Optimizing Data Structures for Highly Dynamic Content in Collective, Adaptive Systems

Köster, Till and Hauptmann, Felix and Uhrmacher, Adelinde M. (2018) Optimizing Data Structures for Highly Dynamic Content in Collective, Adaptive Systems. In: Winter Simulation Conference (WSC 2018), 09-12 Dec 2018, Gothenburg, Sweden. Poster.

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Abstract

In discrete event simulation of collective, adaptive systems (CAS), it is necessary to store all the entities of the system in some data structure. However, collective adaptive systems, which are characterized by a high fluctuation of entities, pose a challenge for typical data structures. To address this problem we developed the sequential pile container and evaluated its performance based on a set of benchmarks and in comparison to the data structure Set and unordered_set from the C++ template library and a recently developed data structure, i.e., plf::colony. The performance of plf::colony and the sequential pile proved overall superior in these benchmarks, and performed equally well in inserting, copying and iterating over all entities. Sequential pile outperforms plf::colony at deleting elements.

Item Type: Conference or Workshop Item (Poster)
Projects: ESCeMMo