28-02-2013, 10:12 AM
Optimal Stochastic Location Updates in Mobile Ad Hoc Networks
Optimal Stochastic.doc (Size: 39 KB / Downloads: 22)
Abstract
we develop a stochastic sequential decision framework to analyze this problem. Under a Markovian mobility model, the location update decision problem is modeled as a Markov Decision Process (MDP). We first investigate the monotonicity properties of optimal NU and LSU operations with respect to location inaccuracies under a general cost setting. From the discovered separation property of the problem structure and the monotonicity properties of optimal actions, we find that 1) there always exists a simple optimal threshold-based update rule for LSU operations; 2) for NU operations, an optimal threshold-based update rule exists in a low-mobility scenario. In the case that no a priori knowledge of the MDP model is available, we also introduce a practical model-free learning approach to find a near-optimal solution for the problem..
EXISTING SYSTEM
Current model does not encompass user’s past behavior.
Can we incorporate knowledge of the physical world to improve accuracy?
Proposed System
Two types of location updates
–Neighborhood Update (NU) -update location information within a neighboring region
–Location Server Update (LSU) -update the node’s location information at one or multiple distributed location serv
Goals of Paper
Have you ever wished that you would come to know your friend’s locations without asking them?
Have you ever wished that you would get to know which friend is just few kilometers away from you and would then meet him personally?
The application “Friend Locator on Mobiles” solves all these problems. It offers below services