A Simple Mobility Model Realizing Designated Node Distributions and Natural Node Movement

In mobile wireless networks such as WSNs, WMNs and MANETs, movement of sensor nodes, clients and relay nodes has a great impact on the performance. Nevertheless, geography is too simplified in random-based mobility models such as RWP, while it is unrealistic to prepare trace-based mobility patterns for potential combinations of geography and mobility. To fulfill the gap, this paper provides a new method to automatically generate natural mobility patterns realizing designated node distributions. The goal of this work is to synthesize the movement patterns that can capture real (or intentional) node distributions. The method determines the probabilities of choosing waypoints from the subregions, satisfying the given node distributions. For this purpose, the relationship between the probabilities and node distributions is analyzed. Based on the analysis, the problem is formulated as an optimization problem of minimizing the error from the designated node distribution. Since the problem has non-linear constraints, a heuristic algorithm is designed to derive the near-optimal solutions. Several experiments have been conducted to show that a variety of node distributions could be realized in the proposed mobility model where the maximum error from the given node distributions was around 0.5%. Additionally, a case study has been conducted to show the applicability of the method.