Abstract
An increasing fraction of the data disseminated through the Internet varies frequently and unpredictably. These time-varying data are generally used in real-time information delivery applications, such as stock update, weather data and sports score. Nowadays, most of the web servers running the HTTP protocol, clients need to regularly pull the time-varying data according to the variation of the occurrences received by the clients. However, the effective and reliable approach is pushing from the server. That is, a server with push capability retains state information affiliated to clients then pushes only those changes that are of interest to the clients. Yet, the server bandwidth and the network bandwidth are both limited, the total number of push and pull is restricted by a prior bound. So, the foundation of pushing and pulling time-varying data is to maintain the coherency control as well as to regulate the pull interval simultaneously. Note that these push and pull techniques are complementary to each other. In pure pull approach, the degree of temporal coherency attained is relatively low while in pure push approach, it is rather high. In this thesis, we present an interaction mechanism for incorporating both push and pull techniques. First, an approach that adaptively adjusts the pull interval due to the variation of the perceived data is presented. Then, we utilize push events to deal with unpredictable spike using the coherency control. Finally, we let the push event adjusts the pull interval to prevent the ineffective pulls. Besides, several dimensions have been compared in our results: communication overhead, temporal coherency and fidelity. Experimental results indicate that the proposed adaptive time-varying data dissemination is expected to meet diverse coherency control and for the effective and scalable utilization of server and network resources.