Error in the UNITY substitution rule for subscripted operators

UNITY, introduced by Chandy and Misra [ChM88], is a programming logic intended to reason about temporal properties of distributed programs. Despite the fact that UNITY does not have the full power of, for example, linear temporal logic, it enjoys popularity due to its simplicity.There was however a serious problem with the Substitution Rule. The logic is incomplete without the rule, and with the rule it is inconsistent.     

Prolog/Rex-a way to extend Prolog for better knowledgerepresentation

Prolog/Rex represents a powerful amalgamation of the latest techniques for knowledge representation and processing, rich in semantic features that ease the difficult task of encoding heterogeneous knowledge of real-world applications. The Prolog/Rex concept mechanism lets a user represent domain entities in terms of their structural and behavioral properties, including multiple inheritance, arbitrary user-defined relations among entities, annotated values (demons), incomplete knowledge, etc. A flexible rule language helps the knowledge engineer capture human expertise and provide flexible control of the reasoning process. Additional Prolog/Rex strength that cannot be found in any other hybrid language made on top of Prolog is language level support for keeping many potentially contradictory solutions to a problem, allowing possible solutions and their implications to be automatically generated and completely explored before they are committed. The same mechanism is used to model time-states, which are useful in planning and scheduling applications of Prolog/Rex     

Function materialization in object bases: design, realization, andevaluation

View materialization is a well-known optimization technique of relational database systems. We present a similar, yet more powerful, optimization concept for object-oriented data models: function materialization. Exploiting the object-oriented paradigm-namely, classification, object identity, and encapsulation-facilitates a rather easy incorporation of function materialization into (existing) object-oriented systems. Only those types (classes) whose instances are involved in some materialization are appropriately modified and recompiled, thus leaving the remainder of the object system invariant. Furthermore, the exploitation of encapsulation (information hiding) and object identity provides for additional performance tuning measures that drastically decrease the invalidation and rematerialization overhead incurred by updates in the object base. First, it allows us to cleanly separate the object instances that are irrelevant for the materialized functions from those that are involved in the materialization of some function result, and this to penalize only those involved objects upon update. Second, the principle of information hiding facilitates fine-grained control over the invalidation of precomputed results. Based on specifications given by the data type implementor, the system can exploit operational semantics to better distinguish between update operations that invalidate a materialized result and those that require no rematerialization. The paper concludes with a quantitative analysis of function materialization based on two sample performance benchmarks obtained from our experimental object base system GOM     

Site and query scheduling policies in multicomputer databasesystems

We study run-time issues, such as site allocation and query scheduling policies, in executing read-only queries in a hierarchical, distributed memory, multicomputer system. The particular architecture considered is based on the hypercube interconnection. The data are stored in a base cube, which is controlled by a control cube and host node hierarchy. Input query trees are transformed into operation sequence trees, and the operation sequences become the units of scheduling. These sequences are scheduled dynamically at run-time. Algorithms for dynamic site allocation are provided. Several query scheduling policies that support interquery concurrency are also studied. Average query completion times and initiation delays are obtained for the various policies using simulations     

RAPS: a rule-based language for specifying resource allocation andtime-tabling problems

A general language for specifying resource allocation and time-tabling problems is presented. The language is based on an expert system paradigm that was developed previously by the authors and that enables the solution of resource allocation problems by using experts' knowledge and heuristics. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thus provides a convenient knowledge acquisition tool. The language syntax is powerful and allows the specification of rules and constraints that are very difficult to formulate with traditional approaches, and it also supports the specification of various control and backtracking strategies. We constructed a generalized inference engine that runs compiled resource allocation problem specification language (RAPS) programs and provides all necessary control structures. This engine acts as an expert system shell and is called expert system for resource allocation (ESRA). The performance of RAPS combined with ESRA is demonstrated by analyzing its solution of a typical resource allocation problem     

Partial indexing for nonuniform data distributions in relationalDBMS's

It is well known that the effectiveness of relational database systems is greatly dependent on the efficiency of the data access strategies. For this reason, much work has been devoted to the development of new access techniques, supported by adequate access structures such as the B⁺trees. The effectiveness of the B ⁺tree also depends on the data distribution characteristics; in particular, poor performance results when the data show strong key value distribution unbalancing. The aim of this paper is to present the partial index: a new access structure that is useful in such cases of unbalancing, as an alternative to the B⁺tree unclustered indexes. The access structures are built in the physical design phase, and at execution (or compilation) time, the optimizer chooses the most efficient access path. Thus, integration of the partial indexing technique in the design and in the optimization process are also described     

Performance evaluation of rule grouping on a real-time expertsystem architecture

Uses a Markov process to model a real-time expert system architecture characterized by message passing and event-driven scheduling. The model is applied to the performance evaluation of rule grouping for real-time expert systems running on this architecture. An optimizing algorithm based on Kernighan-Lin heuristic graph partitioning for the real-time architecture is developed and a demonstration system based on the model and algorithm has been developed and tested on a portion of the advanced GPS receiver (AGR) and manned manoeuvring unit (MMU) knowledge bases     

Sort vs. hash revisited

Efficient algorithms for processing large volumes of data are very important both for relational and new object-oriented database systems. Many query-processing operations can be implemented using sort- or hash-based algorithms, e.g. intersections, joins, and duplicate elimination. In the early relational database systems, only sort-based algorithms were employed. In the last decade, hash-based algorithms have gained acceptance and popularity, and are often considered generally superior to sort-based algorithms such as merge-join. In this article, we compare the concepts behind sort- and hash-based query-processing algorithms and conclude that (1) many dualities exist between the two types of algorithms, (2) their costs differ mostly by percentages rather than by factors, (3) several special cases exist that favor one or the other choice, and (4) there is a strong reason why both hash- and sort-based algorithms should be available in a query-processing system. Our conclusions are supported by experiments performed using the Volcano query execution engine     

Evaluation of a parallel branch-and-bound algorithm on a class ofmultiprocessors

We propose and evaluate a parallel “decomposite best-first” search branch-and-bound algorithm (dbs) for MIN-based multiprocessor systems. We start with a new probabilistic model to estimate the number of evaluated nodes for a serial best-first search branch-and-bound algorithm. This analysis is used in predicting the parallel algorithm speed-up. The proposed algorithm initially decomposes a problem into N subproblems, where N is the number of processors available in a multiprocessor. Afterwards, each processor executes the serial best-first search to find a local feasible solution. Local solutions are broadcasted through the network to compute the final solution. A conflict-free mapping scheme, known as the step-by-step spread, is used for subproblem distribution on the MIN. A speedup expression for the parallel algorithm is then derived using the serial best-first search node evaluation model. Our analysis considers both computation and communication overheads for providing realistic speed-up. Communication modeling is also extended for the parallel global best-first search technique. All the analytical results are validated via simulation. For large systems, when communication overhead is taken into consideration, it is observed that the parallel decomposite best-first search algorithm provides better speed-up compared to other reported schemes