AI

Recursion in Scalable Protocols via Distributed Data Flows

Abstract

This paper proposes a new approach to representing scalable hierarchical distributed multi-party protocols, and reasoning about their behavior. The established endpoint-to-endpoint message-passing abstraction provides little support for modeling distributed algorithms in hierarchical systems, in which the hierarchy and membership dynamically evolve. This paper explains how with our new Distributed Data Flow (DDF) abstraction, hierarchical architecture can be modeled via recursion in the language. This facilitates a more concise code, and it enables automated generation of scalable hierarchical implementations for heterogeneous network environments.