Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems最新文献_第4页

Model Agnostic Time Series Analysis via Matrix Estimation 基于矩阵估计的模型不可知时间序列分析

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-06-20 DOI: 10.1145/3309697.3331479

Anish Agarwal, M. Amjad, D. Shah, Dennis Shen

{"title":"Model Agnostic Time Series Analysis via Matrix Estimation","authors":"Anish Agarwal, M. Amjad, D. Shah, Dennis Shen","doi":"10.1145/3309697.3331479","DOIUrl":"https://doi.org/10.1145/3309697.3331479","url":null,"abstract":"We propose an algorithm to impute and forecast a time series by transforming the observed time series into a matrix, utilizing matrix estimation to recover missing values and de-noise observed entries, and performing linear regression to make predictions. At the core of our analysis is a representation result, which states that for a large class of models, the transformed time series matrix is (approximately) low-rank. In effect, this generalizes the widely used Singular Spectrum Analysis (SSA) in the time series literature, and allows us to establish a rigorous link between time series analysis and matrix estimation. The key to establishing this link is constructing a Page matrix with non-overlapping entries rather than a Hankel matrix as is commonly done in the literature (e.g., SSA). This particular matrix structure allows us to provide finite sample analysis for imputation and prediction, and prove the asymptotic consistency of our method. Another salient feature of our algorithm is that it is model agnostic with respect to both the underlying time dynamics and the noise distribution in the observations. The noise agnostic property of our approach allows us to recover the latent states when only given access to noisy and partial observations a la a Hidden Markov Model; e.g., recovering the time-varying parameter of a Poisson process without knowing that the underlying process is Poisson. Furthermore, since our forecasting algorithm requires regression with noisy features, our approach suggests a matrix estimation based method---coupled with a novel, non-standard matrix estimation error metric---to solve the error-in-variable regression problem, which could be of interest in its own right. Through synthetic and real-world datasets, we demonstrate that our algorithm outperforms standard software packages (including R libraries) in the presence of missing data as well as high levels of noise.","PeriodicalId":268462,"journal":{"name":"Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122533641","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: 3

PROFET: Modeling System Performance and Energy Without Simulating the CPU 在不模拟CPU的情况下建模系统性能和能量

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-06-20 DOI: 10.1145/3309697.3331502

M. Radulovic, Rommel Sánchez Verdejo, P. Carpenter, Petar Radojkovic, B. Jacob, E. Ayguadé

引用次数: 5

Efficient Distributed Workload (Re-)Embedding 高效分布式工作负载(重)嵌入

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-26 DOI: 10.1145/3309697.3331503

M. Henzinger, S. Neumann, S. Schmid

引用次数: 16

App in the Middle: Demystify Application Virtualization in Android and its Security Threats 应用在中间:揭开Android应用虚拟化及其安全威胁的神秘面纱

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-26 DOI: 10.1145/3309697.3331517

Lei Zhang, Zhemin Yang, Yuyu He, Mingqi Li, Sen Yang, Min Yang, Yuan Zhang, Zhiyun Qian

{"title":"App in the Middle: Demystify Application Virtualization in Android and its Security Threats","authors":"Lei Zhang, Zhemin Yang, Yuyu He, Mingqi Li, Sen Yang, Min Yang, Yuan Zhang, Zhiyun Qian","doi":"10.1145/3309697.3331517","DOIUrl":"https://doi.org/10.1145/3309697.3331517","url":null,"abstract":"Customizability is a key feature of the Android operating system that differentiates it from Apple's iOS. One concrete feature that gaining popularity is called \"app virtualization''. This feature allows multiple copies of the same app to be installed and opened simultaneously (e.g., with multiple accounts logged in). Virtualization frameworks are used by more than 100 million users worldwide. As with any new system features, we are interested in two aspects: (1) whether the feature itself introduces security risks and (2) whether the feature is abused for unintended purposes. This paper conducts a systematic study on the two aspects of the app virtualization techniques. With a thorough study of 32 popular virtualization frameworks from Google Play, we identify seven areas of potential attack vectors and find that most of the frameworks are susceptible to them. By deeply investigating their ecosystem, we show, with demonstrations, that attackers can easily distribute malware that takes advantage of these attack vectors. In addition, we show that the same virtualization techniques are also abused by malware as an alternative and easy-to-use repackaging mechanism. To this end, we design and implement a new app repackage detector. After scanning 250,145 apps from app markets, it finds 164 repackaged apps that attempt to steal user credentials and private data.","PeriodicalId":268462,"journal":{"name":"Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125069178","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: 17

Crystal Gazer: Profile-Driven Write-Rationing Garbage Collection for Hybrid Memories Crystal Gazer:混合内存的配置文件驱动的写配给垃圾收集

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-26 DOI: 10.1145/3309697.3331492

Shoaib Akram, Jennifer B. Sartor, K. McKinley, L. Eeckhout

{"title":"Crystal Gazer: Profile-Driven Write-Rationing Garbage Collection for Hybrid Memories","authors":"Shoaib Akram, Jennifer B. Sartor, K. McKinley, L. Eeckhout","doi":"10.1145/3309697.3331492","DOIUrl":"https://doi.org/10.1145/3309697.3331492","url":null,"abstract":"Emerging non-volatile memory (NVM) technologies offer greater capacity than DRAM. Unfortunately, production NVM exhibits high latency and low write endurance. Hybrid memory combines DRAM and NVM to deliver greater capacity, low latency, high en- durance, and low energy consumption. Write-rationing garbage col- lection mitigates NVM wear-out by placing highly-written objects in DRAM and the rest in NVM. Existing write-rationing garbage collectors dynamically monitor object writes to place highly writ- ten objects in DRAM. Unfortunately, monitoring writes incurs a non-negligible performance overhead. This work proposes Crystal Gazer, profile-driven write-rationing garbage collection for hybrid memories. Allocation sites are statically profiled, and highly writ- ten objects are predicted based on previous program executions. Unlike prior work, this paper exposes a Pareto trade-off between DRAM usage and NVM lifetime. Experimental results on an emula- tion platform show that Crystal Gazer eliminates the performance overhead of dynamic monitoring, while reducing more NVM writes than state-of-the-art write-rationing garbage collectors.","PeriodicalId":268462,"journal":{"name":"Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116760637","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: 9

Hyper-Scalable JSQ with Sparse Feedback 具有稀疏反馈的超可伸缩JSQ

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-06 DOI: 10.1145/3311075

Mark van der Boor, S. Borst, J. V. Leeuwaarden

{"title":"Hyper-Scalable JSQ with Sparse Feedback","authors":"Mark van der Boor, S. Borst, J. V. Leeuwaarden","doi":"10.1145/3311075","DOIUrl":"https://doi.org/10.1145/3311075","url":null,"abstract":"Load balancing algorithms play a vital role in enhancing performance in data centers and cloud networks. Due to the massive size of these systems, scalability challenges, and especially the communication overhead associated with load balancing mechanisms, have emerged as major concerns. Motivated by these issues, we introduce and analyze a novel class of load balancing schemes where the various servers provide occasional queue updates to guide the load assignment. We show that the proposed schemes strongly outperform JSQ(d) strategies with comparable communication overhead per job, and can achieve a vanishing waiting time in the many-server limit with just one message per job, just like the popular JIQ scheme. The proposed schemes are particularly geared however towards the sparse feedback regime with less than one message per job, where they outperform corresponding sparsified JIQ versions. We investigate fluid limits for synchronous updates as well as asynchronous exponential update intervals. The fixed point of the fluid limit is identified in the latter case, and used to derive the queue length distribution. We also demonstrate that in the ultra-low feedback regime the mean stationary waiting time tends to a constant in the synchronous case, but grows without bound in the asynchronous case.","PeriodicalId":268462,"journal":{"name":"Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129594837","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: 17

Learning Graphs from Noisy Epidemic Cascades 从噪声流行病级联中学习图

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-06 DOI: 10.1145/3309697.3331511

Jessica Hoffmann, C. Caramanis

引用次数: 8

Improved Queue-Size Scaling for Input-Queued Switches via Graph Factorization 基于图分解的输入排队交换机的改进队列大小缩放

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-03-01 DOI: 10.1017/apr.2020.31

Jiaming Xu, Y. Zhong

引用次数: 4

Network Resilience Assessment via QoS Degradation Metrics: An Algorithmic Approach 基于QoS退化度量的网络弹性评估:一种算法方法

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2019-02-05 DOI: 10.1145/3309697.3331470

Lan N. Nguyen, M. Thai

引用次数: 3

Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs 相关Erdős-Rényi图对齐的规范化标注算法分析

Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2018-04-25 DOI: 10.1145/3309697.3331505

Osman Emre Dai, Daniel Cullina, N. Kiyavash, M. Grossglauser

{"title":"Analysis of a Canonical Labeling Algorithm for the Alignment of Correlated Erdős-Rényi Graphs","authors":"Osman Emre Dai, Daniel Cullina, N. Kiyavash, M. Grossglauser","doi":"10.1145/3309697.3331505","DOIUrl":"https://doi.org/10.1145/3309697.3331505","url":null,"abstract":"Graph alignment in two correlated random graphs refers to the task of identifying the correspondence between vertex sets of the graphs. Recent results have characterized the exact information-theoretic threshold for graph alignment in correlated Erdős-Rényi graphs. However, very little is known about the existence of efficient algorithms to achieve graph alignment without seeds. In this work we identify a region in which a straightforward $calO(n^11/5 łog n )$-time canonical labeling algorithm, initially introduced in the context of graph isomorphism, succeeds in aligning correlated Erdős-Rényi graphs. The algorithm has two steps. In the first step, all vertices are labeled by their degrees and a trivial minimum distance alignment (i.e., sorting vertices according to their degrees) matches a fixed number of highest degree vertices in the two graphs. Having identified this subset of vertices, the remaining vertices are matched using a alignment algorithm for bipartite graphs. Finally, we show that the implementation of a variant of this algorithm allows for the efficient alignment of large graphs under limited noise.","PeriodicalId":268462,"journal":{"name":"Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129966460","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: 31