We present and evaluate a class of signaling protocols for wireless digital networks. The presented signaling protocols are stable, they induce good delay characteristics and they possess resistance to feed back errors. We also evaluate a system deploying the IEEE 802.11 as a signaling protocol, instead. In the presence of relatively tight admission delay constraints in signaling, the latter is significantly inferior to our proposed signaling technique. As the above admission delay constraints diminish, the IEEE 802.11 MAC protocol breaks down, while our proposed signaling technique maintains its high performance characteristics.

We present, analyze, and numerically evaluate extended algorithms for detecting changes from an acting stochastic process to a number of possible alternatives. The algorithms are sequential, requiring minimal memory capacity and operational complexity, and they incorporate decision thresholds. The performance of the algorithms is controlled by the selection of the thresholds. An online learning algorithm adapts the thresholds dynamically, to attain prespecified error performance. Asymptotically, the first algorithmic extension detects the acting process correctly, in an expected stopping time sense. In addition, the probability of error induced by a reinitialization algorithmic extension converges asymptotically to zero, when the acting process changes infrequently (with order inversely proportional to the value of the decision thresholds). The presented algorithmic systems are quite powerful and their applications are numerous, ranging from industrial quality control, to identification of changes in patterns, to traffic and performance monitoring in high-speed networks.

We present, analyze, and numerically evaluate extended algorithms for detecting changes from an acting stochastic process to a number of possible alternatives. The algorithms are sequential, requiring minimal memory capacity and operational complexity, and they incorporate decision thresholds. The performance of the algorithms is controlled by the selection of the thresholds. Asymptotically, the first algorithmic extension detects the acting process correctly in an expected stopping time sense. In addition, the probability of error induced by a reinitialization algorithmic extension converges asymptotically to zero, when the acting process changes infrequently (with order inversely proportional to the value of the decision thresholds). The presented algorithmic systems are quite powerful and their applications are numerous, ranging from industrial quality control to traffic and performance monitoring in highspeed networks.

A. Burrell et al. (1993; 1994) described an implementation efficient capacity allocation protocol for multimedia traffic (voice, video, high and low speed data). The protocol determines the capacity allocation of each traffic dynamically, and induces moving boundaries within prespecified and fixed channel frames. The channel frames are selected to satisfy the jittering constraints of all the traffic, such as voice, video and high versus low speed data. The high level protocol, in conjunction with the channel frame structure and the specifics of the transmission policy, may satisfy all traffic and QOSs and may simultaneously attain high channel utilization, for certain variability conditions of the traffic rates and at relatively low implementation cost. In the work presented, the system stability, channel utilization, traffic rejection rate and packet/cell delay are examined. Performance evaluation results are presented.>