Carlos Baquero will give a talk, in person and online, for the Coffee House Tech Talk Series. 

The details of the talk are below. A lunch will be provided after the talk.

Title: CRDTs: State-based approaches to high availability

Speaker: Carlos Baquero

When: 11am Tue 4 July

Where: 4^th floor Bayes Centre, Coffee House

Registration: https://www.smartsurvey.co.uk/s/D8MKWE/

External link: https://meeting.huaweicloud.com/welink/webrtc/?lang=en-US#/j/98055933

Meeting ID: 98055933

Passcode: 493142

Abstract

Distributed systems are inherently complex and exposed to failures in their components. While distributed algorithms try to do their best in handling node and network failures, it is often not possible to mask them. In the presence of

failures, systems that thrive for high availability need to allow users to always submit operations and observe the local state (ensuring local-first), leading to potential divergence. Designs with Conflict-free Replicated Data Types (CRDTs) have been used extensively to guarantee that it is possible to converge to a state that reflects concurrent operations.

Bio

Carlos Baquero is a Professor in the Department of Informatics Engineering within FEUP, and area coordinator at the High Assurance Laboratory (HASLab) within INESC TEC. He currently teaches courses in Operating Systems and in Large Scale Distributed Systems. Research interests cover data management in eventual consistent settings, distributed data aggregation and causality tracking. He worked in the development of data summary mechanisms such as Scalable Bloom Filters, causality tracking for dynamic settings with Interval Tree Clocks and Dotted Version Vectors and predictable eventual consistency with Conflict-Free Replicated Data Types. Most of this research has been applied in industry, namely in the Riak distributed database, Redis CRDBs, Akka distributed data and Microsoft Azure Cosmos DB.

【BAYES COFFEE HOUSE TECH TALK SERIES】CRDTs: State-based approaches to high availability / Huawei-Edinburgh Joint Lab by blogadmin is licensed under a Creative Commons Attribution CC BY 3.0