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Poster: Towards cryptographic agility in end-to-end encryption systems for computer generated telemetry data. 24

Poster: Towards cryptographic agility in end-to-end encrypti...

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25th International Workshop on Mobile computing systems and Applications (HOTMOBILE)

作者： Silonosov, Alexandr Baranovskyi, Oleksii Henesey, Lawrence Blekinge Inst Technol Karlskrona Sweden

ISBN: (纸本)9798400704970

The research presented focuses on cryptographic-agility for End-to-End Encryption systems (E2EE) that could be implemented for telemetry data *** recent report 1 by Microsoft after a security incident, describes the consequences that lead to encryption key leakage from telemetry data of highly protected production system. Internet of Things (IoT) and mobile devices constantly produce telemetry data which contains sensitive information. The data partially belongs to vendor, but IoT consumer's consent is needed to access such data for troubleshooting or forensic analysis. Goyal et al [2] proposed Attribute Based Encryption (ABE) as a solution for legitimately access the audit log contents by engineering team.

关键词： Internet of things

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CityScouter: Exploring the Atmosphere of Urban Landscapes and Visitor Demands with Multimodal Data

CityScouter: Exploring the Atmosphere of Urban Landscapes an...

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

作者： Kubota, Yuki Anno, Soto Taniguchi, Tomomi Miyazaki, Kosei Tsujimoto, Akira Yasuda, Hiraki Sakamoto, Takayuki Ishikawa, Takaaki Tsubouchi, Kota Shimosaka, Masamichi Tokyo Inst Technol Tokyo Japan Taniguchi Tomomi Design Tokyo Japan Hyogo Univ Akashi Hyogo Japan Nikken Sekkei Ltd Tokyo Japan Yahoo Japan Corp Tokyo Japan

ISBN: (纸本)9798400702006

This paper proposes a novel demo application named CityScouter that utilizes multimodal data to analyze various aspects of urban characteristics quantitatively. Existing studies have proposed systems to examine either the physical characteristics of cities or the nature of people residing there. However, there is a lack of systems that analyze the characteristics of cities from both the physical and the residents' aspects. CityScouter addresses this challenge by leveraging computer vision technologies to quantify the quality of the urban landscape atmosphere and combining it with location information and user search history to reveal the desires of people visiting the area. The application is user-friendly and compatible with mobile devices, enabling users to conveniently enhance their understanding of cities while exploring them. Additionally, we provide reviews from urban development experts, offering insights into the applicability of our application. Furthermore, we showcase the usefulness and user experience of CityScouter through live demonstrations at the conference venue.

关键词： Urban ladscape analysis Search history Urban planning

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Enhanced Transportation and Locomotion Mode Recognition through Difference and Variance analysis In Inertial Sensing Data 24

Enhanced Transportation and Locomotion Mode Recognition thro...

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

作者： Hoang Khang Phan Tu Nhat Khang Nguyen Khuong Cong Duy Nguyen Nguyen Phat Vo Anh Tuan Ha Nhat Tan Le Vietnam Natl Univ Ho Chi Minh city Univ Technol Dept Biomed Engn Ho Chi Minh City Vietnam Vietnam Natl Univ Ho Chi Minh city Univ Technol Fac Comp Sci & Engn Ho Chi Minh City Vietnam

ISBN: (纸本)9798400710582

This paper presents the approach and results of Team Bun-Bo for the Sussex-Huawei Locomotion-Transportation (SHL) recognition challenge focusing on human activity detection. The objective of the challenge is to classify 8 modes of transportation-standing still, walking, running, biking, car, bus, train, and subway-using data collected from Inertial measurement Units (IMUs). Our approach involved extensive feature extraction from raw and processed kinematic indices, including acceleration, gyroscope, and magnetic data. Specific features included total acceleration across 3 axes and the horizontal plane, angles between different sensor axes, and successive differences of kinematic indices. We applied three ensemble boosting models under varying training and validation scenarios. Our findings highlight the Extreme Gradient Boosting Classifier (XGB), which achieved superior performance with an accuracy of 92% and an F1-score of 93%, outperforming other classifiers by margins ranging from 5% to 15%. This study underscores the effectiveness of advanced feature extraction techniques and ensemble learning models in enhancing the accuracy of transportation mode recognition systems based on IMU data.

关键词： Transportation and Locomotion Recognition Sussex-Huawei Locomotion Challenge 2024 Machine learning Inertial measurement Unit Smartphone data

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An Incremental Multi-Level, Multi-Scale Approach to Assessment of Multifidelity HPC systems

An Incremental Multi-Level, Multi-Scale Approach to Assessme...

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2024 Workshops of the International Conference for High Performance computing, Networking, Storage and analysis, SC Workshops 2024

作者： Shilpika, Shilpika Lusch, Bethany Vishwanath, Venkatram Papka, Michael E. Argonne National Laboratory Argonne Leadership Computing Facility United States Department of Computer Science University of Illinois Chicago United States

ISBN: (纸本)9798350355543

With the growing complexity in architecture and the size of large-scale computing systems, monitoring and analyzing system behavior and events has become daunting. Monitoring data amounting to terabytes per day are collected by sensors housed in these massive systems at multiple fidelity levels and varying temporal resolutions. In this work, we develop an incremental version of multiresolution dynamic mode decomposition (mrDMD), which converts high-dimensional data to spatial-temporal patterns at varied frequency ranges. Our incremental implementation of the mrDMD algorithm (I-mrDMD) promptly reveals valuable information in the massive environment log dataset, which is then visually aligned with the processed hardware and job log datasets through our generalizable rack visualization using D3 visualization integrated into the Jupyter Notebook interface. We demonstrate the efficacy of our approach with two use scenarios on a real-world dataset from a Cray XC40 supercomputer, Theta. © 2024 IEEE.

关键词： Dynamic mode decomposition high performance computing incremental analysis mrDMD online analysis scalability visualization

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Improving the Efficiency of In-Memory-computing Macro with a Hybrid Analog-Digital computing Mode for Lossless Neural Network Inference 24

Improving the Efficiency of In-Memory-Computing Macro with a...

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61st acm/IEEE Design Automation Conference, DAC 2024

作者： Zheng, Qilin Li, Ziru Ku, Jonathan Wang, Yitu Taylor, Brady Fan, Deliang Chen, Yiran Duke University United States Johns Hopkins University United States

ISBN: (纸本)9798400706011

Analog in-memory-computing (IMC) is an attractive technique with a higher energy efficiency to process machine learning workloads. However, the analog computing scheme suffers from large interface circuit overhead. In this work, we propose a macro with a hybrid analog-digital mode computation to reduce the precision requirement of the interface circuit. Considering the distribution of the multiplication and accumulation (MAC) value, we propose a nonlinear transfer function of the computing circuits by only accurately computing low MAC value in the analog domain with a digital mode to deal with the high MAC value with smaller possibility. Silicon measurement results show that the proposed macro could achieve 160 GOPS/mm2 area efficiency and 25.5 TOPS/W for 8b/8b matrix computation. The architectural-level evaluation for real workloads shows that the proposed macro can achieve up to 2.92× higher energy efficiency than conventional analog IMC designs. © 2024 Copyright held by the owner/author(s).

关键词： Static random access storage

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On the Dynamics of Single-Orbit Requester-Provider systems 23

On the Dynamics of Single-Orbit Requester-Provider Systems

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26th acm International Conference on Modelling, analysis, and Simulation of Wireless and Mobile systems (MSWiM)

作者： Cordero-Fuertes, Juan-Antonio Ecole Polytech Lab Informat Palaiseau France

ISBN: (纸本)9798400703669

This paper considers decentralized systems of multiple agents that interact in order to perform distributed computing or efficient information transfer in variant, constrained environments. These systems appear in various relevant use cases, including reliable multicast distribution, or dynamic resource allocation in systems in the Internet edge (datacenters, IOT deployments). This paper introduces an abstract, mathematical model, that allows to study analytically the behavior of these systems, as a set of interacting requesters and providers. The paper describes system orbits, and concentrates on the study of single-orbit systems. Ergodicity of system behavior in the single-orbit case is proved, and a full description of the stationary system behavior is derived. Closed expressions of the stationary distribution of requester decisions are provided. Analytical results are validated through extensive simulations. These single-orbit results are a necessary step for the analysis and further optimization of dynamic performance of these systems.

关键词： networking dynamic systems multi-agent system content distribution adaptive stochastic stability equilibrium mathematical model simulations

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A Comprehensive Benchmarking analysis of Fault Recovery in Stream Processing Frameworks 18

A Comprehensive Benchmarking Analysis of Fault Recovery in S...

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18th International Conference on Distributed and Event-Based systems (DEBS)

作者： Vogel, Adriano Henning, Soren Perez-Wohlfeil, Esteban Ertl, Otmar Rabiser, Rick Johannes Kepler Univ Linz JKU Dynatrace Coinnovat Lab Linz Austria Dynatrace LLC Dynatrace Res Linz Austria Johannes Kepler Univ Linz LIT CPS Lab Linz Austria

ISBN: (纸本)9798400704437

Nowadays, several software systems rely on stream processing architectures to deliver scalable performance and handle large volumes of data in near real-time. Stream processing frameworks facilitate scalable computing by distributing the application's execution across multiple machines. Despite performance being extensively studied, the measurement of fault tolerance-a key feature offered by stream processing frameworks-has still not been measured properly with updated and comprehensive testbeds. Moreover, the impact that fault recovery can have on performance is mostly ignored. This paper provides a comprehensive analysis of fault recovery performance, stability, and recovery time in a cloud-native environment with modern open-source frameworks, namely Flink, Kafka Streams, and Spark Structured Streaming. Our benchmarking analysis is inspired by chaos engineering to inject failures. Generally, our results indicate that much has changed compared to previous studies on fault recovery in distributed stream processing. In particular, the results indicate that Flink is the most stable and has one of the best fault recovery. Moreover, Kafka Streams shows performance instabilities after failures, which is due to its current rebalancing strategy that can be suboptimal in terms of load balancing. Spark Structured Streaming shows suitable fault recovery performance and stability, but with higher event latency. Our study intends to (i) help industry practitioners in choosing the most suitable stream processing framework for efficient and reliable executions of data-intensive applications;(ii) support researchers in applying and extending our research method as well as our benchmark;(iii) identify, prevent, and assist in solving potential issues in production deployments.

关键词： benchmarking fault tolerance performance stream processing

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EnTurbo: Accelerate Confidential Serverless computing via Parallelizing Enclave Startup Procedure 24

EnTurbo: Accelerate Confidential Serverless Computing via Pa...

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61st acm/IEEE Design Automation Conference, DAC 2024

作者： Zhu, Yifan Li, Peinan Bai, Yunkai Huang, Yubiao Wang, Shiwen Wang, Xingbin Meng, Dan Hou, Rui Key Laboratory of Cyberspace Security Defense Institute of Information Engineering Cas China School of Cyber Security University of Chinese Academy of Sciences China

ISBN: (纸本)9798400706011

Serverless computing has gained widespread attention, and Trusted Execution Environments (TEEs) are well-suited for safeguarding user privacy. However, the additional startup procedure introduced by TEEs imposes considerable performance overhead on confidential serverless workloads. This paper introduces a novel parallelized enclave startup design, EnTurbo, which eliminates the integrity dependence of the enclave startup procedure, accelerating it while ensuring its security. Additionally, EnTurbo parallelizes the measurement procedure, enabling multi-thread measurement for acceleration with provable security. We evaluate EnTurbo by running confidential serverless workloads on SGX simulation mode. Results show that EnTurbo effectively speeds up enclave serverless by 1.42x-6.48x (SGXv1) and 1.33x-3.76x (SGXv2). © 2024 Copyright held by the owner/author(s).

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SIGMETRICS/PERFORMANCE 2024 - Abstracts of the 2024 acm SIGMETRICS/IFIP PERFORMANCE Joint International Conference on measurement and Modeling of Computer systems

SIGMETRICS/PERFORMANCE 2024 - Abstracts of the 2024 ACM SIGM...

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2024 acm SIGMETRICS/IFIP Performance Conference on measurement and Modeling of Computer systems, SIGMETRICS/PERFORMANCE 2024

ISBN: (纸本)9798400706240

The proceedings contain 52 papers. The topics discussed include: approximations to study the impact of the service discipline in systems with redundancy;multi-dimensional state space collapse in non-complete resource pooling scenarios;strongly tail-optimal scheduling in the light-tailed M/G/1;heavy-traffic optimal size- and state-aware dispatching;MetaVRadar: measuring metaverse virtual reality network activity;analysis of false negative rates for recycling bloom filters (yes, they happen!);invertible bloom lookup tables with listing guarantees;lightweight acquisition and ranging of flows in the data plane;agents of autonomy: a systematic study of robotics on modern hardware;automated backend allocation for multi-model, on-device ai inference;and learning the optimal control for evolving systems with converging dynamics.

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Privee: A Wearable for Real-Time Bladder Monitoring System

Privee: A Wearable for Real-Time Bladder Monitoring System

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

作者： Zhang, Ruoyu Fang, Ruijie Fang, Chongzhou Homayoun, Houman Goncu-Berk, Gozde Univ Calif Davis Davis CA 95616 USA

ISBN: (纸本)9798400702006

Urinary incontinence (UI) is a prevalent condition affecting millions of individuals worldwide, leading to various physical, social, and psychological challenges that diminish their quality of life. Current management approaches primarily focus on containment rather than proactive monitoring and warning systems. This paper presents the development and evaluation of a novel wearable technology called Privee, designed as an unobtrusive undergarment to monitor bladder fullness in real-time. Privee utilizes e-textile-based bioimpedance spectroscopy technology, which noninvasively assesses bladder fullness by analyzing the electrical properties of body tissues and fluids. The undergarment incorporates eight embroidered electrodes and textile transmission lines seamlessly integrated into the fabric. By continuously monitoring the bioimpedance signals from the bladder, Privee provides real-time information about the bladder's fullness level. This data is processed using a specialized algorithm to estimate the need for urination. The noninvasive nature of Privee eliminates the discomfort and risks associated with invasive monitoring methods, offering a user-friendly and convenient solution for individuals with UI, overactive bladder, or post-operative care needs. This innovative technology has the potential to improve patients' quality of life and optimize healthcare costs associated with UI management.

关键词： Internet of Things(IoT) Bio-Impedance measurement Wearable Device Non-Invasive Bladder Real-Time Monitoring

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