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    Öğe
    Medical Data Retrieval By Named Data Networking of Things Architecture in Contiki NG OS
    (Institute of Electrical and Electronics Engineers Inc., 2022) Demir, Alper Kamil; Manap, Gokce
    Internet of Things (IoT) is becoming an important approach to accomplish healthcare monitoring where critical medical data retrieval is essential in a secure and private manner. Nevertheless, IoT devices have constrained resources. Therefore, acquisition of efficient, secure and private data is very challenging. The current research on applying architecture of Named Data Networking (NDN) to IoT design reveals very promising results. Therefore, we are motivated to combine NDN and IoT, which we call NDN-IoT architecture, for a healthcare application. Inspired by the idea, we propose a healthcare monitoring groundwork integrating NDN concepts into IoT in Contiki NG OS at the network layer that we call µNDN as it is a micro and light-weight implementation. We quantitatively explore the usage of the NDN-IoT approach to understand its efficiency for medical data retrieval. Reliability and delay performances were evaluated and analyzed for a remote health application. Our results, in this study, show that the µNDN architecture performs better than IP architecture when retrieving medical data. Thus, it is worth exploring the µNDN architecture further. © 2022 IEEE.
  • [ X ]
    Öğe
    On the Forwarding Information Base Sizing in Named Data Networking of Things
    (Institute of Electrical and Electronics Engineers Inc., 2022) Manap, Gokce; Bilgili, Sedat; Demir, Alper Kamil
    Named Data Networking (NDN) is a new network architecture derived from the success of the Internet. Specifically, NDN addresses and identifies data by naming. Source and destination host addresses are not required for data communication in the NDN because the data is uniquely named instead. In the NDN network, the Forwarding Information Base (FIB) table is responsible for data forwarding, the Pending Interest Table (PIT) is liable for holding the state of data forwarding process, and the Content Store (CS) is used to stock data chunks within the network to optimize the forwarding time to the data without contacting to the content producer. All these data structures consume the memory of devices existing in the Named Data Networking of Things (NDNoT). Accordingly, the size of the FIB, PIT and CS needs to be carefully adjusted in NDNoT environments for performance tuning and Quality of Service (QoS) provisioning. In this study, we explore the issues of FIB sizing on average and maximum occupancy, reliability and maximum delay for constant bit rate (CBR) traffic where each content producer is addressed with a prefix name in the Cooja simulator environment. The results indicate that FIB table size has an impact on the reliability and maximum delay. During the number of records in FIB outpaces the count of nodes in the network, the reliability decreases gradually. Therefore, in constrained NDNoT environment careful allocation of the memory among FIB, PIT and CS becomes an important issue. According to our knowledge so far, this work is the first study showing the effect of FIB table on the performance in an NDNoT environment. © 2022 IEEE.