The dynamics of knowledge is important for virtual organizations (VOs) knowledge management (KM) to improve the fast response capabilities and flexible problem solving capabilities of VOs in complex environments. This paper proposes a method of modeling knowledge dynamics in VOs, which is composed of three models: knowledge flow model, knowledge conversion model and knowledge sharing space mode...

In this paper we operationally define and measure tacit knowledge at the team level in the software development domain. Through a series of three empirical studies we developed and validated the Team Tacit Knowledge Measure (TTKM) for software developers. In the first study, initial scale items were developed using the repertory grid technique and content analysis. In Study 2, supplied repertor...

Basic Local Alignment Search Tool (BLAST) is a heavily used bioinformatics application that has gotten significant attention from the high performance computing community. The authors have taken BLAST execution a step further and enabled it to execute on grid resources. Adapting BLAST to execute on the grid brings up concerns regarding grid resource heterogeneity, which inevitably cause difficu...

Scheduling of job-requests constitutes one of the most important aspects of grid computing. We propose DGSASAP , a grid scheduler that aims at starting the execution of jobs the soonest possible. DGSASAP is fully decentralized and distributed, based on an inexpensive random peer-to-peer overlay. Currently proposed solutions in literature fail to scale due to their centralized nature or due to t...

The UK DTI funded Biomedical Research Informatics Delivered by Grid Enabled Services (BRIDGES) project developed a Grid infrastructure through which research into the genetic causes of hypertension could be supported by scientists within the large Wellcome Trust funded Cardiovascular Functional Genomics project. The BRIDGES project had a focus on developing a compute Grid and a data Grid infras...

Modern digital terrain models (DTM) are widely used in the exploration of water areas. The models are often based on bathymetric data from a multibeam echosounder. DTM creators should properly select model parameters, firstly the grid resolution. High grid resolution enables creating very accurate models, however, they require high computing power and the data gathered in the grid occupy much m...

In this paper we propose a distributed knowledge management framework for semantics and knowledge creation, population, and reuse on the grid. Its objective is to evolve the Grid toward the Semantic Grid with the ultimate purpose of facilitating problem solving in e-Science. The framework uses ontology as the conceptual backbone and adopts the service-oriented computing paradigm for information...

In this study a new Genetic Algorithm (GA) using Tabu · Local Search mechanism for large-scale computer systems is proposed. We call the GA that uses huge computing resources a Mega Process GA. The GA described in this paper is considered a Mega Process GA. Our proposed method has a GA-specific database that possesses information of space that has been already searched. At the same time, the pr...

Abstract. We consider point location in Delaunay triangulations with the aid of simple data structures. In particular, we analyze methods in which a simple data structure is used to first locate a point close to the query point. For points uniformly distributed on the unit square, we show that the expected point location complexities are Θ( √ n) for the Green-Sibson rectilinear search, Θ(n) for...

Computational grid is an aggregation of geographically distributed network of computing nodes specially designed for compute intensive applications. The diversity of computational grid helps in resource utilization in order to support execution of all types of jobs; fine grain as well as coarse grain. It is observed that, over the period of time in the course of job execution, grid becomes high...