Abstract: The embodiments relate to modeling wireless communications in a network. In wireless communications, the nodes share one or more wireless communication channels. When a node has data to transmit, it must contend with the other nodes for access to the wireless communication channel. In the embodiments, the model is configured to simulate the throughput effects of contention including delays caused by retransmissions due to interference and collisions, listen-and-backoff, unavailability of time slots, etc. The occurrence of failed/dropped transmissions due to buffer overflows, excessive retransmission attempts, and unintended collisions are modeled as well. In addition, the embodiments may simulate the effect of mobility by the nodes and the effect of the location of the nodes relative to each other.

Abstract: The embodiments relate to modeling wireless communications in a network. In wireless communications, the nodes share one or more wireless communication channels. When a node has data to transmit, it must contend with the other nodes for access to the wireless communication channel. In the embodiments, the model is configured to simulate the throughput effects of contention including delays caused by retransmissions due to interference and collisions, listen-and-backoff, unavailability of time slots, etc. The occurrence of failed/dropped transmissions due to buffer overflows, excessive retransmission attempts, and unintended collisions are modeled as well. In addition, the embodiments may simulate the effect of mobility by the nodes and the effect of the location of the nodes relative to each other.

Abstract: Simulation models of media access control and physical layer characteristics facilitate the simulation/emulation of a variety of phenomena that affect transmissions via a wireless media. Such phenomena include media access contention delays, packet drops, and retransmissions that are generally dependent upon changes in transmitter/receiver locations. Each wireless environment is characterized by a model of the communication channel that characterizes transmission effects based on the number of competing transmitters in the environment, which is dynamically determined based on the location of each node in the environment. Additionally, the location of nodes is used to simulate the effects of ‘hidden nodes’, nodes that are unknown to a transmitting node but can interfere with the reception of transmissions at a receiving node. Each device/node model in the wireless environment preferably accesses the same model of the communication channel, thereby minimizing the amount of detail required at each device model.

Abstract: First-order effects of hypothesized fault conditions are determined by propagating discrete test packets between select nodes and noting the change of path, if any, taken by the test packet under each condition relative to the fault-free path. Tools are provided to create classes of node pairs of interest, and test packets are created only for select classes. The network is analyzed to identify fault conditions that are likely to impact system performance, and only these fault conditions are simulated. By providing a methodology for selecting classes of node pairs to test, and prioritizing the faults to simulate, a first-order survivability analysis of large networks can be performed efficiently and effectively. The efficiency of this technique is also enhanced by providing test packets that are representative of a wide range of possible source-destination combinations, and by evaluating only the source-destination combinations that may be directly affected by each fault condition.

Abstract: First-order effects of hypothesized fault conditions are determined by propagating discrete test packets between select nodes and noting the change of path, if any, taken by the test packet under each condition relative to the fault-free path. Tools are provided to create classes of node pairs of interest, and test packets are created only for select classes. The network is analyzed to identify fault conditions that are likely to impact system performance, and only these fault conditions are simulated. By providing a methodology for selecting classes of node pairs to test, and prioritizing the faults to simulate, a first-order survivability analysis of large networks can be performed efficiently and effectively. The efficiency of this technique is also enhanced by providing test packets that are representative of a wide range of possible source-destination combinations, and by evaluating only the source-destination combinations that may be directly affected by each fault condition.

Abstract: A sub-system is provided to a discrete event simulator (DES) to expedite simulation execution by first detecting a non-quiescent steady-state condition in the simulated system, and when the steady-state condition is detected, the simulator determines a state, and subsequently simulates the system at a skip-ahead time using this determined state, or a predicted state based on the determined state. Convergence analysis is used to determine whether the system is at, or approaching, a steady-state condition. This convergence skip-ahead process achieves faster analysis by avoiding the computation that would conventionally be required to simulate the system behavior during the time interval that is skipped.

Abstract: Simulation models of media access control and physical layer characteristics facilitate the simulation/emulation of a variety of phenomena that affect transmissions via a wireless media. Such phenomena include media access contention delays, packet drops, and retransmissions that are generally dependent upon changes in transmitter/receiver locations. Each wireless environment is characterized by a model of the communication channel that characterizes transmission effects based on the number of competing transmitters in the environment, which is dynamically determined based on the location of each node in the environment. Additionally, the location of nodes is used to simulate the effects of ‘hidden nodes’, nodes that are unknown to a transmitting node but can interfere with the reception of transmissions at a receiving node. Each device/node model in the wireless environment preferably accesses the same model of the communication channel, thereby minimizing the amount of detail required at each device model.

Abstract: A method and system for flow propagation analysis uses ‘tracers’ that are iteratively propagated through a simulated network between source and destination elements. These tracers are structured to contain traffic flow information from source to destination, and to reflect changes as the flow is affected by each element along the path from source to destination. The resultant flow information at the destination corresponds to the effective throughput from the source to the destination, and the flow information at the output of each intermediate element in the network corresponds to the potentially achievable throughput through that element for the given source-to-destination flow.

Abstract: A method and system for flow propagation analysis uses ‘tracers’ that are iteratively propagated through a simulated network between source and destination elements. These tracers are structured to contain traffic flow information from source to destination, and to reflect changes as the flow is affected by each element along the path from source to destination. The resultant flow information at the destination corresponds to the effective throughput from the source to the destination, and the flow information at the output of each intermediate element in the network corresponds to the potentially achievable throughput through that element for the given source-to-destination flow.

Abstract: A sub-system is provided to a discrete event simulator (DES) to expedite simulation execution by first detecting a non-quiescent steady-state condition in the simulated system, and when the steady-state condition is detected, the simulator determines a state, and subsequently simulates the system at a skip-ahead time using this determined state, or a predicted state based on the determined state. Convergence analysis is used to determine whether the system is at, or approaching, a steady-state condition. This convergence skip-ahead process achieves faster analysis by avoiding the computation that would conventionally be required to simulate the system behavior during the time interval that is skipped.