PRECISE Seminar: Robust Abstractions for Replicated Shared State

PRECISE Seminar: Robust Abstractions for Replicated Shared State
Tue, November 25, 2014 @ 1:30pm EST
Levine Hall - Room 307
3330 Walnut Street
Philadelphia, PA 19104
Speaker
Sebastian Burckhardt, Ph.D.
Microsoft Corporation
Abstract

In the age of cloud-connected mobile devices, users want responsive apps that read and write shared data everywhere, at all times, even if network connections are slow or unavailable. Replication and eventual consistency, while able to deliver this experience, require us to face the complexity of asynchronous update propagation and conflict resolution. Our research goal is to find abstractions that encapsulate this complexity, in order to simplify the programming of distributed applications that are responsive, reactive, and collaborative.

In this talk, we first discuss the general principles of eventual consistency. Then, we introduce our programming model, consisting of cloud types (for declarative type-based conflict resolution) and the GLUT model (an operational consistency model based on a global log of update transactions). Finally, we report on our practical experiences with supporting cloud types and GLUT in the TouchDevelop programming language and mobile development environment.

Speaker Bio

Sebastian Burckhardt was born and raised in Basel, Switzerland, where he studied Mathematics at the local University. During an exchange year at Brandeis University, he discovered his affinity to Computer Science and immigrated to the United States. After a few years of industry experience at IBM, he returned to academia and earned his PhD in Computer Science at the University of Pennsylvania.  Since then, he has worked as a researcher at Microsoft Research in Redmond.  His general research interest is the study of programming models for of concurrent, parallel, and distributed systems. More specific interests include consistency models, concurrency testing, self-adjusting computation, and the concurrent revisions programming model.