Efficient topology discovery protocol using IT-SDN for software-defined wireless sensor network

Joseph Kipongo, Ebenezer Esenogho, Theo G. Swart

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


The internet of things (IoT) and wireless sensor networks (WSNs) are two promising technologies for supporting new services and applications. However, because IoT and WSN entail interaction and transaction of device topology discovery protocols, WSN facing some challenges. Topology discovery (TD) is important for WSN in IoT since sensor nodes (SNs) are the main points of this network. Networking these SN (IoT-devices) has a few difficulties such as energy and bandwidth consumption, and data storage issues resulting from frequent interactions and transactions between devices. Because these challenges cannot be resolved by one solution, we focused on reducing the energy consumption associated with a WSN. We proposed software-defined networking (SDN) model to tackle energy-efficiency issue in a WSN setup by integrating SDN and WSN, which gave rise to a more robust system, software-defined wireless sensor network (SDWSN). In this direction, we proposed an improved fuzzy-logic-based strategy, fuzzy topology discovery protocol (FTDP). It used IT-SDN (an SDN-based WSN framework) to increase the network’s lifepan due to its low energy consumption. The link layer discovery protocol (LLDP) to build the SDN controller’s topology. The system’s performance was presented and compared, demonstrating that with an effective SDWSN discovery policy, energy efficiency is achievable.

Original languageEnglish
Pages (from-to)256-269
Number of pages14
JournalBulletin of Electrical Engineering and Informatics
Issue number1
Publication statusPublished - Feb 2022


  • Discovery protocol
  • Energy efficiency
  • Software-defined networking
  • Topology discovery
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Electrical and Electronic Engineering


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