<p>Distributed real-time system consists of many tasks on different processors communicating with</p><p>each other. The communication between these tasks must occur in bounded time. In our thesis we</p><p>are considering a holistic approach to estimate the end-to-end delays between two processors</p><p>communicating with each other. For both tasks scheduled by fixed priority and dynamic priority,</p><p>the system model considered is time token passing ring. The method is described to calculate</p><p>worst-case communication delay of the message sent by certain tasks over the network. Once the</p><p>worst-case communication delay of the message is obtained, and all required parameters are</p><p>provided i.e. deadline of the message, transmission time of the packet etc, one can figure out how</p><p>many messages will successfully meet their deadline. Thus this will enable us to select</p><p>appropriate algorithm according to system requirement.</p>

Distributed real-time system consists of many tasks on different processors communicating with each other. The communication between these tasks must occur in bounded time. In our thesis we are considering a holistic approach to estimate the end-to-end delays between two processors communicating with each other. For both tasks scheduled by fixed priority and dynamic priority, the system model considered is time token passing ring. The method is described to calculate worst-case communication delay of the message sent by certain tasks over the network. Once the worst-case communication delay of the message is obtained, and all required parameters are provided i.e. deadline of the message, transmission time of the packet etc, one can figure out how many messages will successfully meet their deadline. Thus this will enable us to select appropriate algorithm according to system requirement.