A Method For Estimating Rfid Protocol Execution Time Based On Flowgraph Model

The TPG protocol designed to efficiently group all tags according to a given partition so that tags in the same group will have the same group ID. Using the TPG protocol; the RFID reader sends the group ID followed by the IDs of the RFID tags only once without repeatedly sending the same group ID to each RFID tag. An existing theoretical solution proposed to measure the execution time of the TPG protocol does not provide comprehensive solutions. For example, the missing solutions consider the RFID tag response time and can only be used to measure the TPG protocol execution time in the RFID reader-to-RFID tag (one-to-many) environment, but not in the RFID reader-to-RFID tag (many-to-many) environment. A flowgraph model is proposed in this research to overcome the limitations of the existing TPG protocol equation. It is essential to measure the execution time of the TPG protocol in a many-to-many RFID network topology because the application of the TPG protocol is not limited to a one-to-many RFID network topology. Currently, the many-to-many RFID network topology widely uses to improve authentication efficiency. Therefore, measuring the execution time of the TPG protocol in a many-to-many RFID network topology is essential to determine the efficiency of the TPG protocol. The proposed equations based on the flowgraph model to estimate the total execution time of the TPG protocol can apply in three types of RFID network topologies: one-to-one (RFID reader and RFID tag), one-to-many (RFID reader and RFID tags), and many-to-many (RFID reader and RFID tags)

Deadlock detection and dihomotopic reduction via progress shell decomposition

Deadlock detection for concurrent programs has traditionally been accomplished by symbolic methods or by search of a state transition system. This work examines an approach that uses geometric semantics involving the topological notion of dihomotopy to partition the state space into components, followed by an exhaustive search of the reduced state space. Prior work partitioned the state-space inductively; however, this work shows that a technique motivated by recursion further reduces the size of the state transition system. The reduced state space results in asymptotic improvements in overall runtime for verification. Thus, with efficient partitioning, more efficient deadlock detection and eventually more efficient verification of some temporal properties can be expected for large problems --Abstract, page iii

Model reductions in MDG-based model checking

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

The Effect Of Direct Yaw Moment On Human Controlled Vehicle Systems

Advances in computing technology have had a profound impact on the design and development of modern vehicle systems. These advances have provided the basis for virtual design and testing in simulated environments, as well as the development of active control systems capable of providing improved vehicle safety, efficiency, and performance. Continued developments in hybrid powertrains and on-board computing will provide for greater amounts of control, through the integration of larger numbers of actuators and more complex control schemes. The intention of this research is to investigate the effects of advanced vehicle dynamics controls on the human operated vehicle system. Hybrid electric vehicle systems incorporating multiple electric drive motors are capable of actively distributing drive and braking torque to the individual wheels of the vehicle. The modulation of these torques can be used to optimize or alter the dynamic response of the vehicle, through the application of a direct yaw moment. A control structure capable of determining and dynamically allocating appropriate control signals for over-actuated vehicle systems is proposed. A dynamic simulation of a virtual prototype BMW 330i is utilized to evaluate the effects of active drive torque vectoring on vehicle response. The effects of the proposed system on the human operator are also evaluated, through the use of driver model in-the-loop simulations. The results presented indicate the promising potential of direct yaw moment control in modulating the response of human operated vehicle systems. The interactions between the human driver model and control systems were shown to be favourable. The scientific contributions and implications of the research are detailed, including application of closed-loop simulation to engineering education. Conclusions on the efficacy of developed models, methodologies and systems are given. Finally, recommendations on potential improvements and future research regarding vehicle modelling and motion control are provided