Ultra-wideband cognitive interrogator network for indoor location tracking - part 1: system architecture and network performance analysis

We explore the potential application of cognitive interrogator network (CIN) in remote monitoring of mobile subjects in domestic environments, where the ultra-wideband radio frequency identification (UWB-RFID) technique is considered for accurate source localization. We first present the CIN architecture in which the central base station (BS) continuously and intelligently customizes the illumination modes of the distributed transceivers in response to the systempsilas changing knowledge of the channel conditions and subject movements. Subsequently, the analytical results of the locating probability and time-of-arrival (TOA) estimation uncertainty for a large-scale CIN with randomly distributed interrogators are derived based upon the implemented cognitive intelligences. Finally, numerical examples are used to demonstrate the key effects of the proposed cognitions on the system performance

Performance analysis of a register insertion ring with a variable size buffer

There has been a recent revival of interest in the register insertion (RI) protocol because of its high throughput and low delay characteristics. Several variants of the protocol have been investigated with a view to integrating voice and data applications on a single local area network (LAN). In this paper the performance of an RI ring with a variable size buffer is studied by modelling and simulation. The chief advantage of the proposed scheme is that an efficient but simple bandwidth allocation scheme is easily incorporated. Approximate formulas are derived for queue lengths, queueing times, and total end-to-end transfer delays. The results are compared with previous analyses and with simulation estimates. The effectiveness of the proposed protocol in ensuring fairness of access under conditions of heavy and unequal loading is investigated.

Performance evaluation of a distributed algorithm for an inverse heat conduction problem

Numerical solutions of realistic 2-D and 3-D inverse problems may require a very large amount of computation. A two-level concept on parallelism is often used to solve such problems. The primary level uses the problem partitioning concept which is a decomposition based on the mathematical/physical problem. The secondary level utilizes the widely used data partitioning concept. A theoretical performance model is built based on the two-level parallelism. The observed performance results obtained from a network of general purpose Sun Sparc stations are compared with the theoretical values. Restrictions of the theoretical model are also discussed.