We propose an approximation for the loss probability, P/sub L/(x), in a finite buffer system with buffer size x. Our study is motivated by the case of a high-speed network where a large number of sources are expected to be multiplexed. Hence, by appealing to central limit theorem type of arguments, we model the input process as a general Gaussian process. Our result is obtained by making a simple mapping from the tail probability in an infinite buffer system to the loss probability in a finite buffer system. We also provide a strong asymptotic relationship between our approximation and the actual loss probability for a fairly large class of Gaussian input processes. We derive some interesting asymptotic properties of our approximation and illustrate its effectiveness via a detailed numerical investigation.

Presents the analytical methods to evaluate the forward/inverse force transmission capabilities of fully parallel manipulators. Two eigenvalue problems corresponding to the forward and inverse force transmission analyses are formulated. In view of the forward force transmission analysis, the conditions of the maximum isotropic force and moment transmissions are investigated for both planar and spatial parallel manipulators. Finally, numerical examples of the forward and inverse force transmission analyses are presented and the numerical algorithm of selecting actuator forces in the whole reachable workspace is suggested.

This paper presents the analytical methods to evaluate the forward/inverse kinetostatic capabilities of robotic manipulators. The eigenvalue problems corresponding to the forward and inverse kinetostatic capability analyses have been formulated. The forward kinetostatic capability analysis is to determine the magnitude bounds of the force and moment (linear and angular velocity) vectors generated at the end-effector for the given magnitude of actuating forces (velocities). Conversely, the inverse analysis is to find the magnitude bound of actuating forces (velocities) for the given magnitudes of the force and moment (linear and angular velocity) vectors at the end-effector. The inverse analysis is important since it can provide a designer with valuable information about how to choose the actuators. It has been shown that the eigenvalues from the forward and inverse analyses have a reciprocal relation with each other, which implies that solving either of the eigenvalue problems may complete the forward/inverse kinetostatic capability analyses. It has been also presented that the proposed kinetostatic capability analysis can be extended to redundant manipulators.