Database technology for embedded software systems

点击翻译按钮获取中文摘要

Commercial relational engines are a multi-billion dollar industry, and are testimony to the reductions in the cost of developing and maintaining information systems that derive from the use of the SQL language and the consequent deployment of these engines. The proposed research program is guided by the hypothesis that comparable reductions in the cost of developing and maintaining embedded software would also ensue from the use of the SQL language, which in turn requires a number of new or improved capabilities with the underlying technology.    First, there is a need for improved query optimization for cases involving much richer forms of both conceptual and internal database schema since query plans generated by query optimizers must be comparible in performance to low-level code written directly by expert programmers. This places much greater demands on the sophistication of various facets of query optimization, including physical data models and data encoding, view integration capabilities and conceptual data modeling.    Second, there are a number of properties of embedded systems that affect the indexing and encoding of data. For example, decisions on the selection of appropriate indexing in this setting can now be driven by threshold requirements dictating that a particular query must run in logarithmic or even constant time. Other consequences are the need for more general and reliable data integration capabilities, and on alternative local data encoding in main or flash memory.    And third, there is a need for alternative transaction models in which a database server can be much more client aware in terms of the dynamic aspects of client interactions with the server. This can enable, for example, the use of deadlock free locking protocols and a consequent decoupling of concurrency control from data recovery, an essential requirement for many embedded systems in which logging and general abort capabilities would otherwise lead to unacceptable runtime overhead.