A Time and Capture Probability Aware Closed Form Frame Slotted ALOHA Frame Length Optimization PROJECT TITLE :A Time and Capture Probability Aware Closed Form Frame Slotted ALOHA Frame Length OptimizationABSTRACT:Minimizing the reading time in dense radio-frequency identification (RFID) networks could be a vital issue. Commonly used RFID systems are based on frame alotted ALOHA (FSA) for tag anti-collision management. The usual approach for improved reading times with massive tag populations is that the optimization of the number of slots per frame. In real RFID systems, the slot period depends on the slot kind (i.e. idle, successful, or collided). Further, collided slots might be converted to successful slots by capturing the strongest transponder, i.e. the therefore-called capture result. Recent publications have proposed numerical solutions for obtaining the optimum frame length beneath these assumptions. The authors employ numerical solutions that need Multi-dimensional look-up tables for getting the optimum frame length. In this letter, we propose a closed kind answer for the analytical calculation of the optimum frame length. The proposed resolution gives a novel closed kind equation for the frame length considering the various slot durations and therefore the capture impact. Moreover, this letter presents a replacement method to calculate the capture likelihood per frame. Simulations indicate that the proposed solution offers accurate results for all relevant parameter configurations while not any would like for multi-dimensional look-up tables. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Leveraging Heterogeneous Power for Improving Datacenter Efficiency and Resiliency Performance Comparison of EKF-Based Algorithms for Orientation Estimation on Android Platform