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Failure detection is a key technology in tolerant system. Failure detectors without adaptive mechanism cannot meet the requirements of QOS (quality of service) of applications because of the variations of the network in actual distributed system. Adaptive failure detectors should dynamically adjust the detecting quality according to the variations of the real-time state of the network. Assuming that the delay and loss of the messages is a random probability, a failure detection model based on the predicted message delay is proposed in this paper. A P_AC-AFD adaptive failure detection algorithm is realized based on the above model which is on the basis of the prediction from historical message delay and contains checking idea. Experimental results show that the algorithm can relieve the effect of the delay and loss of the message on the failure detection while ensuring the accuracy and completeness of detection

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The World Wide Web has become the primary means for information dissemination. Due to the limited resources of the network bandwidth, users always suffer from long time waiting. Web prefetching and Web caching are the primary approaches to reducing the user perceived access latency and improving the quality of service. In this paper, a SPN (Stochastic Petri Nets) model of Web prefetching and caching system is constructed, and based on which, the performance analysis of the integrated Web prefetching and caching model are made. The performance metrics latency, throughput are compared and analyzed theoretically. Simulations show that compared with caching mechanism, Web prefetching mechanism can further reduce the access latency, improve the throughput and the hit ratio efficiently. The performance evaluation based on the SPN model provides an implementation basis for Web prefetching and caching.

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