ABSTRACT
Towards a Universal Model for Personal Mobility Management in Wireless
Networks
Professor Sajal K. Das, Director Center for Research in Wireless Mobility
and Networking (CReWMaN), Department of Computer Science & Engineering, The
University of Texas at Arlington
The global convergence of wired/wireless telecommunication
networks and IP-based data networks to form a seamless global
personal communication system (PCS) has set up the stage for
a network independent universal location service. Symbolic
representation of location space in terms of cells is the key
to its viability. In this talk we will characterize the
complexity of the mobility tracking problem in a cellular
environment under an information-theoretic framework. We will
identify Shannon's entropy measure as a basis for comparing
user mobility models. By building and maintaining a dictionary
of individual user's path updates (as opposed to the widely
used location updates), we propose an adaptive on-line algorithm
called LeZi-update, that can learn subscibers' profiles.
This technique evolves out of the concepts of lossless compression.
The compressibility of the variable-to-fixed length encoding of
the acclaimed Lempel-Ziv family of algorithms reduces the update
cost, whereas their built-in predictive power can be effectively
used to reduce paging cost. Under this framework, universal learning,
estimation and prediction of personal mobility is still possible
for well-behaved users, in spite of the fact no single mobility
model works for the diverse set of wireless infrastructures.
Maintained by rbennett@cs.ucl.ac.uk