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Adaptivity in Distributed Agent-Based Simulation

Book Contribution - Book Abstract Conference Contribution

Subtitle:A Generic Load-Balancing Approach
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.
Book: Multi-Agent-Based Simulation XXI : 21st International Workshop, MABS 2020, Auckland, New Zealand, May 10, 2020: revised selected papers
Pages: 1 - 12
ISBN:978-3-030-66887-7
Publication year:2021
Keywords:P1 Proceeding
Accessibility:Closed