38 citations · 52 across the 9 of their papers we have counts for
6 papers · 1 filter
vPALs: Towards Verified Performance-aware Learning System For Resource Management
Guoliang He, Gingfung Yeung, Sheriffo Ceesay +1
Accurately predicting task performance at runtime in a cluster is advantageous for a resource management system to determine whether a task should be migrated due to performance de…
Are Clouds Ready to Accelerate Ad hoc Financial Simulations?
Blesson Varghese, Adam Barker
Applications employed in the financial services industry to capture and estimate a variety of risk metrics are underpinned by stochastic simulations which are data, memory and comp…
Optimal Deployment of Geographically Distributed Workflow Engines on the Cloud
Long Thai, Adam Barker, Blesson Varghese +2
When orchestrating Web service workflows, the geographical placement of the orchestration engine(s) can greatly affect workflow performance. Data may have to be transferred across…
Executing Bag of Distributed Tasks on the Cloud: Investigating the Trade-offs Between Performance and Cost
Long Thai, Blesson Varghese, Adam Barker
Bag of Distributed Tasks (BoDT) can benefit from decentralised execution on the Cloud. However, there is a trade-off between the performance that can be achieved by employing a lar…
Uncovering the Perfect Place: Optimising Workflow Engine Deployment in the Cloud
Michael Luckeneder, Adam Barker
When orchestrating highly distributed and data-intensive Web service workflows the geographical placement of the orchestration engine can greatly affect the overall performance of…
Academic Cloud Computing Research: Five Pitfalls and Five Opportunities
Adam Barker, Blesson Varghese, Jonathan Stuart Ward +1
This discussion paper argues that there are five fundamental pitfalls, which can restrict academics from conducting cloud computing research at the infrastructure level, which is c…