Publications related to Client–server model

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uBFT: Microsecond-Scale BFT using Disaggregated Memory

Rachid Guerraoui, Antoine Murat, Mihail Igor Zablotchi, Athanasios Xygkis, Naama Ben David

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 ...

2023

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Michael Christoph Gastpar, Aditya Pradeep

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

2023

Privatized graph federated learning

Ali H. Sayed, Stefan Vlaski, Elsa Rizk

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 ...

SPRINGER2023

Authenticated private information retrieval

Bryan Alexander Ford, Simone Maria Stefano Colombo, Henry Nathaniel Corrigan-Gibbs, Kirill Nikitin

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 ...

Berkeley2023

Decentralized learning made easy with DecentralizePy

Anne-Marie Kermarrec, Rafael Pereira Pires, Akash Balasaheb Dhasade, Rishi Sharma, Milos Vujasinovic

Decentralized learning (DL) has gained prominence for its potential benefits in terms of scalability, privacy, and fault tolerance. It consists of many nodes that coordinate without a central server and exchange millions of parameters in the inherently ite ...

2023

Federated Linear Bandit Learning via Over-the-air Computation

Yuning Jiang, Xin Liu, Ting Wang

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...

IEEE2023

Oracular Byzantine Reliable Broadcast

Rachid Guerraoui, Manuel José Ribeiro Vidigueira, Martina Camaioni, Matteo Monti

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 ...

Schloss Dagstuhl - Leibniz-Zentrum für Informatik2022

When to Hedge in Interactive Services

Edouard Bugnion, Mia Primorac

In online data-intensive (OLDI) services, each client request typically executes on multiple servers in parallel; as a result, “system hiccups”, although rare within a single server, can interfere with many client requests and cause violations of service-l ...

USENIX2021

Client–server model

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Chat with Graph Search

uBFT: Microsecond-Scale BFT using Disaggregated Memory

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Privatized graph federated learning

Authenticated private information retrieval

Decentralized learning made easy with DecentralizePy

Federated Linear Bandit Learning via Over-the-air Computation

Oracular Byzantine Reliable Broadcast

When to Hedge in Interactive Services

Integrity and Metadata Protection in Data Retrieval

Authenticated private information retrieval

Privatized graph federated learning

Decentralized learning made easy with DecentralizePy

uBFT: Microsecond-Scale BFT using Disaggregated Memory

Integrity and Metadata Protection in Data Retrieval

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Federated Linear Bandit Learning via Over-the-air Computation

When to Hedge in Interactive Services

Oracular Byzantine Reliable Broadcast