SNAIL gateway: Dual-mode wireless access points for WiFi and IP-based wireless sensor networks in the internet of things

One of the important challenges in the Internet of Things (IoT) is how to acquire the physical context of things. IP-based wireless sensor networks (IP-WSNs) could be a promising approach to collecting the physical context of things and to integrating WSNs to the Internet. However, realizing IP-WSNs in IoT exposes two major challenges. One is how to embed the Internet Protocol (IP) in resource-constrained sensor nodes. The other is how to achieve real-world deployment of WSNs and its integration with the Internet on the fly and on the cheap. In this paper, we present the SNAIL (Sensor Networks for All-IP World) project and introduce a new type of IP-WSN gateway, which supports dual wireless access points for WiFi and IP-WSN, enabling deployment of SNAIL nodes in an easy and rapid manner as for the solution. To show the proof-of-concept, we implement a new SNAIL platform from tiny sensor nodes to a gateway.

[1]  Daniel Minoli IPv6 Over Low‐Power WPAN (6Lowpan) , 2013 .

[2]  Young-Joo Kim,et al.  SSL-Based Lightweight Security of IP-Based Wireless Sensor Networks , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[3]  David E. Culler,et al.  Transmission of IPv6 Packets over IEEE 802.15.4 Networks , 2007, RFC.

[4]  Daeyoung Kim,et al.  Inter-MARIO: A Fast and Seamless Mobility Protocol to Support Inter-Pan Handover in 6LoWPAN , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[5]  Adam Dunkels,et al.  Contiki - a lightweight and flexible operating system for tiny networked sensors , 2004, 29th Annual IEEE International Conference on Local Computer Networks.

[6]  Adam Dunkels,et al.  Full TCP/IP for 8-bit architectures , 2003, MobiSys '03.

[7]  Daeyoung Kim,et al.  SNAIL: an IP-based wireless sensor network approach to the internet of things , 2010, IEEE Wireless Communications.

[8]  David E. Culler,et al.  TinyOS: An Operating System for Sensor Networks , 2005, Ambient Intelligence.