In a still more complex world of networks, devices, sensors and so forth, adaptivity to the surroundings is a key aspect for applications. This is in particular important for wireless, mobile scenarios, where we encounter the most complicated and dynamic changes of context (both user, service and device context). Examples of typical contextual information such as location, time, and network condition in mobile scenarios will be used to illustrate use cases for context management system, and how this information can be used to adapt applications and services to the user. These information are dynamic, and when accessed over networks for adaptivity purposes, access delays challenges the reliability of the information. This, in turn leads to potential misbehavior of adaptive applications to the end users great dissatisfaction.
In this course several important steps necessary to reliable and user acceptable context aware applications and services will be addressed. 1) Collection and distribution of dynamic context information elements, 2) modeling of selected stochastic context information with focus on location (Markov models etc.), 3) application design and development and 4) acceptance and interaction with users.
The course will focus context management as a network service, including reliability studies of access mechanisms and selected types of context information, e.g. location, working in a wireless mobile environment. Further, modeling of information elements will be of focus, since the dynamics of the information plays a crucial role in reliability of the information being used, where both stochastic as well as semantic models will be explained.
How contextual information is sampled and preprocessed is also an important aspect of context management, but is not covered in detail in this course. The Machine Learning course is in this regard recommended as a complimentary course.
Tentative course plan:
Day 1:
9:00 – 12:00 : Introduction to context aware systems and management (RLO)
13:00 – 16:00: Reliable collection and distribution of context information (RLO)
Day 2:
9:00-12:00 : Location as context information (JJN)
13:00 – 16:00 : Analytic modelling of stochastic information elements (JJN)
Day 3:
9:00 – 12:00 : Design and development of context adaptive applications (RLO)
13:00 – 16:00 : User acceptance and interaction (LBL)

Rasmus L. Olsen, email:

Rasmus L. Olsen, Aalborg University
Lars Bo Larsen, Aalborg University
Jimmy Jessen Nielsen, Aalborg University


November 11-14, 2013

Aalborg University

Zip code:


Number of seats:

October 21, 2013

Important information concerning PhD courses
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.