An accurate Markov model for slotted CSMA/CA algorithm in IEEE 802.15.4 networks

In this letter we propose an Markov model for slotted CSMA/CA algorithm working in a non-acknowledgement mode, specified in IEEE 802.15.4 standard. Both saturation throughput and energy consumption are modeled as functions of backoff window size, number of contending devices and frame length. Simulations show that the proposed model can achieve a very high accuracy (less than 1% mismatch) if compared to all existing models (bigger than 10% mismatch).

Performance analysis of ONOE protocol - an IEEE 802.11 link adaptation algorithm

Link adaptation (LA) plays an important role in adapting an IEEE 802.11 network to wireless link conditions and maximizing its capacity. However, there is a lack of theoretic analysis of IEEE 802.11 LA algorithms. In this article, we propose a Markov chain model for an 802.11 LA algorithm (ONOE algorithm), aiming to identify the problems and finding the space of improvement for LA algorithms. We systematically model the impacts of frame corruption and collision on IEEE 802.11 network performance. The proposed analytic model was verified by computer simulations. With the analytic model, it can be observed that ONOE algorithm performance is highly dependent on the initial bit rate and parameter configurations. The algorithm may perform badly even under light channel congestion, and thus, ONOE algorithm parameters should be configured carefully to ensure a satisfactory system performance. Copyright © 2011 John Wiley & Sons, Ltd.

A novel algorithm of posture best fit based on key characteristics for large components assembly

Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors.