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.
Christopher Meiklejohn loves distributed systems and programming languages. Previously, Christopher worked at Basho Technologies, Inc. on the distributed key-value store, Riak, at Mesosphere on the Apache Mesos cloud computing framework, and at Machine Zone working on designing distributed algorithms. Christopher is currently an Erasmus Mundus doctoral student at Université catholique de Louvain in Belgium and Instituto Superior Técnico in Portugal, and develops a programming model for distributed computing, called Lasp.
