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CANVIS: context-aware network visualisation using smartphones

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review



This paper describes a prototype application which enables the real-time monitoring and visualization of large Wide Area Networks (WANs) using smartphone devices. The techniques employed allow field engineers to rapidly gain access to a large information repository through the use of a camera equipped mobile phone. More specifically, the use of visual codes [11] attached to networking hardware and infrastructure cabling enables the real-time visualization of network traffic and statistics to be triggered by the capturing of images from a personal device. Moreover, the location and orientation of the phone are used as contextual parameters in order to control the specific information to be retrieved. The prototype described in this paper is currently under evaluation by Information Systems Services (ISS) which is responsible for network support across Lancaster University, the student residences network and also a large regional WAN spanning the whole of the North West of England. Our aim was to establish whether or not this user interaction technique could be harnessed for a real world application that would benefit field engineers who are responsible for maintaining a live production network interconnecting tens of thousands of hosts.

Bibliographic note

This work stems from our ongoing partnership with the university's information systems services (ISS) in the Network Research and Special Projects Unit, and combines experimental systems research with real deployment and end-user trials. The paper describes the CANVIS platform, which enables the real-time monitoring and visualisation of large Wide Area Networks (WANs) using Smartphone devices. The techniques employed allow networking field engineers access to real-time visualisations of network traffic and router statistics through a Smartphone, equipped with visual code recognition software. The acceptance rate for MobileHCI 2005 was 21%.