In this letter, we propose an effective cooperative caching system under the assumption that each web object is accessed randomly. Under this assumption, the access frequency per unit time is given by Poisson distribution and the probability distribution of the web object in the future is derived. Based on this probability distribution, one can obtain the criterion to allocate the web objects with more access expected to the cache servers closer to clients. It is also shown that there is a tradeoff between the precision to allocate objects and the efficiency of caching.

To develop highly reliable switching software efficiently, a more powerful computer-aided verification system is needed. In this paper, we present an object-oriented switching software verification system, focusing on the basic concept and verification method. The system consists of three basic functions: a model of the switching system, a simulation control mechanism, and a verification mechanism. We also give our evaluation of this system.

Proxy caches have been used for a very long time to enhance the performance of web access. Along with the recent development of CDN (Content Distribution Network), the web proxy caching has also been adopted in many main techniques. This paper presents a new viewpoint on the possible improvement to the cooperative proxy caching, which can reduce outbound traffic and therefore ideally result in better response time. We take notice to the regional total cost of cache objects for optimizing content distribution. By contrast to the regular removal policies based on single proxy server, we prefer to evaluate a retrieved web object based on the metrics gathered from multiply proxy caches regionally. We particularly introduce a concept called post-removal analysis, which is used in measuring the value of the removed objects. Finally, we use the real proxy cache Squid to implement our proposal and modify the well-known cache benchmarking tool Web Polygraph to test this cooperative prototype. The test results prove that the proposed scheme can bring noticeable improvement on the performance of proxy caching.

This paper describes the error probability of the second order BAM estimated by a computer simulation and an analytical calculation method. The computer simulation suggests that the iterations to retrieve a library pattern almost converge within four times and the difference between once and twice is much larger than that between twice and four times. The error probability at the output of the second iteration is estimated by the analytical method. The effect of the noise bits is also estimated using the analytical method. The BAM with larger n is more robust for the noise. For example, the noise bits of 0.15n cause almost no degradation of the error probability when n is larger than 100. If the error probability of 10-4 is allowable, the capacity of the second order BAM can be increased by about 40% in the presence of 0.15n noise bits when n is larger than 500.

This paper describes relation between the number of library pairs and error probability to have all the pairs as fixed points for second-order bidirectional associative memory (BAM). To estimate accurate error probability, three methods have been compared; (a) Gaussian approximation, (b) characteristic function method, and (c) Hermite Gaussian approximation (proposed by this paper). Comparison shows that Gaussian approximation is valid for the larger numbers of neurons in both two layers than 1000. While Hermite Gaussian approximation is applicable for the larger number of neurons than 30 when Hermite polynomials up to 8th are considered. Capacity of second-order BAM at the fixed error probability is estimated as the function of the number of neurons.