Video Search Using Map Reduce Framework in an Education Cloud

Abstract

Video search systems have become popular in recent years. The system prompts users to give a string query and retrieves the matched video quickly from the user for playing. There is still no established search method available for scalable fast search in large distributed video databases. In video search systems, when the number of online users reaches a certain scale, it will greatly reduce the response from the server. There are many video resources stored in distributed databases which should be accessible to all the users. If many users access the videos at the same time, it may lead to increase in load on the server. To solve this problem, cloud computing technology is used. A distributed database is used for storing and indexing videos. This system uses Map Reduce paradigm for retrieving the videos in distributed fashion. Map Reduce approach allows splitting the tasks into sub-tasks and then assigning it to various virtual nodes present in the cloud, which are then processed and consolidated to give the final output. Thus, the processing speed is increased while the processing time is greatly reduced.KeywordsCloud computingDistributed databaseMap reduce