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The potential for applying the proposed DNA-based computation to database operations and query-solving simulation is theoretically favorable, given the operational time complexity of O (6xy − 10y + 8k + 21) bio-steps of the RDNA model, where x, y and k are the total number of levels, the number of relational tables and the number of binary value bits, respectively.
It can process unstructured data far faster than traditional database operations.
We show how to discover the regularities in processing of elementary and complex database operations in a chaos of hundreds of thousands apparently not related database operations.
Atomic database operations are modeled based on our framework and are used as building blocks to model more complex database operations.
Program analysis is also exploited to extract semantics to allow non-serializable interleavings of database operations.
Therefore, it has a negative impact on the execution latency of database operations.
In this work we show how to model relational database operations using UML.
This chapter introduces algorithmic techniques used in implementing spatial database operations.
This is certainly a problem for database operations with theorem-provers, and so has drawn much attention from computer scientists.
(i) Database centric architectures hide the heterogeneity of underlying networks by only allowing access to network information using database operations.
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