Abstract

We utilize tools from information theory to develop adaptive algorithms for two key problems in cellular networks, namely location tracking and resource management. The use of information theory is motivated by the fundamental observation that overheads in many aspects of mobile computing can be traced to the randomness, or uncertainty, in an individual user’s movement behavior. We present a modelindependent, information-theoretic approach for estimating and managing this uncertainty and relate it to the entropy or information content of the user’s movement process. Information-theoretic mobility management algorithms are very simple, yet reduce overhead by 80 % in simulated scenarios by optimally adapting to each individual’s movement. They also allow for flexible tradeoff between location update and paging costs. Simulation results also demonstrate how an information-theory motivated resource provisioning strategy can meet QoS bounds with very small wastage, thus dramatically reducing the overall blocking rate. 1

Citations