ICN based Architecture for IoT
draft-zhang-iot-icn-architecture-01

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Last updated 2014-12-05 (latest revision 2014-06-03)
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This Internet-Draft is no longer active. A copy of the expired Internet-Draft can be found at
https://www.ietf.org/archive/id/draft-zhang-iot-icn-architecture-01.txt

Abstract

Internet of Things (IoT) promises to connect billions of objects to Internet. After deploying many stand-alone IoT systems in different domains, the current trend is to develop a unified IoT platform so that objects can be made accessible to applications across organizations and domains. Towards this goal, quite a few proposals have been made to build a unified IoT platform as an overlay on today's Internet. Such an overlay solution, however, is inadequate to address the important challenges posed by a unified IoT system, especially in terms of mobility, scalability, and communication reliability, due to the inherent inefficiencies of the current Internet. To address this problem, we propose to build a unified IoT platform based on the Information Centric Network (ICN) architecture, which we call ICN-IoT. ICN-IoT leverages the salient features of ICN, and thus provides seamless mobility support, scalability, and efficient content and service delivery. In this proposal, we first present a few popular IoT scenarios in smart homes, smart grid, smart transportation, and smart healthcare. Then we identify a list of important requirements with the unified IoT architecture that promises to support tens of billions of objects. After discussing the weaknesses of the current overlay- based IoT solution, we propose an ICN-based solution, ICN-IoT, which can sufficiently satisfy these requirements. We present an example ICN-IoT architecture and discuss how it supports efficient data discovery, data processing and data distribution. Finally, we show that ICN-IoT efficiently supports context- based scenarios, which are very common for many IoT applications.

Authors

Yanyong Zhang (yyzhang@winlab.rutgers.edu)
Dipankar Raychadhuri (ray@winlab.rutgers.edu)
Ravi Ravindran (ravi.ravindran@huawei.com)
Guoqiang Wang (gq.wang@huawei.com)

(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)