Sensitive Distance Estimates Technique Analysis for Continuously K-Nearest Neighbors Query in Multi-Stream Processing

In many real-world applications, data streams are usually collected in a decentralized manner such like sensor network, ubiquities sensor network, internet traffic analysis, and so on. In particularly, requirements for continuous, fast, high-volumes, adaptability, costly streaming data, an approximated analysis is needful for fast response to users on forward predicates. Distance estimate for both of “continuously” queries and streams is still a more challenge area because of a smaller or larger threshold selected is very easily to lead to a wrong result for continuously k-nearest neighbor queries. Therefore, we proposed a required filtering method to help to choose a well threshold of distance estimate in order to control error rates of approximated answers.