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Journal Article
Adaptive and optimized agent placement scheme for parallel agent‐based simulation
- Authors
- Ki-Sung Jin, Sang-Min Lee, Young-Chul Kim
- Issue Date
- 2022-04
- Citation
- ETRI Journal, v.44, no.2, pp.313-326
- ISSN
- 1225-6463
- Publisher
- 한국전자통신연구원 (ETRI)
- Language
- English
- Type
- Journal Article
- Abstract
- This study presents a noble scheme for distributed and parallel simulations with optimized agent placement for simulation instances. The traditional parallel simulation has some limitations in that it does not provide sufficient performance even though using multiple resources. The main reason for this discrepancy is that supporting parallelism inevitably requires additional costs in addition to the base simulation cost. We present a comprehensive study of parallel simulation architectures, execution flows, and characteristics. Then, we identify critical challenges for optimizing large simulations for parallel instances. Based on our cost?밷enefit analysis, we propose a novel approach to overcome the performance constraints of agent-based parallel simulations. We also propose a solution for eliminating the synchronizing cost among local instances. Our method ensures balanced performance through optimal deployment of agents to local instances and an adaptive agent placement scheme according to the simulation load. Additionally, our empirical evaluation reveals that the proposed model achieves better performance than conventional methods under several conditions.
- KSP Keywords
- Adaptive agent, Agent placement, Balanced performance, Comprehensive study, Conventional methods, Empirical Evaluation, Multiple resources, Novel approach, Optimal deployment, Parallel Simulation, Performance constraints
This work is distributed under the term of Korea Open Government License (KOGL)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
(Type 4: : Type 1 + Commercial Use Prohibition+Change Prohibition)
