Parallel proximity detection and the distribution list algorithm

Abstract

Generalized proximity detection for moving objects in a logically correct parallel discrete-event simulation is an interesting and fundamentally challenging problem. Determining who can see whom in a manner that is fully scalable in terms of CPU usage, number of messages, and memory requirements is highly non-trivial. A new scalable approach has been developed to solve this problem. This algorithm, called The Distribution List, has been designed and tested using the object-oriented Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) operating system. Preliminary results show that the Distribution List algorithm achieves excellent parallel performance.