Modeling and simulation of an improved random direction mobility model for wireless networks using colored Petri nets

Wireless networks have received increased attention from researchers due to their extensive set of applications and ubiquitous communication facility. The underlying mobility model plays a key role in mobility management, which is a prominent communication means in delivering services to mobile users accurately. Random direction is a synthetic mobility model that is widely used in simulators, while simulation is universally considered the most effective method for the design and analysis of the characteristics of mobility models. However, simulation is limited in its capabilities and it may generate unrealistic, error-prone results and consume more time. Further, the random direction mobility model produces unrealistic movement patterns due to a sharp turn problem and it forces the mobile host to travel to the edge of the terrain. To alleviate the issues of the random direction mobility model, this paper presents a colored Petri net (CPN)-based formal approach as an improved direction mobility model. Further, the proposed algorithm to tackle the sharp turn problem is implemented by using the CPN formalism. The formal semantics of the CPN allow a graphical, intuitive approach to design, simulate, execute, and validate the model.