Much is understood about success factors, issues, and lessons learned in implementing e-learning in the context of higher education. A consensus is emerging that suggests that each institution is unique and hence requires a highly customized e-learning strategy. This paper presents a strategy formulation process that takes a community building view towards strategy formulation. In specific, the process uses the future search conference and the Cademenos model of growth of e-learning within higher education. An application and evaluation of the strategy formulation process at an American University is presented

The development of efficient algorithms to process the different forms of transitive-closure (TC) queries within the context of large database systems has recently attracted a large volume of research efforts. In this paper, we present two new algorithms suitable for processing one of these forms, the so called strong partially instantiated transitive closure, in which one of the query's arguments is instantiated to a set of constants and the processing of which yields a set of tuples that draw their values from both of the query's instantiated and uninstantiated arguments. These algorithms avoids the redundant computations and high storage cost found in a number of similar algorithms. Using simulation, this paper compares the performance of the new algorithms with those found in literature and shows clearly the superiority of the new algorithms.

The development of efficient algorithms to process the different forms of transitive-closure queries within the context of large database systems has attracted a large volume of research efforts. The authors present a new algorithm that is suitable for processing one of these forms, the strong partially instantiated query, in which one of the query's arguments is instantiated to a set of constants. The processing of this algorithm yields a set of tuples that draw their values from both of the query's instantiated and uninstantiated arguments. This algorithm avoids the redundant computations and the high storage costs found in a number of similar algorithms.>

An algorithm suitable for the full transitive closure problem, which is used to solve uninstantiated recursive queries in deductive databases, is presented. In this algorithm there are two phases. In the first phase a general graph is condensed into an acyclic graph and at the same time a special sparse matrix is formed from the acyclic graph. The second phase is the main one, where all of the page I/O operations are minimized. Simulation is used to study the performance of this algorithm and compare it with that of previous algorithms.>

A method is proposed for identifying relevant integrity constraints (ICs) for queries involving joins/unions of base relations and defined relations by use of graphs. The method does not rely on heavy preprocessing or redundancy. To effectively select those ICs that are relevant to a given query, the relationship between the predicates in the query is identified using an AND/OR tree where an AND mode represents a join operation and an OR node represents a union operation. Ways of collecting ICs are described that are not directly related to the query but can be useful in query optimization.>

The performances of several algorithms suitable for processing an important class of recursive queries called the instantiated transitive closure (TC) queries are studied and compared. These algorithms are the wavefront, delta -wavefront, and a generic algorithm called super-TC. During the evaluation of a TC query, the first two algorithms may read a given disk page more than once, whereas super-TC reads the disk page at most once. A comprehensive performance evaluation of these three algorithms using rigorous analytical and simulation models is presented. The study reveals that the relative performance of the algorithms is a strong function of the parameters which characterize the processed TC query and the relation referenced by that query. The superiority of one of the super-TC variants over all of the other presented algorithms is shown.>

The author presents and evaluates, using rigorous analytical models, a number of parallel algorithms suitable for processing an important class of recursive queries, the instantiated transitive closure (TC) queries. These algorithms are variants of the sequential delta -wavefront algorithm, designed to run on a shared-nothing (message-passing) type of multiprocessor system. The results obtained indicate that the relative performance of these algorithms is a strong function of not only the parameters which characterize the database and the processed query. Two parallel algorithms have been identified to be the best performing ones, one for systems with slow interconnection networks and the other for systems with fast networks. It is also found that allocating too many nodes to a query which does not need them results in a substantial loss of potential speedup in the processing of the query. >

Several strategies for processing queries in data-intensive logic bases (deductive databases) have been recently proposed. These strategies can be grouped into the one-tuple-at-a-time and the set-of-tuples-at-a-time classes. A strategy of the first class searches the logic base for one solution to the processed query at any point in time and uses backtracking to find alternative solutions. A strategy of the second class searches the logic base to find all of the solutions to the query simultaneously, thus eliminating the need for backtracking. The modification of Prolog's tuple-at-a-time processing strategy into a set-at-a-time one is investigated. The set-modified version of Prolog has been implemented, and the resulting interpreter has been benchmarked against a classical Prolog one, showing a dramatic improvement in performance.>

The authors develop and present a large set of parallel algorithms for implementing the join operation on a shared-memory multiprocessor database machine. The development of these algorithms follows a structured approach. The major steps involved in the processing of the join operation by the machine are first identified. Then, alternative join algorithms are constructed by concatenating the different ways of performing these steps. A study of the performance of the proposed algorithms is presented. This study shows, among other things, that for a given hardware configuration there is not just one overall best performing join algorithm, but rather different algorithms score the best performance, depending on the characteristics of the data participating in the join operation.>

This paper presents an architectural design for a back-end database machine (DBM) suitable for supporting multiple-user, on-line, very large relational database systems (systems with capacities larger than 1010 bytes). This machine is called the Michigan Relational Database Machine (MIRDM). In designing such a machine a structured approach is followed. First, the DBM's proposed so far are reviewed using a novel classification scheme. Second, this review, the very large relational database system requirements, and the restrictions imposed by the current and near-future state of technology are used to formulate a set of design guidelines. Consequently, an architecture for a cost-effective DBM that meets this set of guidelines is synthesized. Some of the algorithms developed for implementing the primitives of the new machine are also presented. Finally, we highlight some of the important differences between the new DBM and some of the previously proposed ones.