In real-time database,it is desirable to execute transactions within their deadlines using fresh(temporally consistent)data which can reflect the continuously changing external environments,e.g.,current temperature or stock prices.Traditional databases can not support time constraints and data temporal consistency for disk I/Os.While in MMDBs(Main Memory Database),most of disk I/Os has been removed during the normal processing.Traditional MMDBs assume that the entire databases are stored in volatile main memory,while their backup copies are kept in an Archive Database(AD)residing on secondary storage.This approach can not work when the volatile main memory is not large enough,especially in embedded systems with limited main memory.The appealing alternative is just to guarantee that no disk I/Os block transaction when running it. So the load of the MMDB becomes more frequent.The load of the MMDB plays a critical role for the system and therefore turns into an extruding problem that needs to be deeply discussed.The scheme takes transaction priority and data characteristics such as temporality and access frequency into account for the data exchange.Most of the scheme is based on the result of static pre-analysis of transaction for ARTs-EDB,which distills the time information,data characteristics,and access processes of the transaction. The"super access process"makes a transaction started before its whole dataset placed in ARTs-EDB, reducing the probability of missing deadline.This new approach greatly improves the practicability of MMDBs to embedded real-time database. |