Abstract

Consistency is hard and coordination is expensive. As we move into the world of connected ‘Internet of Things’ style applications, or large-scale mobile applications, devices have less power, periods of limited connectivity, and operate over unreliable asynchronous networks. This poses a problem with shared state: how do we handle concurrent operations over shared state, while clients are offline, and ensure that values converge to a desirable result without making the system unavailable?

We look at a new programming model, called Lasp. This programming model combines distributed convergent data structures with a dataflow execution model designed for distribution over large-scale applications. This model supports arbitrary placement of processing node: this enables the user to author applications that can be distributed across data centers and pushed to the edge.

Bio: Christopher Meiklejohn loves distributed systems and programming languages. Previously, Christopher worked at Basho Technologies, Inc. on the distributed key-value store, Riak. Christopher develops a programming model for distributed computation, called Lasp. Christopher is currently a Ph.D. student at the Université Catholique de Louvain in Belgium.