Abstract
Many scientific datasets are generated in a given data structure (e.g., a graph) and are reused for various analyses. From this viewpoint, instead of streaming these datasets into conventional big-data tools such as MapReduce or Spark, we should maintain their data structures over distributed memory and repeat deploying mobile computing units to the datasets. Since thread migration, mobile agents, and parallel ABM (agent-based modeling) simulators enable migration of execution entities, this paper looks at four Java-based representative systems: JCilk, IBM Aglets, Repast Simphony, and the MASS library. Our analysis of their programmability and parallel performance demonstrates that MASS can competitively perform distributed data analysis in an emergent collective group behavior among reactive agents.
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Wenger, M., Acoltzi, J., Fukuda, M. (2021). Comparing Thread Migration, Mobile Agents, and ABM Simulators in Distributed Data Analysis. In: Dignum, F., Corchado, J.M., De La Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS 2021. Lecture Notes in Computer Science(), vol 12946. Springer, Cham. https://doi.org/10.1007/978-3-030-85739-4_27
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DOI: https://doi.org/10.1007/978-3-030-85739-4_27
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