Research On Content Acquisition And Cache Deployment Strategies Of Content Service System

Under the environment of triple nework convergence, there are more and more rich content and the type of business, in which multimedia content is one of the main business. Multimedia content service system is a modern service system platform which is based on the the high-speed broadband network, show the text, sound, images, video and other digital media content to the supported access terminal like PC, mobile phones, set-top boxes and other fixed or mobile terminal in an interactive form. With the rapid development of the multimedia industry, the rapid emergence of new multimedia services, new products and the increasing of the number of users put forwrd the higher demand of the content service system.This dissertation relies on the issue "The Development of Collaborative Supporting Environment for Operation, Management, and Control of New Generation Services", which under the national863major project "new generation of high-trusted network", focues on and goes deep into the technologies of content acquisition, service node choose, and cache deployment strategies for the construction of content service system. The main contributions and innovations are as follows:1). A dynamic adjusting preemptive multi-priority based strategy for content acquisition is proposed. This strategy considers four aspects of the task, they are video type,the acquising history, the filesize of the video, the waiting time, then it adjusts the priority of the video in the waiting queue periodically by the acquising history The simulate result shows that the strategy can achieve a balance of the total waiting time between the two video types and it can adjust the parameter to adjust the seqence of the video, for the flexibility of video content acquising.2). A tabu search-based algorithm is porposed for k additional services node address selection problem, based on the revenue model. The algorithm uses a dynamically adjusted taboo object-wide policy to avoid the algorithm into a local optimal solution, as to improve the quality of the solution. Simulation results show that, under different parameters, tabu search algorithm can obtain better results than GreedyAdd, and GreedyRemove algorithm. Tabu search algorithm execution time is higher than GreedyAdd and GreedyRemove, but the k additional services node address selection problem does not require real-time, to sacrifice the time of the algorithm complexity to obtain better results is feasible.3). A sequential add algorithm for the cooperated cache deployment problem and a dynamic programming algorithm for the QoS aware cache deployment problem are proposed. The sequential add algorithm utilizes the object popularity, network distance, the request information that every node receive and system cache distribution information, every node that on the request path make a decision on cache deployment in sequence, meanwhile, this algorithm distributes the calculation to the nodes on the request path. As the simulation result shows, this sequential add algorithm has higher hit ratios and lower access latency than LRU and Graph Algorithm. The dynamic programming algorithm first to ensure the requested QoS requirements are met, on this basis, the cache deployment problem is decomposed into a series of sub-problems, and then use dynamic programming algorithm to find the optimal cache deployment. The simulation results show the dynamic programming algorithm can achive a good balance between the access latency and the requested availability. When the request is more concentrated, the dynamic programming algorithm can have better performance than the MODULO and LRU both in access latency and requested availability.