Browsing College of Engineering and Informatics by Author "Howley, Enda"
Now showing items 1-6 of 6
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Applying reinforcement learning towards automating resource allocation and application scalability in the cloud
Duggan, Jim; Howley, Enda; Barrett, Enda (Wiley, 2012-05-30)Public Infrastructure as a Service (IaaS) clouds such as Amazon, GoGrid and Rackspace deliver computational resources by means of virtualisation technologies. These technologies allow multiple independent virtual machines ... -
Co-evolutionary analysis: a policy exploration method for system dynamics models
Hongliang, Liu; Howley, Enda; Duggan, Jim (System Dynamics Society / Wiley, 2012-10-22)In system dynamics (SD), complex nonlinear systems can generate a wide range of possible behaviours that frequently require search and optimization algorithms in order to explore optimal policies. Within the SD literature, ... -
The influence of random interactions and decision heuristics on norm evolution in social networks
Mungovan, Declan; Howley, Enda; Duggan, Jim (Springer, 2011-05)In this paper we explore the effect that random social interactions have on the emergence and evolution of social norms in a simulated population of agents. In our model agents observe the behaviour of others and update ... -
A learning architecture for scheduling workflow applications in the cloud
Barrett, Enda; Howley, Enda; Duggan, Jim (IEEE, 2011-09-15)The scheduling of workflow applications involves the mapping of individual workflow tasks to computational resources, based on a range of functional and non-functional quality of service requirements. Workflow applications ... -
Observations on the shortest independent loop set algorithm
Huang, Jinjing; Howley, Enda; Duggan, Jim (System Dynamics Society / Wiley, 2012-07-31)The shortest independent loop set (SILS) algorithm is a widely adopted loop selection method in eigenvalue elasticity analysis to identify dominant loops. However, we find that, in an individual-based model, the SILS cannot ... -
Particle swarm optimisation with gradually increasing directed neighbourhoods
Liu, Hongliang; Howley, Enda; Duggan, Jim (Association for Computing Machiner, 2011)Particle swarm optimisation (PSO) is an intelligent random search algorithm, and the key to success is to effectively balance between the exploration of the solution space in the early stages and the exploitation of the ...