A web-based OLAP client typically runs inside a generic browser on a web-based, resource-constrained device. Currently, this client is responsible for only delivery of what is rendered by the OLAP server. A functional prototype of a client-centric OLAP system is built, which features a customized middleware on the server side and a web client incorporating a lightweight, in-memory OLAP data/query engine. We develop three interactive data visualization tools that run against the data engine on the client side. Our experimental results show that in comparison to the traditional server-centric model, our client-centric OLAP model is clearly superior and capable of delivering a higher level of user satisfaction. A novel technique is presented for in-client aggregation over a large set of data items represented in a scatter plot.

This paper considers the design, implementation, and performance of ADODA with emphasis on aggregate computation. ADODA is a MOLAP data engine for OLAP applications. As embedded software, it features a compact and portable design. A multi-tier structure is devised to store the aggregates and primary data in one single data structure, so that they are accessed in the same way, and they are indistinguishable in the interface to an application. A compression scheme based on a B-tree is described. A formal model for aggregate computation is proposed, within which an aggregation algorithm is introduced and proved to be correct. This algorithm is shown to be applicable to non-compressed and compressed cubes. Since the pre-computation is a bottom-up process, it can stop at any level in any dimension, which is a useful feature for controlling the cost of pre-computation. Performance experiments are described, which aim to demonstrate the feasibility of ADODA for a real life dataset. The aggregation algorithm is also run against synthetic data sets to show the performance trends with increasing sizes of the primary data set and/or the number of dimensions.

Multicast communication in a distributed system connected by a local area network can increase parallelism, and it can also provide a greater functionality than one-to-one communication. In the authors' multicast protocol, the sender directs a message to a named group of receivers, which can be specified by function without requiring the sender to know the specific members of the group. Each host's kernel in the network can respond to every group message sent, providing various levels of reliability. It was found that the overhead of providing dependable multicast over a single local area network was very small, mainly because the protocol operates at the kernel level rather than the user level. Several forms of this multicast communication, expressed as simple message-passing communication primitives, are described, and the effectiveness of the protocol is evaluated using an example of a distributed algorithm. Performance analyses and actual performance data for the protocol are presented.>

A model for distributed sorting on a local area network (LAN) is presented. This model, contrary to the conventional model, takes into account both local processing time and communication time. This model is intended to provide a framework within which the performances of various distributed sorting algorithms are analyzed and implemented on Ethernet-connected Sun workstations. The empirical results by and large agree with the predictions derivable from the model. They show that local processing, particularly sorting of local subfiles, dominates the whole process, as far as response time is concerned. All algorithms examined have similar asymptotic behavior for large files. For medium-sized files, the degree of communication parallelism has a great impact on algorithm performance.>

An underlying relational database model and the database query language SQL are assumed, and methods are presented for responding with appropriate answers to null value responses. This is done by using a knowledge base based on RM/T, an extended relational model. The advantages of this approach are described. To demonstrate the utility of the knowledge base model, a simple knowledge base is constructed. The algorithms that provide additional information when a null answer is returned are detailed.>

When natural language front-ends are introduced to database management systems, generation of quality responses have proven problematical in situations when null values arise. In our work, in which we assume the database query language is SQL, we present methods for responding with appropriate answers to null value responses. To do so we use a knowledge base based on RM/T, an extended relational model proposed by E. F. Codd. The advantages of this approach are described. To demonstrate the utility of the knowledge base, a simple knowledge base is constructed. A detailed algorithm is given to provide additional information when a null answer is returned.

We adapt several parallel sorting algorithms (block sorting algorithms) and distributed sorting algorithms for implementation on an Ethernet network with diskless Sun workstations. We argue that the performance of sorting algorithms on local area networks (LANs) should be analyzed in a manner that is different from the ways that parallel and distributed sorting algorithms are usually analyzed. Consequently, we propose an empirical approach which will provide more insight into the performance of the algorithms. We obtain data on communication time, local processing time, and response time (i.e. total running time) of each algorithm for various file sizes and different numbers of processors. Comparing the performance data with our theoretical analysis, we attempt to provide rationale for the behaviour of the algorithms and project the future behaviour of the algorithms as file size, number of processors, or interprocessor communication facilities change.