Measurement and Analysis of Computing Systems (POMACS)


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Proceedings of the ACM on Measurement and Analysis of Computing Systems - SIGMETRICS, Volume 1 Issue 2, December 2017

Safe Randomized Load-Balanced Switching By Diffusing Extra Loads
Sen Yang, Bill Lin, Jun Xu
Article No.: 29
DOI: 10.1145/3154487

Load-balanced switch architectures are known to be scalable in both size and speed, which is of interest due to the continued exponential growth in Internet traffic. However, the main drawback of load-balanced switches is that packets can depart...

Predictive Impact Analysis for Designing a Resilient Cellular Backhaul Network
Sen Yang, Yan He, Zihui Ge, Dongmei Wang, Jun Xu
Article No.: 30
DOI: 10.1145/3154488

Backhaul transport network design and optimization for cellular service providers involve a unique challenge stemming from the fact that an end-user's equipment (UE) is within the radio reach of multiple cellular towers: It is hard to evaluate the...

Censored Demand Estimation in Retail
Muhammad J. Amjad, Devavrat Shah
Article No.: 31
DOI: 10.1145/3154489

In this paper, the question of interest is estimating true demand of a product at a given store location and time period in the retail environment based on a single noisy and potentially censored observation. To address this...

Online Learning of Optimally Diverse Rankings
Stefan Magureanu, Alexandre Proutiere, Marcus Isaksson, Boxun Zhang
Article No.: 32
DOI: 10.1145/3154490

Search engines answer users' queries by listing relevant items (e.g. documents, songs, products, web pages, ...). These engines rely on algorithms that learn to rank items so as to present an ordered list maximizing the probability that it...

A Refined Mean Field Approximation
Nicolas Gast, Benny Van Houdt
Article No.: 33
DOI: 10.1145/3154491

Mean field models are a popular means to approximate large and complex stochastic models that can be represented as N interacting objects. Recently it was shown that under very general conditions the steady-state expectation of any performance...

Towards Fast-Convergence, Low-Delay and Low-Complexity Network Optimization
Sinong Wang, Ness Shroff
Article No.: 34
DOI: 10.1145/3154492

Distributed network optimization has been studied for well over a decade. However, we still do not have a good idea of how to design schemes that can simultaneously provide good performance across the dimensions of utility optimality, convergence...

On Non-Preemptive VM Scheduling in the Cloud
Konstantinos Psychas, Javad Ghaderi
Article No.: 35
DOI: 10.1145/3154493

We study the problem of scheduling VMs (Virtual Machines) in a distributed server platform, motivated by cloud computing applications. The VMs arrive dynamically over time to the system, and require a certain amount of resources (e.g. memory, CPU,...

An Optimal Randomized Online Algorithm for QoS Buffer Management
Lin Yang, Wing Shing Wong, Mohammad H. Hajiesmaili
Article No.: 36
DOI: 10.1145/3154494

The QoS (Quality of Service) buffer management problem, with significant and diverse computer applications, e.g., in online cloud resource allocation problems, is a classic online admission control problem in the presence of resource constraints....

On the Convergence Rate of Distributed Gradient Methods for Finite-Sum Optimization under Communication Delays
Thinh T. Doan, Carolyn L. Beck, R. Srikant
Article No.: 37
DOI: 10.1145/3154496

Motivated by applications in machine learning and statistics, we study distributed optimization problems over a network of processors, where the goal is to optimize a global objective composed of a sum of local functions. In these problems, due to...

The PDE Method for the Analysis of Randomized Load Balancing Networks
Reza Aghajani, Xingjie Li, Kavita Ramanan
Article No.: 38
DOI: 10.1145/3154497

We introduce a new framework for the analysis of large-scale load balancing networks with general service time distributions, motivated by applications in server farms, distributed memory machines, cloud computing and communication systems. For a...

Designing Low-Complexity Heavy-Traffic Delay-Optimal Load Balancing Schemes: Theory to Algorithms
Xingyu Zhou, Fei Wu, Jian Tan, Yin Sun, Ness Shroff
Article No.: 39
DOI: 10.1145/3154498

In this paper, we establish a unified analytical framework for designing load balancing algorithms that can simultaneously achieve low latency, low complexity, and low communication overhead. We first propose a general class \Pi of load...

Towards Optimality in Parallel Scheduling
Benjamin Berg, Jan-Pieter Dorsman, Mor Harchol-Balter
Article No.: 40
DOI: 10.1145/3154499

To keep pace with Moore's law, chip designers have focused on increasing the number of cores per chip rather than single core performance. In turn, modern jobs are often designed to run on any number of cores. However, to effectively leverage...

Performance of Balanced Fairness in Resource Pools: A Recursive Approach
Thomas Bonald, Céline Comte, Fabien Mathieu
Article No.: 41
DOI: 10.1145/3154500

Understanding the performance of a pool of servers is crucial for proper dimensioning. One of the main challenges is to take into account the complex interactions between servers that are pooled to process jobs. In particular, a job can generally...

Tomographic Node Placement Strategies and the Impact of the Routing Model
Yvonne-Anne Pignolet, Stefan Schmid, Gilles Tredan
Article No.: 42
DOI: 10.1145/3154501

Fault-tolerant computer networks rely on mechanisms supporting the fast detection of link failures. Tomographic techniques can be used to implement such mechanisms at low cost: it is often sufficient to deploy a small number of tomography nodes...

The CSI Framework for Compiler-Inserted Program Instrumentation
Tao B. Schardl, Tyler Denniston, Damon Doucet, Bradley C. Kuszmaul, I-Ting Angelina Lee, Charles E. Leiserson
Article No.: 43
DOI: 10.1145/3154502

The CSI framework provides comprehensive static instrumentation that a compiler can insert into a program-under-test so that dynamic-analysis tools - memory checkers, race detectors, cache simulators, performance profilers, code-coverage...

Distributed Statistical Machine Learning in Adversarial Settings: Byzantine Gradient Descent
Yudong Chen, Lili Su, Jiaming Xu
Article No.: 44
DOI: 10.1145/3154503

We consider the distributed statistical learning problem over decentralized systems that are prone to adversarial attacks. This setup arises in many practical applications, including Google's Federated Learning. Formally, we focus on a...

A Fine-grained Event-based Modem Power Model for Enabling In-depth Modem Energy Drain Analysis
Xiaomeng Chen, Jiayi Meng, Y. Charlie Hu, Maruti Gupta, Ralph Hasholzner, Venkatesan Nallampatti Ekambaram, Ashish Singh, Srikathyayani Srikanteswara
Article No.: 45
DOI: 10.1145/3154504

Cellular modems enable ubiquitous Internet connectivities to modern smartphones, but in doing so they become a major contributor to the smartphone energy drain. Understanding modem energy drain requires a detailed power model. The prior art, an...