Adaptive Resource Provisioning Mechanism in VEEs for Improving Performance of HLA-Based Simulations

Author:

Li Zengxiang1,Cai Wentong2,Turner Stephen John2,Li Xiaorong3,Duong Ta Nguyen Binh4,Goh Rick Siow Mong1

Affiliation:

1. Institute of High Performance Computing, Singapore

2. Nanyang Technological University, Singapore

3. Infocomm Development Authority of Singapore, Singapore

4. Ngee Ann Polytechnic, Singapore

Abstract

Parallel and distributed simulations (or High-Level Architecture (HLA)-based simulations) employing optimistic synchronization allow federates to advance simulation time freely at the risk of overoptimistic executions and execution rollbacks. As a result, the simulation performance may degrade significantly due to the simulation workload imbalance among federates. In this article, we investigate the execution of parallel and distributed simulations on Cloud and data centers with Virtual Execution Environments (VEEs). In order to speed up simulation execution, an Adaptive Resource Provisioning Mechanism in Virtual Execution Environments (ArmVee) is proposed. It is composed of a performance monitor and a resource manager. The former measures federate performance transparently to the simulation application. The latter distributes available resources among federates based on the measured federate performance. Federates with different simulation workloads are thus able to advance their simulation times with comparable speeds, thus are able to avoid wasting time and resources on overoptimistic executions and execution rollbacks. ArmVee is evaluated using a real-world simulation model with various simulation workload inputs and different parameter settings. The experimental results show that ArmVee is able to speed up the simulation execution significantly. In addition, it also greatly reduces memory usage and is scalable.

Funder

Future Data Center Technology Thematic Strategic Research Programme of the Singapore Agency for Science, Technology and Research

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Modeling and Simulation

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