Finding context attributes
Using spatial indices to form high-level context attributes:
Nowhere (or everywhere) -> Garching -> FMI -> 1st floor -> AR lab
The SR graph nodes have a list of these attributes (if list is empty
These attributes group different SR subgraphs together into
ToDo: Are domains and supernodes the same?
Model bootstrapping mechanism
The context is used to specify a high-level spatial information
combined with the knowledge of the current infrastructure. This
information is used to optimize the search for new relations in the SR
graph because only the current neighborhood defined by the
attributes must be considered.
The initial context is "nowhere". The Ubitrack system broadcasts a
"HelpMe" request to all nodes in the current subnet (technical details
about building subnets not important here). This is realized by
"context estimation components" (services). They are capable of
broadcasting the messages as well as setting the attributes
- My local ID (unique in domains, must it be unique globally ?)
- My current context, modeled by attributes
- A list of my configurable context estimation services
If the request contains no context information, an "initial context
estimation" service is contacted. It returns following information:
- If context can be derived (e.g. from the fact that the connection
has been established), return it with a list of services
which can be contacted to refine the context.
- If not, return configuration data for the local context estimation
service. If no configuration is available, return the old context
with empty list.
If new context is returned with a list:
- Contact the new services from the list until the context cannot be
If configuration is returned:
- Reconfigure local services. Estimate the context yourself. If not
successful, use old context.
If old context is returned: Use it as current context.
Initial context service
This service must be found iff no context is available.
Model anonymous objects
The new concept of the context is used when new objects must be
identified in the SR graphs.
Picture here !
X is an object tracked by A
Y is an object tracked by B
The "real" ID of X is M2, the one of Y is M2. The question is how to
find the correct IDs and assign them to the anonymous objects.
Ubitrack must consider all measurements to find possible correlations
between X and M2 as well as between X and M1. This is inefficient in
great graphs. So we consider the spatial high-level context of both
subsystems to get only the relevant measurments.
To fine the correlations we must probably consider following
properties of the objects:
First derivation to eliminate static edges.
ToDo: is this working? -> see literature
ToDo: more properties to consider?
User setup: GPS tracker, WLAN
User exits at bus station. Send "HelpMe" request with no
contect. Return: configure your GPS tracker if you have one and send
information to service blablubb.
Blablubb returns context "You are in Garching".
ToDo: to be refined
- 19 Feb 2004