boundaries will reflect the true nature of Internet performance disparities than misleading patterns observed as a result of data sampling variations. We apply and evaluate a series of statistical techniques to: (1) aggregate Internet performance over geographic regions;(2) overlay interpolated maps with various sampling unit choices;and (3) spatially cluster boundary units to identify contiguous areas with similar performance characteristics. We assess the effectiveness of the techniques we apply by comparing the similarity of the resulting boundaries for monthly samples drawn from the dataset. Our evaluation shows that the combination of techniques we apply achieves higher similarity compared to directly calculating central measures of network metrics over census tracts or neighborhood boundaries. These findings underscore the important role of spatial modeling in accurately assessing and optimizing the distribution of Internet performance, which can better inform policy, network operations, and long-term planning decisions.

关键词： Access networks Latency Crowdsourcing Interpolation Spatial analysis

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INT-MC: Low-Overhead In-Band Network-Wide Telemetry Based on Matrix Completion

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proceedings of the acm on measurement and analysis of computing systems 2024年第3期8卷 1-30页

作者： Zeng, Xin Xie, Kun Li, Yanbiao Xu, Ke Xie, Gaogang Wen, Jigang Cong, Yinchuan Liang, Wei Hunan Univ Changsha Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Hunan Univ Sci & Technol Xiangtan Peoples R China

In-band Network Telemetry (INT) enhances real-time, high-resolution network monitoring capabilities by incorporating fine-grained internal state information into packets. Utilizing INT for network-wide visualization can significantly bolster network management and operation. Although existing studies have made significant contributions, they have not been able to simultaneously meet the following two objectives: 1) Comprehensive visibility of the network's internal state, which refers to obtaining information on all switch ports and their corresponding link states;2) Low measurement overhead, which involves reducing measurement bandwidth overhead and minimizing the impact of the measurement process on the network. We designed INT-MC to meet both of these objectives. INT-MC is an efficient and cost-effective network-wide telemetry solution based on matrix completion. By modeling link metadata as a matrix and leveraging its low-rank property, INT-MC selectively measures certain links. It then employs matrix completion algorithms to infer information about unmeasured links, thereby achieving low-overhead network-wide telemetry. Designing paths to cover the target links involves an NP-complete problem, and the high computational complexity may delay the measurement tasks. To circumvent this, we propose an improved scheme based on Eulerian digraph decomposition, transforming the path calculation problem into a high-information path selection problem, significantly reducing computational costs. We have implemented an INT-MC prototype within the NSFNet topology, consisting of 14 Tofino switches and 10 end-hosts, and conducted extensive experiments and evaluations. The results indicate that INT-MC incurs only 16% of the measurement overhead compared to existing network-wide telemetry solutions, while achieving nearly identical accuracy. Even under high-frequency measurements of 20 times per second, the bandwidth overhead of INT-MC is approximately 0.075% of the total bandwi

关键词： In-band network telemetry Matrix completion Network-wide telemetry Network measurement

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Allocating Public Goods via Dynamic Max-Min Fairness: Long-Run Behavior and Competitive Equilibria

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proceedings of the acm on measurement and analysis of computing systems 2025年第1期9卷 1-45页

作者： Onyeze, Chido Banerjee, Siddhartha Fikioris, Giannis Tardos, Eva Cornell Univ Ithaca NY 14850 USA

Dynamic max-min fair allocation (DMMF) is a simple and popular mechanism for the repeated allocation of a shared resource among competing agents: in each round, each agent can choose to request or not for the resource, which is then allocated to the requesting agent with the least number of allocations received till then. Recent work has shown that under DMMF, a simple threshold-based request policy enjoys surprisingly strong robustness properties, wherein each agent can realize a significant fraction of her optimal utility irrespective of how other agents' behave. While this goes some way in mitigating the possibility of a 'tragedy of the commons' outcome, the robust policies require that an agent defend against arbitrary (possibly adversarial) behavior by other agents. This however may be far from optimal compared to real world settings, where other agents are selfish optimizers rather than adversaries. Therefore, robust guarantees give no insight on how agents behave in an equilibrium, and whether outcomes are improved under one. Our work aims to bridge this gap by studying the existence and properties of equilibria under DMMF. To this end, we first show that despite the strong robustness guarantees of the threshold based strategies, no Nash equilibrium exists when agents participate in DMMF, each using some fixed threshold-based policy. On the positive side, however, we show that for the symmetric case, a simple data-driven request policy guarantees that no agent benefits from deviating to a different fixed threshold policy. In our proposed policy agents aim to match the historical allocation rate with a vanishing drift towards the rate optimizing overall welfare for all users. Furthermore, the resulting equilibrium outcome can be significantly better compared to what follows from the robustness guarantees. Our results are built on a complete characterization of the steady-state distribution under DMMF, as well as new techniques for analyzing strategic agent out

关键词： Game Theory Mechanism Design analysis of Random Processes Equilib- rium Computation

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Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning

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proceedings of the acm on measurement and analysis of computing systems 2023年第1期7卷 1-51页

作者： Zhang, Yizhou Qu, Guannan Xu, Pan Lin, Yiheng Chen, Zaiwei Wierman, Adam Tsinghua Univ Beijing Peoples R China Carnegie Mellon Univ Pittsburgh PA USA Duke Univ Durham NC USA CALTECH Pasadena CA USA

We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dimensionality and to reduce communication, we propose a Localized Policy Iteration (LPI) algorithm that provably learns a near-globally-optimal policy using only local information. In particular, we show that, despite restricting each agent's attention to only its.. -hop neighborhood, the agents are able to learn a policy with an optimality gap that decays polynomially in... In addition, we show the finite-sample convergence of LPI to the global optimal policy, which explicitly captures the trade-off between optimality and computational complexity in choosing kappa. Numerical simulations demonstrate the effectiveness of LPI.

关键词： Multi-agent reinforcement learning networked systems machine learning distributed algorithms

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EarComp 2023: Fourth International Workshop on Earable computing

EarComp 2023: Fourth International Workshop on Earable Compu...

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acm International Joint Conference on Pervasive and Ubiquitous computing / acm International Symposium on Wearable computing (UbiComp/ISWC)

作者： Ferlini, Andrea Montanari, Alessandro Roy, Nirupam Farrahi, Katayoun Nokia Bell Labs Cambridge England Univ Maryland College Pk MD USA Univ Southampton Southampton Hants England

ISBN: (纸本)9798400702006

The objective of the 4th acm International Workshop on Earable computing (EarComp 2023) is to provide an academic forum and bring together researchers, practitioners, and design experts to discuss how sensory earables technologies have and can complement human sensing research. It also aims to provide a launchpad for bold and visionary ideas and serve as a catalyst for advancements in this emerging new Earable computing research space.

关键词： Earable Human Sensing Behaviour analysis Data systems

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