Flash memory is widely used as the secondary storage in lightweight computing devices due to its outstanding advantages over magnetic disks. Flash memory has many access characteristics different from those of magnetic disks, and how to take advantage of them is becoming an important research issue. There are two existing approaches to storing data into flash memory: page-based and log-based. The former has good performance for read operations, but poor performance for write operations. In contrast, the latter has good performance for write operations when updates are light, but poor performance for read operations. In this paper, we propose a new method of storing data, called page-differential logging, for flash-based storage systems that solves the drawbacks of the two methods. The primary characteristics of our method are: (1) writing only the difference (which we define as the page-differential) between the original page in flash memory and the up-to-date page in memory; (2) computing and writing the page-differential only once at the time the page needs to be reflected into flash memory. The former contrasts with existing page-based methods that write the whole page including both changed and unchanged parts of data or from log-based ones that keep track of the history of all the changes in a page. Our method allows existing disk-based DBMSs to be reused as flash-based DBMSs just by modifying the flash memory driver, i.e., it is DBMS-independent. Experimental results show that the proposed method improves the I O performance by 1.2 6.1 times over existing methods for the TPC-C data of approximately 1 Gbytes.
In page-based methods, there are two update schemes , @cite_2 ,--- ,in-place update and out-place update ,--- ,depending on whether or not the logical page is always written into the same physical page. When a logical page needs to be reflected into flash memory, the in-place update overwrites it into the specific physical page that was read , @cite_2 , but the out-place update writes it into a new physical page , @cite_18 @cite_15 .
@cite_18 @cite_15 @cite_2
2015692847 1551453953 2029617471 190622319
When updating a knowledge base, several problems may arise. One of the most important problems is that of integrity constraints satisfaction. The classic approach to this problem has been to develop methods for checking whether a given update violates an integrity constraint. An alternative approach consists of trying to repair integrity constraints violations by performing additional updates that maintain knowledge base consistency. Another major problem in knowledge base updating is that of view updating, which determines how an update request should be translated into an update of the underlying base facts. We propose a new method for updating knowledge bases while maintaining their consistency. Our method can be used for both integrity constraints maintenance and view updating. It can also be combined with any integrity checking method for view updating and integrity checking. The kind of updates handled by our method are: updates of base facts, view updates, updates of deductive rules, and updates of integrity constraints. Our method is based on events and transition rules, which explicitly define the insertions and deletions induced by a knowledge base update. Using these rules, an extension of the SLDNF procedure allows us to obtain all possible minimal ways of updating a knowledge base without violating any integrity constraint. This paper introduces techniques for updating knowledge bases represented in extended logic programs. Three different types of updates, view updates, theory updates, and inconsistency removal, are considered. We formulate these updates through abduction, and provide methods for computing them with update programs. An update program is an extended logic program which specifies changes on abductive hypotheses, then updates are computed by the U-minimal answer sets of an update program. The proposed technique provides a uniform framework for these different types of updates, and each update is computed using existing procedures of logic programming. The Katsuno and Mendelzon theory of belief update has been proposed as a reasonable model for revising beliefs about a changing world. However, the semantics of update relies on information which is not readily available. We describe an alternative semantical view of update in which observations are incorporated into a belief set by: a) explaining the observation in terms of a set of plausible events that might have caused that observation; and b) predicting further consequences of those explanations. We also allow the possibility of conditional explanations. We show that this picture naturally induces an update operator under certain assumptions. However, we argue that these assumptions are not always reasonable, and they restrict our ability to integrate update with other forms of revision when reasoning about action. Abstract We propose an extension of the SLDNF proof procedure for checking integrity constraints in deductive databases. To achieve the effect of the simplification methods investigated by Nicolas [1982], Lloyd, Sonenberg, and Topor [1986], and Decker [1986], we use clauses corresponding to the updates as top clauses for the search space. This builds in the assumption that the database satisfied its integrity constraints prior to the transaction, and that, therefore, any violation of the constraints in the updated database must involve at least one of the updates in the transaction. Different simplification methods can be simulated by different strategies for literal selection and search. The SLDNF proof procedure needs to be extended to use as top clause any arbitrary deductive rule, denial, or negated fact, to incorporate inference rules for reasoning about implicit deletions resulting from other deletions and additions, and to allow an extended resolution step for reasoning forward from negated facts.