Engineering emergence for cluster configuration

Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

On "fitting in": the effects of social context and gender on big 5 trait expression.

[This is a summary of an Oral Presentation] The study explored the expression of Big 5 personality traits in three different social contexts (with parents friends and work colleagues) to test the prediction that personality is socially variable due to the motivation to ‘fit in’. The questionnaire-based method produced results that support this hypothesis; all Big 5 traits were significantly variable across contexts with Conscientiousness the least variable and Extraversion possessiveness. The results indicated that females reported being more distressed than males and older respondents reported being less distressed then younger respondents. The findings from this study contribute to the literature on online infidelity in terms of understanding differences in the way it is perceived.