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POMACS V8, N2, June 2024 Editorial
The Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) focuses on the measurement and performance evaluation of computer systems and operates in close collaboration with the ACM Special Interest Group SIGMETRICS. All papers ...
BONES: Near-Optimal Neural-Enhanced Video Streaming
Accessing high-quality video content can be challenging due to insufficient and unstable network bandwidth. Recent advances in neural enhancement have shown promising results in improving the quality of degraded videos through deep learning. Neural-...
A Closer Look into IPFS: Accessibility, Content, and Performance
The InterPlanetary File System (IPFS) has recently gained considerable attention. While prior research has focused on understanding its performance characterization and application support, it remains unclear: (1) what kind of files/content are stored in ...
Analysis of False Negative Rates for Recycling Bloom Filters (Yes, They Happen!)
Bloom Filters are a desirable data structure for distinguishing new values in sequences of data (i.e., messages), due to their space efficiency, their low false positive rates (incorrectly classifying a new value as a repeat), and never producing false ...
FedQV: Leveraging Quadratic Voting in Federated Learning
Federated Learning (FL) permits different parties to collaboratively train a global model without disclosing their respective local labels. A crucial step of FL, that of aggregating local models to produce the global one, shares many similarities with ...
Learning the Optimal Control for Evolving Systems with Converging Dynamics
We consider a principle or controller that can pick actions from a fixed action set to control an evolving system with converging dynamics. The actions are interpreted as different configurations or policies. We consider systems with converging dynamics, ...
Multi-dimensional State Space Collapse in Non-complete Resource Pooling Scenarios
The present paper establishes an explicit multi-dimensional state space collapse (SSC) for parallel-processing systems with arbitrary compatibility constraints between servers and job types. This breaks major new ground beyond the SSC results and queue ...
Network Fairness Ambivalence: When does social network capital mitigate or amplify unfairness?
Social networks inherit societal biases present across lines of gender, race, socioeconomic status, and other factors. Networks can structurally perpetuate unequal access to information and opportunities through homophilous dynamics. While there is ...
Server Saturation in Skewed Networks
We consider a model inspired by compatibility constraints that arise between tasks and servers in data centers, cloud computing systems and content delivery networks. The constraints are represented by a bipartite graph or network that interconnects ...
Strongly Tail-Optimal Scheduling in the Light-Tailed M/G/1
We study the problem of scheduling jobs in a queueing system, specifically an M/G/1 with light-tailed job sizes, to asymptotically optimize the response time tail. This means scheduling to make \mathbfP [T > t], the chance a job's response time exceeds t,...
TAO: Re-Thinking DL-based Microarchitecture Simulation
Microarchitecture simulators are indispensable tools for microarchitecture designers to validate, estimate, optimize, and manufacture new hardware that meets specific design requirements. While the quest for a fast, accurate and detailed ...