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检索条件"任意字段=Abstracts of the 2018 ACM International Conference on Measurement and Modeling of Computer Systems"

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Kernel vs. user-level networking: Don't throw out the stack with the interrupts 24

Kernel vs. user-level networking: Don't throw out the stack ...

引用

2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Cai, Peter Karsten, Martin David R. Cheriton School of Computer Science University of Waterloo WaterlooON Canada

ISBN: (纸本)9798400706240

This paper reviews the performance characteristics of network stack processing for communication-heavy server applications. Recent literature often describes kernel-bypass and user-level networking as a silver bullet to attain substantial performance improvements, but without providing a comprehensive understanding of how exactly these improvements come about. We identify and quantify the direct and indirect costs of asynchronous hardware interrupt requests (IRQ) as a major source of overhead. While IRQs and their handling have a substantial impact on the effectiveness of the processor pipeline and thereby the overall processing efficiency, their overhead is difficult to measure directly when serving demanding workloads. This paper presents an indirect methodology to assess IRQ overhead by constructing preliminary approaches to reduce the impact of IRQs. While these approaches are not suitable for general deployment, their corresponding performance observations indirectly confirm the conjecture. Based on these findings, a small modification of a vanilla Linux system is devised that improves the efficiency and performance of traditional kernel-based networking significantly, resulting in up to 45% increased throughput without compromising tail latency. In case of server applications, such as web servers or Memcached, the resulting performance is comparable to using kernel-bypass and user-level networking when using stacks with similar functionality and flexibility. © 2024 Copyright held by the owner/author(s).

关键词： Efficiency

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Proceedings of NetEcon 2018: The 13th Workshop on the Economics of Networks, systems, and Computation - In conjunction with acm SIGMETRICS 2018: The acm SIGMETRICS international conference on measurement and modeling of computer systems

Proceedings of NetEcon 2018: The 13th Workshop on the Econom...

引用

13th Workshop on the Economics of Networks, systems, and Computation, NetEcon 2018 - In conjunction with the acm SIGMETRICS international conference on measurement and modeling of computer systems, acm SIGMETRICS 2018

ISBN: (纸本)9781450359160

The proceedings contain 9 papers. The topics discussed include: are data caps reasonable?;are data caps reasonable?;a winners-take-all incentive mechanism for crowd-powered systems;relating metric distortion and fairness of social choice rules;disaggregating user evaluations using the shapley value;optimal pricing for a peer-to-peer sharing platform under network externalities;diffusion in random networks: impact of degree distribution;economics of UAV-provided mobile services;and signaling in online retail: efficacy of public signals.

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Heavy-traffic optimal size- and state-aware dispatching 24

Heavy-traffic optimal size- and state-aware dispatching

引用

2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Xie, Runhan Grosof, Isaac Scully, Ziv Department of Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA United States Carnegie Mellon University Computer Science Department PittsburghPA United States Georgia Institute of Technology School of Industrial and Systems Engineering AtlantaGA United States School of Operations Research and Information Engineering Cornell University IthacaNY United States

ISBN: (纸本)9798400706240

We study the problem of dispatching jobs to multiple FCFS (First-Come, First-Served) queues. We consider the case where the dispatcher is size-aware, meaning it learns the size (i.e. service time) of each job as it arrives;and state-aware, meaning it always knows the amount of work (i.e. total remaining service time) at each queue. While size- and state-aware dispatching to FCFS queues has been extensively studied, little is known about optimal dispatching for the objective of minimizing mean delay. In this work, we propose the first size- and state-aware dispatching policy, called CARD (Controlled Asymmetry Reduces Delay), that provably minimizes mean delay in heavy traffic. This work summarizes our full paper. © 2024 Copyright held by the owner/author(s).

关键词： Queueing theory

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Continuous query-based data trading 24

Continuous query-based data trading

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2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Cheng, Jin Ding, Ningning Lui, John C.S. Huang, Jianwei School of Science and Engineering Shenzhen Institute of Artificial Intelligence and Robotics for Society The Chinese University of Hong Kong Shenzhen Shenzhen China Department of Electrical and Computer Engineering Northwestern University Evanston United States Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9798400706240

In the era of big data, traditional data trading methods designed for one-time queries on static databases fail to meet the demands of continuous query-based trading on streaming data, often resulting in repeated and inaccurate charges due to neglecting computation sharing in continuous query execution. To address this, we introduce CQTrade, the first trading framework tailored for continuous queries, which incorporates computation sharing across different time windows and queries, enhancing integration with existing trading systems. Our contributions include a theoretical analysis of computation-sharing techniques, the development of a general optimization problem to maximize seller revenue adaptable to various techniques, and the proposal of a branch-and-price algorithm to handle the problem's complexity. Our evaluation shows that the proposed framework improves the success rate of data trading by 12.8% and boosts the seller's revenue by an average of 28.7%, compared to the one-time query-based data trading methods used in the current data market. © 2024 Copyright held by the owner/author(s).

关键词： Integer programming

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Lightweight acquisition and ranging of flows in the data plane 24

Lightweight acquisition and ranging of flows in the data pla...

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2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Monterubbiano, Andrea Langlet, Jonatan Walzer, Stefan Antichi, Gianni Reviriego, Pedro Pontarelli, Salvatore University of Rome-Sapienza Rome Italy Queen Mary University of London London United Kingdom Cologne University Cologne Germany Politecnico di Milano Milan Italy ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain

ISBN: (纸本)9798400706240

As networks get more complex, the ability to track almost all the flows is becoming of paramount importance. This is because we can then detect transient events impacting only a subset of the traffic. Solutions for flow monitoring exist, but it is getting very difficult to produce accurate estimations for every tuple given the memory constraints of commodity programmable switches. Indeed, as networks grow in size, more flows have to be tracked, increasing the number of tuples to be recorded. At the same time, end-host virtualization requires more specific flowIDs, enlarging the memory cost for every single entry. Finally, the available memory resources have to be shared with other important functions as well (e.g., load balancing, forwarding, ACL). To address those issues, we present FlowLiDAR (Flow Lightweight Detection and Ranging), a new solution that is capable of tracking almost all the flows in the network while requiring only a modest amount of data plane memory, which is not dependent on the size of flowIDs. We implemented the scheme in P4, tested it using real traffic from ISPs, and compared it against four state-of-the-art solutions: FlowRadar, NZE, PR-sketch, and Elastic Sketch. © 2024 Copyright held by the owner/author(s).

关键词： flow measurement high-speed networking programmable data plane

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Democratizing LEO satellite network measurement 24

Democratizing LEO satellite network measurement

引用

2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Izhikevich, Liz Tran, Manda Izhikevich, Katherine Akiwate, Gautam Durumeric, Zakir Stanford University Stanford United States UC San Diego San Diego United States

ISBN: (纸本)9798400706240

Low Earth Orbit (LEO) satellite networks are quickly gaining traction with promises of impressively low latency, high bandwidth, and global reach. However, the research community knows relatively little about their operation and performance in practice. The obscurity is largely due to the high barrier of entry for measuring LEO networks, which requires deploying specialized hardware or recruiting large numbers of satellite Internet customers. In this paper, we introduce HitchHiking, a methodology that democratizes global visibility into LEO satellite networks. HitchHiking builds on the observation that Internet-exposed services that use LEO Internet can reveal satellite network architecture and performance, bypassing the need for specialized hardware. We evaluate HitchHiking against ground truth measurements and prior methods, showing that it provides more coverage and accuracy. With HitchHiking, we complete the largest study to date of Starlink network latency, measuring over 2,400∼users across 27∼countries. We uncover unexpected patterns in latency that surface how LEO routing is more complex than previously understood. Finally, we conclude with recommendations for future research on LEO networks. © 2024 Copyright held by the owner/author(s).

关键词： Satellites

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Miracle or mirage? A measurement study of nft rug pulls 24

Miracle or mirage? A Measurement study of nft rug pulls

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2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Huang, Jintao He, Ningyu Ma, Kai Xiao, Jiang Wang, Haoyu Huazhong University of Science and Technology Wuhan China Peking University Beijing China

ISBN: (纸本)9798400706240

NFT rug pull is one of the most prominent type of NFT scam, whose definition is that the developers of an NFT project abandon it and run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug pulls have not been systematically measured. To fill the void, this paper presents the first in-depth measurement study of NFT rug pulls. Specifically, we first compile a list of 253 known NFT rug pulls as our initial confirmed rug pulls (i.e., ground truth), based on which we perform a pilot study, highlighting the key symptoms of NFT rug pulls. Then, we design an effective rule-based detector to measure the prevalence of NFT rug pulls in the ecosystem. We have labelled 7,487 happened NFT rug pull projects which were not revealed by our community. To eliminate the potential damage brought by rug pull scams, we take a step further towards designing a real-time prediction model to proactively identify the potential rug pull projects in an early stage ahead of the scam happens. We have implemented a prototype system, and deployed it in the real-world setting for over 6 months. Our system has raised alarms for 5,557 new NFT projects, which works as a whistle blower that pinpoints rug pull scams timely, thus mitigating the impacts. © 2024 Copyright held by the owner/author(s).

关键词： Blockchain

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TAO: Re-Thinking DL-based Microarchitecture Simulation 24

TAO: Re-Thinking DL-based Microarchitecture Simulation

引用

2024 acm SIGMETRICS/IFIP Performance conference on measurement and modeling of computer systems, SIGMETRICS/PERFORMANCE 2024

作者： Pandey, Santosh Yazdanbakhsh, Amir Liu, Hang Rutgers University New BrunswickNJ United States Google DeepMind Mountain ViewCA United States

ISBN: (纸本)9798400706240

Microarchitecture simulators are indispensable tools for microarchitecture designers to validate, estimate, and optimize new hardware that meets specific design requirements. While the quest for a fast, accurate and detailed microarchitecture simulation has been ongoing for decades, existing simulators excel and fall short at different aspects: (i) Although execution-driven simulation is accurate and detailed, it is extremely slow and requires expert-level experience to design. (ii) Trace-driven simulation reuses the execution traces in pursuit of fast simulation but faces accuracy concerns and fails to achieve significant speedup. (iii) Emerging deep learning (DL)-based simulations are remarkably fast and have acceptable accuracy, but introduce substantial overheads from trace regeneration and model re-Training when simulating a new microarchitecture. Re-Thinking the advantages and limitations of the aforementioned three mainstream simulation paradigms, this paper introduces TAO that redesigns the DL-based simulation with three primary contributions: First, we propose a new training dataset design such that the subsequent simulation (i.e., inference) only needs functional trace as inputs, which can be rapidly generated and reused across microarchitectures. Second, to increase the detail of the simulation, we redesign the input features and the DL model using self-Attention to support predicting various performance metrics of interest. Third, we propose techniques to train a microarchitecture agnostic embedding layer that enables fast transfer learning between different microarchitectural configurations and effectively reduces the re-Training overhead of conventional DL-based simulators. TAO can predict various performance metrics of interest, significantly reduce the simulation time, and maintain similar simulation accuracy as state-of-The-Art DL-based endeavors. © 2024 Copyright held by the owner/author(s).

关键词： computer architecture

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Optimal Scheduling in the Multiserver-job Model under Heavy Traffic 23

Optimal Scheduling in the Multiserver-job Model under Heavy ...

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2023 acm SIGMETRICS international conference on measurement and modeling of computer systems, SIGMETRICS 2023

作者： Grosof, Isaac Scully, Ziv Harchol-Balter, Mor Scheller-Wolf, Alan Carnegie Mellon University Computer Science Department PittsburghPA United States Cornell University School of Operations Research and Information Engineering IthacaNY United States Carnegie Mellon University Tepper School of Business PittsburghPA United States

ISBN: (纸本)9798400700743

Multiserver-job systems, where jobs require concurrent service at many servers, occur widely in practice. Essentially all of the theoretical work on multiserver-job systems focuses on maximizing utilization, with almost nothing known about mean response time. Our goal in this paper is to minimize mean response time in a multiserver-job setting. Minimizing mean response time requires prioritizing small jobs while simultaneously maximizing utilization. Our question is how to achieve these joint objectives. We devise the ServerFilling-SRPT scheduling policy, which is the first policy to minimize mean response time in the multiserver-job model in the heavy traffic limit. In addition to proving this heavy-traffic result, we present empirical evidence that ServerFilling-SRPT outperforms all existing scheduling policies for all loads, with orders of magnitude improvements at high load. Because ServerFilling-SRPT requires knowing job sizes, we also define the ServerFilling-Gittins policy, which is optimal when sizes are unknown or partially known. For more detail, see the full paper https://***/10.1145/3570612 © 2023 Owner/Author.

关键词： heavy traffic asymptotic optimality latency gittins sojurn time srpt response time multiserver-job scheduling

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Refinery: Graph Solver as a Service: Refinement-based Generation and Analysis of Consistent Models 24

Refinery: Graph Solver as a Service: Refinement-based Genera...

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46th international conference on Software Engineering: Companion, ICSE-Companion 2024

作者： Marussy, Kristóf Ficsor, Attila Semeráth, Oszkár Varró, Dániel Budapest University of Technology and Economics Department of Measurement and Information Systems Budapest Hungary Linköping University Department of Computer and Information Science Linköping Sweden McGill University Department of Electrical and Computer Engineering Montreal Canada

ISBN: (纸本)9798400705021

Various software and systems engineering scenarios rely on the systematic construction of consistent graph models. However, automatically generating a diverse set of consistent graph models for complex domain specifications is challenging. First, the graph generation problem must be specified with mathematical precision. Moreover, graph generation is a computationally complex task, which necessitates specialized logic solvers. Refinery is a novel open-source software framework to automatically synthesize a diverse set of consistent domain-specific graph models. The framework offers an expressive high-level specification language using partial models to succinctly formulate a wide range of graph generation challenges. Moreover, it provides a modern cloud-based architecture for a scalable graph solver as a service, which uses logic reasoning rules to efficiently synthesize a diverse set of solutions to graph generation problems by partial model refinement. Applications include system-level architecture synthesis, test generation for modeling tools or traffic scenario synthesis for autonomous vehicles. Video demonstration: https://***/Qy-3udNsWsM. Continuously deployed at: https://***/. © 2024 IEEE computer Society. All rights reserved.

关键词： Open source software

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