Evolutionary Algorithms (AEs) for IOT
Submission DeadlineAug. 30, 2020

Online submission system: http://www.sciencepublishinggroup.com/login

Lead Guest Editor
Nour El-Houda Benalia
Signal and Communication Laboratory, Polytechnic National School, El Harrach, Algeria
Guest Editors
  • Rabah Sadoun
    Signal and Communication Laboratory, Polytechnic National School, El Harrach, Algeria
  • Widad Kartous
    Signal and Communication Laboratory, Polytechnic National School, El Harrach, Algeria
  • Ahlem Bentrah
    Batna 2 University, Batna, Algeria
  • Essma Bendiab
    Constantine 2 University, Constantine, Algeria
  • Soraya Hamida
    Batna 2 University, Batna, Algeria
Introduction
Nowadays and with the evolution of computing tools and algorithmics, bio-mimicry is starting to become a reality and a very active research axis. A wide range of algorithms covering most areas such as robotics, biomedical electronics, control systems, finance ... etc. In addition, the field of connected objects (IoT), and its natural variation which is the big data takes more and more a dominating place by imposing in fact the fourth industrial revolution. Cloud and fog computing become another proven reality.
By proposing to integrate into this dynamic, we project through our research activities to combine these three paradigms (bio inspired, IoT (embedded), cloud and fog computing) to explore through training and research this emerging field to through the study of evolutionary algorithms for their implementations on embedded targets through algorithm - architecture matching approach on heterogeneous targets. The challenge is important knowing that this type of algorithm is often seen as having to run on HPC platforms.
We will discuss the application of these bio-inpired algorithms and their implementations in a platform IoT / Big Data in the domains of a certain interest.
Aims and Scope:
  1. Disseminate original, scientific, theoretical research in area of IoT, and bioinspired methods
  2. Look for the advanced bioinspired methods
  3. Aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research
  4. Apply of these methods and their implementations in an IoT / Big Data platform
  5. Seek original and unpublished research papers based on theoretical or experimental works for the publication globally
  6. Design of IoT platform presenting a fog embedded computing declination dedicated to diverse domains of interest
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