MURAL - Maynooth University Research Archive Library



    Complex Event Processing in Smart City Monitoring Applications


    Khazael, Behnam, Malazi, Hadi Tabatabaee and Clarke, Siobhan (2021) Complex Event Processing in Smart City Monitoring Applications. IEEE Access, 9. pp. 143150-143165. ISSN 2169-3536

    [thumbnail of HadiTabatabaeeSmart2021.pdf]
    Preview
    Text
    HadiTabatabaeeSmart2021.pdf

    Download (2MB) | Preview

    Abstract

    Managing multi-tenant edge devices with heterogeneous capabilities scattered across an urban area requires significant communication and computing power, which is challenging when devices are also resource-constrained. These devices play a crucial role in smart city monitoring systems by notifying various municipal organizations about a wide range of ongoing complex events. Some recent approaches in complex event processing use a publish-subscribe architectural pattern to decouple simple event producers from complex event consumers. However, they did not fully address communication efficiency or diverse quality of service (QoS) requirements in aggregating events. This paper proposes a new architecture that integrates the publish-subscribe architectural pattern with software-defined network technology for urban monitoring applications. The architecture enhances monitoring applications with capabilities of distributed processing and detection of complex events. It also enables application developers to define QoS requirements and supports the TESLA complex event specification language. The main focus of our work is on energy and network efficiency. The simulation results demonstrate significant improvements in energy consumption and data packet traffic compared to three close baselines.
    Item Type: Article
    Keywords: Fog computing; Internet of Things; edge computing; smart city; software-defined networking; publish-subscribe architecture; complex event detection; event-based system;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 18616
    Identification Number: 10.1109/ACCESS.2021.3119975
    Depositing User: IR Editor
    Date Deposited: 06 Jun 2024 13:40
    Journal or Publication Title: IEEE Access
    Publisher: IEEE
    Refereed: Yes
    Related URLs:
    URI: https://mural.maynoothuniversity.ie/id/eprint/18616
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only (login required)

    Item control page
    Item control page

    Downloads

    Downloads per month over past year

    Origin of downloads