Secure Context-Aware Mobile SIP User Agent

Detta är en Master-uppsats från KTH/Kommunikationssystem, CoS


Context awareness is an important aspect of pervasive and ubiquitous computing. By utilizing contextual information gathered from the environment, applications can adapt to the user’s specific situation. In this thesis, user context is used to automatically discover multimedia devices and services that can be used by a mobile Session Initiation Protocol (SIP) user agent. The location of the user is captured using various sensing technologies to allow users of our SIP user agent to interact with network attached projectors, speakers, and cameras in a home or office environment.

In order to determine the location of the user, we have developed and evaluated a context aggregation framework that gathers and analyzes contextual information from various sources such as passive infrared sensors, infrared beacons, light intensity, and temperature sensors. Once the location of the user is determined, the Service Location Protocol (SLP) is used to search for services. For this purpose, we have implemented a mobile SLP user agent and integrated it with an existing SIP user agent. The resulting mobile SIP user agent is able to dynamically utilize multimedia devices around it without requiring the user to do any manual configuration.

This thesis also addressed the challenge of building trust relationship between the user agent and the multimedia services. We propose a mechanism which enables the user agent authenticate service advertisements before starting to redirect media streams. The measurements we have performed indicate that the proposed context aggregation framework provides more accurate location determination when additional sensors are incorporated. Furthermore, the performance measurements indicate that the delay incurred by introducing context awareness to the SIP user agent is acceptable for a small deployment such as home and office environment. In order to realize large scale deployments, future investigations are recommended to further improve the performance of the framework.

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