Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Cloud computing represents one of the most important research directions for modern computing systems. Existing research efforts on Cloud computing re all focused on designing advanced storage and query techniques for  static data . None of them consider the problem that data in a Cloud may appear as continuous and rapid  data streams . To address this problem, in this paper  propose a new  LCN-Index  framework to handle continuous data stream queries in the Cloud. LCN-Index uses the  Map-Reduce  computing paradigm to process all the queries. In the Mapping stage, it divides all the queries into a batch of predicate sets which are then deployed onto mapping nodes using  interval predicate index . In the reducing stage, it merges results from the mapping nodes using  multi attribute hash index . In so doing, a data stream can be efficiently evaluated by traversing through the LCN-Index framework. Experiments demonstrate the utility of the proposed method.
['Jun Li', 'Peng Zhang', 'Jianlong Tan', 'Ping Liu', 'Li Guo']
I am writing a research paper on a idea Continuous data stream query in the cloud
[{"from": "human", "value": "I am writing a research paper on a idea Continuous data stream query in the cloud"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Cloud computing represents one of the most important research directions for modern computing systems. Existing research efforts on Cloud computing re all focused on designing advanced storage and query techniques for  static data . None of them consider the problem that data in a Cloud may appear as continuous and rapid  data streams . To address this problem, in this paper  propose a new  LCN-Index  framework to handle continuous data stream queries in the Cloud. LCN-Index uses the  Map-Reduce  computing paradigm to process all the queries. In the Mapping stage, it divides all the queries into a batch of predicate sets which are then deployed onto mapping nodes using  interval predicate index . In the reducing stage, it merges results from the mapping nodes using  multi attribute hash index . In so doing, a data stream can be efficiently evaluated by traversing through the LCN-Index framework. Experiments demonstrate the utility of the proposed method."}]