Safe Locking Policies for Dynamic Databases

AbstractYannakakis showed that a locking policy is not safe if and only if it allows a canonical nonserializable schedule of transactions in which all transactions except one are executed serially (Yannakakis, 1982). In the present paper, we study the generalization of this result to a dynamic database, that is, a database that may undergo insertions and deletions of entities. We illustrate the utility of this generalization by applying it to obtain correctness proofs of three locking policies that handle dynamic databases

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

Implementing OKBC Knowledge Model Using Object Relational Capabilities of Oracle 8

PERK is a storage system that loads knowledge bases (KB) from the Oracle DBMS. Its current limitation is the inability to do client-side memory flushing out. In this paper, we present a new architecture, named PERK-II, which utilizes the object relational capabilities provided by Oracle 8. It can do the client-side buffer management automatically, use object view and complex object retrieval (COR) to reduce network traffic, and push a lot of database functionality from PERK to the Oracle DBMS. So, the system is greatly simplified without sacrificing efficiency. Our basic design is based on open knowledge base connectivity (OKBC), which is an application programming interface (API) for accessing knowledge representation systems (KRS). By far, we have implemented the read-only OKBC operations using the Oracle Call Interface (OCI). Our test results show that the use of the Oracle client-side object cache does not substantially degrade the performance of the system as compared to using a "home grown" in-memory client cache

Safe Locking Policies for Dynamic Databases

It was shown by Yannakakis that a locking policy is not safe if and only if there exists a canonical non-serializable schedule of transactions running according to the rules of the policy in which all the transactions except one are executed serially [Yan82]. In the present paper, we study the generalization of this result to a dynamic database, that is, a database that may undergo insertions and deletions of entities. We illustrate the utility of this generalization by applying it to obtain correctness proofs of three locking policies that handle dynamic databases. Keywords: Concurrency Control, Correctness Issues Safe Locking Policies for Dynamic Databases 1 1 Introduction A locking policy is called safe if any concurrent execution of a set of transactions while locked according to that policy is guaranteed to be correct. Yannakakis showed that a locking policy is not safe if and only if there exists a canonical non-serializable schedule in which all transactions except one ..

A Formal Analysis of Solution Caching

Many inference management systems store and maintain the conclusions found during a derivation process in a form that allows these conclusions to be used during subsequent derivations. As this approach, called "solution caching", allows the system to avoid repeating these derivations, it can reduce the system's overall cost for answering queries. Unfortunately, as there is a cost for storing these conclusions, it is not always desirable to cache every solution found --- this depends on whether the savings achieved by performing fewer inference steps for these future queries exceeds the storage overhead incurred. This paper formally characterizes this tradeoff and presents an efficient algorithm, FOCL, that produces an optimal caching strategy: i.e., given an inference graph of a knowledge base, anticipated frequencies of queries and updates of each node in this graph, and various implementation-dependent cost parameters, FOCL determines which of these nodes should cache their soluti..