Clustered multimedia NOD: Popularity-based article prefetching and placement

According to the current profound development of multimedia and networking technologies, the way people communicate with, naturally, has evolved from a text-oriented into a multimedia-oriented. But, the VOD system technologies can't be easily applied to MNOD system because of the difference of tile basic data and its properties. This is the reason why we propose the MNOD system. NOD data composing news articles make a difference to VOD data in terms of media type and size, life cycle of articles and frequency of clients' interaction. Because of NOD data's intrinsic characteristics, NOD article popularity model may be different from that of VOD videos. Hence, we analyze statistically the log data of one electronic newspaper and show the popularity distribution of articles is different from Zipf's, which is a popularity model of VOD data. We propose a new article popularity model for NOD data, which we call Multi-Selection Zipf distribution. Also, we propose the article prefetching policy based on the popularity model and life cycle model of NOD articles for increasing performance in a MNOD system. And, we consider the data placement on the MNOD system with prefetch cache. The user requests can be serviced from a cache or a disk. Consequently in order to place a NOD data, we must consider the correlation between disks and cache according to data popularity. In this paper, we propose the data placement policy that considers both disk-existence probability and cache-existence probability of a data using data popularity.