containing clear attribute dependences suggest that the answer to this question may be positive. This article shows that, although the Bayesian classifier’s probability estimates are only optimal under quadratic loss if the independence assumption holds, the classifier itself can be optimal under zero

Abstract. We study the weak convergence to Fractional Brownian motion and some examples with applications to traffic modeling. Finally, we get loss probability for queue-length distribution related to self-similar process. 1.

bounds for the positive least root of the functional equation x = b G(µ − µx) are then used to find the asymptotic bounds for the loss probabilities in certain queueing systems with a large number of waiting places, when only an empirical probability distribution function of an interarrival or service

of interest. The following key results are obtained. First, random loss leads to significant throughput deterioration when the product of the loss probability and the square of the bandwidth-delay product is larger than one. Unless network resources are specifically reserved for data traffic, data traffic

The purpose of this paper is to study the loss probabilities of messages in an M/M/1/K queueing system where in addition to losses due to buffer overflow there are also random losses in the incoming and outgoing links. We focus on the influence of adding redundant packets to the messages (as

Abstract – The probability of losing a customer in M/G/n/0 and GI/M/n/0 loss queuing systems with heterogeneous servers is minimized. The first system uses a queue discipline in which a customer who arrives when there are free servers chooses any one of them with equal probability, but is lost

In this paper we propose an approximation for the loss probability in a finite buffer system by making a simple mapping from the tail probability in an infinite buffer system. We focus on the case of a high-speed network where a large number of sources are expected to be multiplexed so that we

Abstract not found

in the Internet. Furthermore, RON was able to improve the loss rate, latency, or throughput perceived by data transfers; for example, about 5 % of the transfers doubled their TCP throughput and 5 % of our transfers saw their loss probability reduced by 0.05. We found that forwarding packets via at most one

distinctive fourfold pattern of risk attitudes: risk aversion for gains and risk seeking for losses of high probability; risk seeking for gains and risk aversion for losses of low probability.