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Adaptive Resource Provisioning Mechanism in VEEs for Improving Performance of HLA-Based Simulations
Author(s) -
Zengxiang Li,
Wentong Cai,
Stephen John Turner,
Xiaorong Li,
Ta Nguyen Binh Duong,
Rick Siow Mong Goh
Publication year - 2015
Publication title -
acm transactions on modeling and computer simulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 51
eISSN - 1558-1195
pISSN - 1049-3301
DOI - 10.1145/2717309
Subject(s) - computer science , provisioning , high level architecture , distributed computing , scalability , virtual machine , cloud computing , workload , live migration , synchronization (alternating current) , real time computing , operating system , virtualization , computer network , interoperability , channel (broadcasting)
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.

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