ADAPTIVE PREFETCHING AND STORAGE REORGANIZATION IN A LOG-STRUCTURED STORAGE-SYSTEM

We present a storage management system that has the ability to adapt t o the data access characteristics of the application that uses it base d on collection and analysis of runtime statistics. This feature is es pecially useful in the storage management layer of database systems, w here applications exhibit relatively predictable access patterns. Adap tive reorganization is performed by the storage management system in a manner that optimizes the access patterns of the system for which it is used, We enhance the log-structured storage system that naturally c aters for write optimization, with the addition of a statistics collec tion mechanism to determine data access patterns of applications. The storage system can serve as a testbed for a variety of statistics anal ysis and clustering mechanisms. Higher level application-specific data clustering mechanisms can be used to override the storage system's lo w-level clustering mechanisms. In addition, the analysis techniques an d reorganization scheme can be used in other storage systems. Performa nce results from our prototype show potential response time speedups o f up to 83 percent over the basic log-structured file system in the be st case, using a combination of storage reorganization and prefetching .