A fuzzy k-coverage approach for RFID network planning using plant growth simulation algorithm

Optimization of network planning is important for the performance improvement of the radio frequency identification (RFID) networks before deployment. This paper proposes an efficient approach for RFID network planning based on k-coverage. A k-coverage model, which is formulated as a multi-dimensional optimization problem with constraint conditions, is developed to evaluate the network performance. The plant growth simulation algorithm (PGSA) is used to optimize the RFID networks by determining the optimal adjustable parameters in the model. In the proposed approach, the objective function and the constraints are separately processed and no external control parameter is required. The simulation results demonstrate the effectiveness of the proposed approach using PGSA in comparison to other algorithms.