Incorporating load factor into the scheduling of soft real-time transactions for main memory databases

Many real-time applications have very tight time constraints which couldn't be met by disk resident databases. For those applications, main memory dat abase where entire database is stored in main memory is the proper choice. It has been shown that coarse-granule locking is better than fins-granule l ocking for main-memory databases. Coarse-granule locking makes it easy to e xtract data access patterns correctly from canned transactions of main memo ry real-time database systems. In this paper, we propose two real-time tran saction scheduling algorithms - CCA-ALF (Cost Conscious Approach with Avera ge Load Factor) and EDF-CR-ALF (Earliest Deadline First-Conditional Restart with ALF)- which use both static (e.g., deadline) and dynamic information (e.g., system load) for main memory databases by utilizing data access patt erns of transactions. We compare the performance of those algorithms with C CA and EDF-HP which do not use system load information at all. Our simulati ons on main memory databases indicate that: i) CCA-ALF is better than EDF-H P, CCA, and EDF-CR-ALF in terms of miss percent and mean lateness, and ii) CCA-ALF adapts well to the changes in the system load. (C) 2000 Published b y Elsevier Science Ltd.