Modeling of task allocation in wireless sensor actors networks to increase actors' utilization using GSPN

Unresolved challenges in scheduling and allocation of tasks to actors in Wireless Sensor Actor Networks (WSANs) have led to lower than expected efficiency of these networks. Since actors in a WSAN may have various capabilities in performing allocated tasks, applying proper scheduling policies can improve the performance of network. The aim of this paper is to maximize total utilization of actors in performing tasks within WSAN. We proposed a Generalized Stochastic Petri Net (GSPN) model to show the task allocation policy applied by the network sink. Then, to achieve maximum actors' utilization, the arrival rate of tasks for each actor should be calculated based on the capability of that actor. Steady state analyzing of the GSPN model and calculating the task dispatching weights at each of the actors, task arrival rates is figured out. The results of applying the proposed GSPN to model allocation of tasks to actors in a typical WSAN demonstrate the applicability of the model

Keywords:

Wireless Sensor Actor Network , Task allocation , Generalized Stochastic Petri nets , Actors' Utilization