Proximity Load Balancing for Distributed Cluster-based Individual-oriented Fish School Simulations

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• 作者：Roberto Solar ^{roberto.solar@caos.uab.es} ; Remo Suppi ^{remo.suppi@uab.es} ; Emilio Luque ^{emilio.luque@uab.es}
• 关键词：High-performance simulation ; individual-oriented models ; distributed simulation ; data clustering ; nearest-neighbor ; load balancing
• 刊名：Procedia Computer Science
• 出版年：2012
• 期刊代码：pc74_18770509
• 类别：cp
• 出版时间：2012
• 卷：9
• 期：Complete
• 页码：328-337
• 文件大小：1621 K

摘要

Partitioning and load balancing are highly important issues in distributed individual-oriented simulation. Choosing how to distribute individuals on the distributed environment can be a crucial factor at the moment of executing the simulation. Partitioning an individual-oriented system should be efficient in order to reduce communication involved in interaction between individuals belong to different logical processes. Furthermore, if the individual-oriented model exhibits mobility patterns, we should be able to maintain the load balancing in order to keep the global application performance. In this work, we present a proximity load balancing strategy for a distributed cluster-based individual-oriented fish school simulator. On one hand, we implement a robust cluster-based partitioning method by means of covering radius criterion and voronoi diagrams. We use a proximity criterion to distribute individuals on the distributed architecture. On the other hand, we propose a proximity load balancing strategy in order to maintain the application performance as the simulation progresses.