2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT) · 2017 · 82 citations · 9 references
ComputingInformation TechnologyComputer NetworksInternet Of ThingsMobile ComputingIot ArchitectureIot NetworkingWireless Sensor NetworksInternet Of Things NetworkingIpv6 AddressingNeighbor DiscoveryNeighbor Discovery ProtocolsNetwork Topology DiscoveryTopology DiscoveryTopology MaintenanceTopology Management
The Internet of Things envisions a vast network of interconnected objects whose topology changes dynamically, making continuous neighbor discovery essential but energy‑intensive due to conventional active listening. This paper investigates the architecture of an IoT network and the functions of its layers, focusing on neighbor discovery. The authors analyze the classic IPv6 neighbor discovery protocol and propose an optimized variant that reduces active listening, thereby lowering energy consumption while maintaining topology awareness.
The Internet of Things (IoT) is a future technology expected to consist of plenty real world objects or things [1]. These devices collaborate together and possibly form a network of things/nodes. Since the nodes can be stationary or mobile the network topology frequently changes, therefore node or neighbor discovery is a continuous process. The process of collaboration involves the devices to discover each other and learn network topology. The conventional node discovery procedures require the nodes to do active listening which would waste significant amount of energy just for establishing topology information [2]. This paper studies the basic architecture of an IoT network and the functions of each of its layers. Further we analyzes Classic Neighbor discovery procedure followed by IPv6 nodes, and an Optimized techniques which modifies this classic approach to reduces active listening and makes it more suitable for IoT.
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On Networking of Internet of Things: Explorations and Challenges
Huadóng Ma, Liang Liu, Anfu Zhou et al. · IEEE Internet of Things Journal · 2015 · 84 citations