Although the shortcut mechanism can be used to reduce the update and query costs, the query cost for the shortcuts mechanism is not better than that of DAT.
The multi-sink concept reduces the query cost and also reduces the communication cost.
Minimizing the query cost among multi-hosts is important to data processing for big data applications.
The query cost reduction is also considered in the DAT algorithm.
The DAT can be updated using the Query Cost Reduction (QCR) method.
The authors proposed a "cache-and-reuse" technique for query cost estimation.
Our protocol allows multiple users to combine their queries to reduce the querying cost while protecting their privacy.
The release of fixed moving velocity makes the query process slowly due to the significant repetitive query cost.
Of these update, the ability to better manage query cost will likely have the most immediate impact.
We prove the correctness of Scoop by theoretical analysis, and verify the efficiency of Scoop in terms of query cost and query time via extensive simulation.
