Parametric heuristic schemes for performance improvement in Frame Slotted Aloha based RFID systems

The performance of the Dynamic Frame Slotted Aloha (DFSA) based RFID Anti-Collision Algorithm depends on the dynamically controlled frame size with the contending tags. Many literatures exploit the tag estimation method and attempt to enhance the system performance by regulating the frame size equal to the estimated tags. Unless the contending tag population is exactly estimated and the frame size is optimally adjusted the system performance cannot be maximized. However, it is always a difficult task to precisely estimate the contending tags in RFID systems. Thus to maximize the system performance, we used a parametric heuristic approach and proposed two simple schemes, namely ID-FSA (Improvised Dynamic-FSA) and ERP-FSA (Exponential Random Partitioning-FSA) algorithms. Unlike other algorithms, ID-FSA algorithm adjusts the optimal frame length for estimated tag population and ERP-FSA adjusts the contending tag population in such a way that the applied static frame size becomes optimal. The performance of our parametric heuristic schemes reveals that there are some potential benefits that can be achieved by adjusting the tags equivalent to the optimal frame length, moreover, regulating the optimal frame length for estimated tags can maximize the system performance.