Adaptivity in Distributed Agent-Based Simulation: A Generic Load-Balancing Approach
| Autor: | Toon Bogaerts, Joachim Denil, Peter Hellinckx, Stig Bosmans, Wim Casteels, Siegfried Mercelis |
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| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Process (engineering) Computer science Distributed computing Dynamic load balancing 02 engineering and technology Load balancing (computing) Execution time Cellular automaton Idle 020901 industrial engineering & automation Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Engineering sciences. Technology |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030668877 MABS Multi-Agent-Based Simulation XXI : 21st International Workshop, MABS 2020, Auckland, New Zealand, May 10, 2020: revised selected papers |
| DOI: | 10.1007/978-3-030-66888-4_1 |
| Popis: | Distributed agent-based simulations often suffer from an imbalance in computational load, leading to a suboptimal use of resources. This happens when part of the computational resoures are waiting idle for another process to finish. Self-adaptive load-balancing algorithms have been developed to use these resources more optimally. These algorithms are typically implemented ad-hoc, making re-usability and maintenance difficult. In this work, we present a generic self-adaptive framework. This methodology is evaluated with the Acsim framework on two simulations: a micro-traffic simulation and a cellular automata simulation. For each of these scenarios a scalable and adaptive load-balancing algorithm is implemented, showing significant improvements in execution time of the simulation. |
| Databáze: | OpenAIRE |
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