ID Layer for Internet of Things Based on Name-Oriented Networking
DOI:
https://doi.org/10.26636/jtit.2013.2.1215Keywords:
Future Internet, ID-based routing, ID layer, Internet of Things, Name-Oriented NetworkingAbstract
Object and service identification is considered as one of the main challenges in the field of Internet of Things (IoT), which can be solved by the introduction of the so called ID (IDentifier) layer. The objective of this layer is to expose IoT objects and services offered by them, to users. Common approach for ID layer is to create it in overlay manner, on the top of existing network. This paper presents a novel architecture of the ID layer, which is characterized by embedding ID layer functionality into the network plane. Moreover, this approach takes advantage of the Name-Oriented Networking (NON) paradigm. To gain easy access to the IoT objects and services, as well as native support for multicast service, human readable ID-based unified addressing with hierarchical structure was exploited. Additionally, in-network caching of forwarded IoT data, inherited from the NON, helps to reduce total network load and supports applications during collaboration with energy-constrained sensors. Such sensors may enter sleep mode to save energy and then the network nodes can serve requests for sensing data, arrived from applications, by using data stored in nodes’ cache. The paper shows the concept of NON-based ID layer and describes functional architecture of network node paying attention on modules and mechanisms related with ID layer functionality. Primary ID layer processes, i.e., object/service registration, resolution and data forwarding are explained in detail. Moreover, the ID-aware network node was implemented on Linux-based platform and tested to check its forwarding characteristics. The tests showed the performance of the of ID network node in data plane operations, which are the more sensitive for scalability issues.
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Copyright (c) 2013 Journal of Telecommunications and Information Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.