Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems最新文献

Argus: Predictable Millimeter-Wave Picocells with Vision and Learning Augmentation 阿格斯:具有视觉和学习增强功能的可预测毫米波皮细胞

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522642

Hem Regmi, Sanjib Sur

{"title":"Argus: Predictable Millimeter-Wave Picocells with Vision and Learning Augmentation","authors":"Hem Regmi, Sanjib Sur","doi":"10.1145/3489048.3522642","DOIUrl":"https://doi.org/10.1145/3489048.3522642","url":null,"abstract":"We propose Argus, a system to enable millimeter-wave (mmWave) deployers to quickly complete site-surveys without sacrificing the accuracy and effectiveness of thorough network deployment surveys. Argus first models the mmWave reflection profile of an environment, considering dominant reflectors, and then uses this model to find locations that maximize the usability of the reflectors. The key component in Argus is an effective deep learning model that can map the visual data to the mmWave signal reflections of an environment and can accurately predict mmWave signal profile at any unobserved locations. It allows Argus to find the best picocell locations to provide maximum coverage and also lets users self-localize accurately anywhere in the environment. Furthermore, Argus allows mmWave picocells to predict device's orientation accurately and enables object tagging and retrieval for VR/AR applications. We implement and validate Argus on two different buildings consisting of multiple different indoor environments. However, the generalization capability of Argus can easily update the model for unseen environments; so, Argus can be deployed to any indoor environment with little or no model fine-tuning.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123297341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Learning To Maximize Welfare with a Reusable Resource 学会利用可重复使用的资源最大化福利

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530960

Matthew Faw, O. Papadigenopoulos, C. Caramanis, S. Shakkottai

引用次数: 1

Monetizing Spare Bandwidth: The Case of Distributed VPNs 备用带宽货币化:分布式vpn的案例

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530966

Yunming Xiao, Matteo Varvello, A. Kuzmanovic

{"title":"Monetizing Spare Bandwidth: The Case of Distributed VPNs","authors":"Yunming Xiao, Matteo Varvello, A. Kuzmanovic","doi":"10.1145/3489048.3530966","DOIUrl":"https://doi.org/10.1145/3489048.3530966","url":null,"abstract":"Residential Internet speeds have been rapidly increasing, reaching averages of ∼ 100 Mbps in most developed countries. Several studies have shown that users have way more bandwidth than they need, only using about 20-30% on a regular day. Several systems exploit this trend by enabling users to monetize their spare bandwidth, e.g., by sharing their WiFi connection or by participating in distributed proxy or VPN (dVPN) services. Despite the proliferation of such systems, little is known on how such marketplaces operate, what are the key factors that determine the price of the spare bandwidth, and how such prices differ worldwide. In this work, we shed some light on this topic using dVPNs as a use-case. We start by formalizing the problem of bandwidth monetization as an optimization between a buyer’s cost and seller’s income. Next, we explore three popular dVPNs (Mysterium, Sentinel, and Tachyon) using both active and passive measurements. We find that dVPNs have a large and growing footprint, and offer comparable performance to their centralized counterpart. We identify Mysterium (in the US) as the most concrete realization of a bandwidth marketplace, for which we derive a value of spare Internet bandwidth ranging between 11 and 14 cents per GB. We also show that both buyers and sellers utilize ad-hoc “rules-of-thumb” when choosing their prices, which results in a sub-optimal marketplace. By applying our optimization, a seller’s income can be tripled by setting a price lower than the default one which allows to attract more buyers. These observations motivate us to create RING , a first and concrete system which helps sellers to automatically adjust their prices and traffic volumes across multiple marketplaces.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124482567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MalRadar: Demystifying Android Malware in the New Era MalRadar:揭秘新时代的Android恶意软件

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530973

Liu Wang, Haoyu Wang, Ren He, Ran Tao, Guozhu Meng, Xiapu Luo, Xuanzhe Liu

{"title":"MalRadar: Demystifying Android Malware in the New Era","authors":"Liu Wang, Haoyu Wang, Ren He, Ran Tao, Guozhu Meng, Xiapu Luo, Xuanzhe Liu","doi":"10.1145/3489048.3530973","DOIUrl":"https://doi.org/10.1145/3489048.3530973","url":null,"abstract":"A reliable and up-to-date malware dataset is critical to evaluate the effectiveness of malware detection approaches. Although there are several widely-used malware benchmarks in our community (e.g., MalGenome, Drebin, Piggybacking and AMD, etc.), these benchmarks face several limitations including out-of-date, size, coverage, and reliability issues, etc. In this paper, we first make effort to create MalRadar, a growing and up-to-date Android malware dataset using the most reliable way, i.e., by collecting malware based on the analysis reports of security experts. We have crawled all the mobile security related reports released by ten leading security companies, and used an automated approach to extract and label the useful ones describing new Android malware and containing Indicators of Compromise (IoC) information. We have successfully compiled MalRadar, a dataset that contains 4,534 unique Android malware samples (including both apks and metadata) released from 2014 to April 2021 by the time of this paper, all of which were manually verified by security experts with detailed behavior analysis. Then we characterize the MalRadar dataset from malware distribution channels, app installation methods, malware activation, malicious behaviors and anti-analysis techniques. We further investigate the malware evolution over the last decade. At last, we measure the effectiveness of commercial anti-virus engines and malware detection techniques on detecting malware in MalRadar. Our dataset can be served as the representative Android malware benchmark in the new era, and our observations can positively contribute to the community and boost a series of studies on mobile security.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"26 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131018674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

NURA: A Framework for Supporting Non-Uniform Resource Accesses in GPUs NURA:支持gpu中非统一资源访问的框架

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522656

Sina Darabi, Negin Mahani, Hazhir Bakhishi, Ehsan Yousefzadeh-Asl-Miandoab, Mohammad Sadrosadati, H. Sarbazi-Azad

{"title":"NURA: A Framework for Supporting Non-Uniform Resource Accesses in GPUs","authors":"Sina Darabi, Negin Mahani, Hazhir Bakhishi, Ehsan Yousefzadeh-Asl-Miandoab, Mohammad Sadrosadati, H. Sarbazi-Azad","doi":"10.1145/3489048.3522656","DOIUrl":"https://doi.org/10.1145/3489048.3522656","url":null,"abstract":"Multi-application execution in Graphics Processing Units (GPUs), a promising way to utilize GPU resources, is still challenging. Some pieces of prior work (e.g. spatial multitasking) have limited opportunity to improve resource utilization, while others, e.g. simultaneous multi-kernel, provide fine-grained resource sharing at the price of unfair execution. This paper proposes a new multi-application paradigm for GPUs, called NURA, that provides high potential to improve resource utilization and ensure fairness and Quality-of-Service(QoS). The key idea is that each streaming multiprocessor (SM) executes the Cooperative Thread Arrays (CTAs) that belong to only one application (similar to spatial multi-tasking) and shares its unused resources with the SMs running other applications demanding more resources. NURA handles resource sharing process mainly using a software approach to provide simplicity, low hardware overhead, and flexibility.We also perform some hardware modifications as an architectural support for our software-based proposal. Our conservative analysis reveals that the hardware area overhead of our proposal is less than 1.07% with respect to the whole GPU die. Our experimental results over various mixes of GPU workloads show that NURA improves throughput by 26% compared to the state-of-the-art spatial multi-tasking, on average, while meeting QoS targets. In terms of fairness, NURA has almost similar results to spatial multitasking, while it outperforms simultaneous multi-kernel by 76%, on average.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128864154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Hierarchical Learning Algorithms for Multi-scale Expert Problems 多尺度专家问题的层次学习算法

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530967

L. Yang, Y. Chen, M. Hajiesmaili, M. Herbster, D. Towsley

引用次数: 0

Understanding the Practices of Global Censorship through Accurate, End-to-End Measurements 通过精确的端到端测量来理解全球审查的做法

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522640

Lin Jin, Shuai Hao, Haining Wang, Chase Cotton

{"title":"Understanding the Practices of Global Censorship through Accurate, End-to-End Measurements","authors":"Lin Jin, Shuai Hao, Haining Wang, Chase Cotton","doi":"10.1145/3489048.3522640","DOIUrl":"https://doi.org/10.1145/3489048.3522640","url":null,"abstract":"It is challenging to conduct a large scale Internet censorship measurement, as it involves triggering censors through artificial requests and identifying abnormalities from corresponding responses. Due to the lack of ground truth on the expected responses from legitimate services, previous studies typically require a heavy, unscalable manual inspection to identify false positives while still leaving false negatives undetected. In this paper, we propose Disguiser, a novel framework that enables end-to-end measurement to accurately detect the censorship activities and reveal the censor deployment without manual efforts. The core of Disguiser is a control server that replies with a static payload to provide the ground truth of server responses. As such, we send requests from various types of vantage points across the world to our control server, and the censorship activities can be recognized if a vantage point receives a different response. In particular, we design and conduct a cache test to pre-exclude the vantage points that could be interfered by cache proxies along the network path. Then we perform application traceroute towards our control server to explore censors' behaviors and their deployment. With Disguiser, we conduct 58 million measurements from vantage points in 177 countries. We observe 292 thousand censorship activities that block DNS, HTTP, or HTTPS requests inside 122 countries, achieving a 106 false positive rate and zero false negative rate. Furthermore, Disguiser reveals the censor deployment in 13 countries.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"51 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116323637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Comprehensive Empirical Study of Query Performance Across GPU DBMSes GPU数据库查询性能的综合实证研究

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522644

Young-Kyoon Suh, Jun Young An, Byungchul Tak, Gap-Joo Na

{"title":"A Comprehensive Empirical Study of Query Performance Across GPU DBMSes","authors":"Young-Kyoon Suh, Jun Young An, Byungchul Tak, Gap-Joo Na","doi":"10.1145/3489048.3522644","DOIUrl":"https://doi.org/10.1145/3489048.3522644","url":null,"abstract":"In recent years, GPU database management systems (DBMSes) have rapidly become popular largely due to their remarkable acceleration capability obtained through extreme parallelism in query evaluations. However, there has been relatively little study on the characteristics of these GPU DBMSes for a better understanding of their query performance in various contexts. To fill this gap, we have conducted a rigorous empirical study to identify such factors and to propose a structural causal model, including key factors and their relationships, to explicate the variances of the query execution times on the GPU DBMSes. To test the model, we have designed and run comprehensive experiments and conducted in-depth statistical analyses on the obtained data. As a result, our model achieves about 77% amount of variance explained on the query time and indicates that reducing kernel time and data transfer time are the key factors to improve the query time. Also, our results show that the studied systems still need to resolve several concerns such as bounded processing within GPU memory, lack of rich query evaluation operators, limited scalability, and GPU under-utilization.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129709473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expert-Calibrated Learning for Online Optimization with Switching Costs 具有切换成本的在线优化的专家校准学习

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530961

Peng Li, Jianyi Yang, Shaolei Ren

引用次数: 2

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search 一个代理设备就足以实现硬件感知的神经结构搜索

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522631

Bingqian Lu, Jianyi Yang, Weiwen Jiang, Yiyu Shi, Shaolei Ren

引用次数: 2