Resource Allocation for Multiple Concurrent In-Network Stream-Processing Applications

This paper investigates the operator mapping problem for in-network stream-processing applications. In-network stream-processing amounts to applying one or more trees of operators in steady-state, to multiple data objects that are continuously updated at different locations in the network. The goal is to compute some final data at some desired rate. Different operator trees may share common subtrees. Therefore, it may be possible to reuse some intermediate results in different application trees. The first contribution of this work is to provide complexity results for different instances of the basic problem, as well as integer linear program formulations of various problem instances. The second second contribution is the design of several polynomial-time heuristics. One of the primary objectives of these heuristics is to reuse intermediate results shared by multiple applications. Our quantitative comparisons of these heuristics in simulation demonstrates the importance of choosing appropriate processors for operator mapping. It also allow us to identify a heuristic that achieves good results in practice

A grid-based infrastructure for distributed retrieval

In large-scale distributed retrieval, challenges of latency, heterogeneity, and dynamicity emphasise the importance of infrastructural support in reducing the development costs of state-of-the-art solutions. We present a service-based infrastructure for distributed retrieval which blends middleware facilities and a design framework to ‘lift’ the resource sharing approach and the computational services of a European Grid platform into the domain of e-Science applications. In this paper, we give an overview of the DILIGENT Search Framework and illustrate its exploitation in the field of Earth Science

Conversational querying

The traditional interaction mechanism with a database system is through the use of a query language, the most widely used one being SQL. However, when one is facing a situation where he or she has to make a minor modification to a previously issued SQL query, either the whole query has to be written from scratch, or one has to invoke an editor to edit the query. This, however, is not the way we converse with each other as humans. During the course of a conversation, the preceding interaction is used as a context within which many incomplete and/or incremental phrases are uniquely and unambiguously interpreted, sparing the need to repeat the same things again and again. In this paper, we present an effective mechanism that allows a user to interact with a database system in a way similar to the way humans converse. More specifically, incomplete SQL queries are accepted as input which are then matched to identified parts of previously issued queries. Disambiguation is achieved by using various types of semantic information. The overall method works independently of the domain under which it is used (i.e., independently of the database schema). Several algorithms that are variations of the same basic mechanism are proposed. They are mutually compared with respect to efficiency and accuracy through a limited set of experiments on human subjects. The results have been encouraging, especially when semantic knowledge from the schema is exploited, laying a potential foundation for conversational querying in databases. © 2004 Elsevier Ltd. All rights reserved