When to Hedge in Interactive Services

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The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

We propose uBFT, the first State Machine Replication (SMR) system to achieve microsecond-scale latency in data centers, while using only 2f+1 replicas to tolerate f Byzantine failures. The Byzantine Fault Tolerance (BFT) provided by uBFT is essential as pu ...

This paper introduces protocols for authenticated private information retrieval. These schemes enable a client to fetch a record from a remote database server such that (a) the server does not learn which record the client reads, and (b) the client either ...

Online services have become ubiquitous in technological society, the global demand for which has driven enterprises to construct gigantic datacenters that run their software. Such facilities have also recently become a substrate for third-party organizatio ...

Byzantine Reliable Broadcast (BRB) is a fundamental distributed computing primitive, with applications ranging from notifications to asynchronous payment systems. Motivated by practical consideration, we study Client-Server Byzantine Reliable Broadcast (CS ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

We present GARFIELD, a library to transparently make machine learning (ML) applications, initially built with popular (but fragile) frameworks, e.g., TensorFlow and PyTorch, Byzantine–resilient. GARFIELD relies on a novel object–oriented design, reducing t ...

Epilepsy is one of the most prevalent paroxystic neurological disorders. It is characterized by the occurrence of spontaneous seizures. About 1 out of 3 patients have drug-resistant epilepsy, thus their seizures cannot be controlled by medication. Automati ...

A major theme of IT in the past decade has been the shift from on-premise hardware to cloud computing. Running a service in the public cloud is practical, because a large number of resources can be bought on-demand, but this shift comes with its own set of ...

The single-server multi-message private information retrieval with side information problem is studied for general cases. In this problem, K independent messages are stored at a single server. One user initially has M messages as side information and wants ...

Federated Learning (FL) is a machine learning setting where many devices collaboratively train a machine learning model while keeping the training data decentralized. In most of the current training schemes the central model is refined by averaging the par ...

Virtually every connection to an Internet service is preceded by a DNS lookup. Lookups are performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations s ...

Modern large-scale data platforms manage colossal amount of data, generated by the ever-increasing number of concurrent users. Geo-replicated and sharded key-value data stores play a central role when building such platforms. As the strongest consistency m ...

In a modern data center (DC), a large majority of costs arise from energy consumption. The most popular technique used to mitigate this issue is virtualization and more precisely virtual machine (VM) consolidation. Although consolidation may increase serve ...

In today’s modern datacenters, the waiting time spent within a server’s queue is a major contributor of the end-to-end tail latency of μs-scale remote procedure calls. In traditional TCP, congestion control handles in-network congestion, while flow control ...

This paper addresses the mean-field behavior of large-scale systems of parallel servers with a processor sharing service discipline when arrivals are Poisson and jobs have general service time distributions when an SQ(d) routing policy is used. Under this ...

Improving the energy efficiency of data centers while guaranteeing Quality of Service (QoS), together with detecting performance variability of servers caused by either hardware or software failures, are two of the major challenges for efficient resource m ...

To meet today's data management needs, it is a widespread practice to use distributed data storage and processing systems. Since the publication of the MapReduce paradigm, a plethora of such systems arose, but although widespread, the capabilities of these ...

When to Hedge in Interactive Services

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PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

uKharon: A Membership Service for Microsecond Applications

Privatized graph federated learning

uBFT: Microsecond-Scale BFT using Disaggregated Memory

Authenticated private information retrieval

Hardware and Software Support for RPC-Centric Server Architecture

Oracular Byzantine Reliable Broadcast

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

GARFIELD: System Support for Byzantine Machine Learning (Regular Paper)

Personalized Real-Time Federated Learning for Epileptic Seizure Detection

Understanding and Mitigating Latency Variability of Latency-Critical Applications

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Ensemble Distillation for Robust Model Fusion in Federated Learning

Encrypted DNS double right arrow Privacy? A Traffic Analysis Perspective

Efficient Protocols for Enforcing Causal Consistency in Geo-Replicated Key-Value Data Stores

Drowsy-DC: Data center power management system

Flow control for Latency-Critical RPCs

The mean-field behavior of processor sharing systems with general job lengths under the SQ(d) policy

MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers

Formal Approaches to Querying Big Data in Shared-Nothing Systems