Skip to Main Content
Distributed systems which use nonstationary communicating objects have to address the problem of managing locations of these objects. We study location management (LM) and its impact on application performance in the context of dynamic load-balancing for parallel distributed computing. We summarize our experience with LM in distributed object-based systems by comparing six location management policies (LMPs). The LMPs are studied within the PREMA framework used mainly for parallel mesh generation and refinement applications. Our experimental study is using a synthetic tunable microbenchmark and two mesh generation applications. We explain why the commonly adopted in practice Jump Update LMP is efficient for most of our applications and we compare it with the other location management techniques. We show how the performance of a particular LMP can be affected by the application properties and its data layout. Finally, we identify the conditions under which certain LMPs are more beneficial than jump update.