The heterogeneity in the communicating terminals needs to he handled through software-supported adaptation, The real-time dynamical adaptation brings the system more time cost unavoidably. In this paper, we propose QoS pre-estimation for user admission control and system load control. Feedback acts as adjuster of the input parameters of the pre-estimate module. We present tests results to evaluate our approach, The test results show that our service quality control mechanism is effective.
This paper describes the theory, implementation, and experimental evaluation of an Aggregation Cache Replacement （ ACR ） algorithm. By considering application background, carefully choosing weight values, using a special formula to calculate the similarity, and clustering ontologies by similarity for getting more embedded deep relations, ACR combines the ontology similarity with the value of object and decides which object is to be replaced. We demonstrate the usefulness of ACR through experiments. （a） It is found that the aggregation tree is created wholly differently according to the application cases. Therefore, clustering can direct the content adaptation more accurately according to the user perception and can satisfy the user with different preferences. （b） After comparing this new method with widely-used algorithm Last-Recently-Used （LRU） and First-in-First-out （FIFO） method, it is found that ACR outperforms the later two in accuracy and usability. （c） It has a better semantic explanation and makes adaptation more personalized and more precise.
The heterogeneity in the communicating terminals needs to be handled through software-supported adaptation. A QoS （quality of service） pre-estimation for user admission control and system load control is proposed. In the QoS pre-estimation, the content quality and wait time characteristics are combined together. The feedback control that acts as an adjuster of the input parameters of the pre-estimate module to improve the estimate accuracy is also described in detail. Test results show that the service quality control mechanism is effective, and the system capacity can be improved.
