The Hidden Complexity of Distributed Systems

The field of distributed computing has a long history, of more than fifty years. During that time, our understanding of the field has improved immensely and a certain body of folklore beliefs has formed. However, such folklore beliefs are not necessarily always true.

In this thesis, we identify hidden complexities (in the sense of intricacies or costs) of distributed systems that contradict some of these folklore beliefs. Specifically, in this thesis, we challenge accepted beliefs in the following way: i) consensus algorithms need not be leader-based: there exists a deterministic leaderless consensus algorithm that is robust to non-synchronous periods, ii) completing a state machine replication command can be arbitrarily more expensive than solving a consensus instance, and iii) no data store actually provides fast transactions because they are impossible. Our results are associated to some of the fundamental problems in the field of distributed computing and are of significant practical relevance.