Mutual exchange of parameters between opportunistic networks and distributed databases

Betreuer / Ansprechpartner

  • Björn Butzin
  • Peter Danielis
  • Martin Kasparick
  • Hannes Grunert
  • Prof. Timmermann
  • Andreas Heuer

    Charakter

    • Konzeption
    • Prototypische Implementierung

    Vorkenntnisse

    • Grundkenntnisse über Netzwerke
    • DB I oder DB II
    • Programmierkenntnisse in C++
    • Erfahrungen im Umgang mit OMNeT++ (Netzwerksimulator)

    Beschreibung

    Instead of using a centralized computer cluster with homogeneous nodes and high-performance network connections, the Internet of Things (IoT) shall be used as a large-scale distributed database engine. By distributing the calculation of analysis results on sensor nodes and other low-resource devices, performance as well as privacy issues can be addressed and protection of corporate knowledge can be ensured. In contrast to existing solutions, in the most constrained part of the network, node may use sleep cycles to save energy and are therefore not always available. Hence, whenever available we want the nodes to opportunistically share their knowledge by broadcasting it to other nodes in transmission range. Thereby, their knowledge may even be obtained from another node. To enable the proper functionality of the distributed system as a whole, parameters need to be adjusted and shared. Parameters comprise, among other things, parameters for the opportunistic communication (e.g., broadcast intervals), database constraints (e.g., integrity constraints and dependencies), privacy, and energy constraints. Simulators like the discrete network simulator OMNeT++ allow for a suitable simulation of a large-scale network with user-defined functionality. Your objective of this thesis is therefore to develop a network simulation model for the mutual exchange of optimization parameters between opportunistic networks and distributed databases. You are supposed to investigate, which parameters have the highest impact on the proper functionality of the distributed system. Subsequently, optimized parameter values shall be exchanged between the different system nodes.

    Arbeitsschritte

    • Stand der Technik: Netzwerksimulator OMNeT++
    • Stand der Forschung
      • Opportunistic Networks
      • Verteilte Datenbanken
    • Entwicklung eines Simulationsmodells für hochskalierbare verteilte Datenbanken
    • Wahl eines realistischen Szenarios für die Evaluation
    • Evaluation des gewählten Szenarios, inklusive Identifikation der Parameter und Optimierung

    Technologien

    • C++
    • OMNeT++
    • Verteilte Datenbanken

    Literatur

    • Grunert, Hannes and Kasparick, Martin and Butzin, Björn and Heuer, Andreas and Timmermann, Dirk (2016) From Cloud to Fog and Sunny Sensors. In: Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", 12-14 Sep 2016, Potsdam, Germany.
    • Grunert, Hannes and Heuer, Andreas (2016) Datenschutz im PArADISE. Datenbank-Spektrum, 16 (2). pp. 107-117. ISSN 1618-2162
    • Peter Danielis, Sylvia T. Kouyoumdjieva, Gunnar Karlsson: DiVote: A Distributed Voting Protocol for Mobile Device-to-Device Communication. ITC 2016: 69-77
    • Peter Danielis, Sylvia T. Kouyoumdjieva, Gunnar Karlsson: UrbanCount: Mobile crowd counting in urban environments. IEMCON 2017: 640 - 648