A scalable and distributed dendritic cell algorithm for big data classification

Zaineb Chelly Dagdia

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)
297 Downloads (Pure)


In the era of big data, scaling evolution up to large-scale data sets is a very interesting and challenging task. The application of standard biological systems in such data sets is not straightforward. Therefore, a new class of scalable biological systems that embraces the huge storage and processing capacity of distributed platforms is required. In this work, we focus on the Dendritic Cell Algorithm (DCA), a bio-inspired classifier, and its limitation when coping with very large data sets. To overcome this limitation, we propose a novel distributed DCA version for data classification based on the MapReduce framework to distribute the functioning of this algorithm through a cluster of computing elements. Our experimental results show that our proposed distributed solution is suitable to enhance the performance of the DCA enabling the algorithm to be applied over big data classification problems
Original languageEnglish
Article number100432
JournalSwarm and Evolutionary Computation
Early online date01 Sept 2018
Publication statusPublished - 01 Nov 2019


  • Big data
  • Dendritic cell algorithm
  • Distributed processing


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