Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Traditionally, the "best effort, cost free" model of Supercomputers/Grids does not consider pricing. Clouds have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on "pay-as-you-go" model. Large scale many-task workflow (MTW) may be suited for execution on Clouds due to its scale-* requirement (scale up, scale out, and scale down). In the context of scheduling, MTW execution cost must be considered based on users' budget constraints. ,  address the problem of scheduling MTW on Clouds and present a budget-conscious scheduling algorithm, referred to as Scale Star (or Scale-*). Scale Star assigns the selected task to a virtual machine with higher comparative advantage which effectively balances the execution time-and-monetary cost goals. In addition, according to the actual charging model, an adjustment policy, refer to as {\em DeSlack}, is proposed to remove part of slack without adversely affecting the overall make span and the total monetary cost.  evaluate Scale Star with an extensive set of simulations and compare with the most popular HEFT-based LOSS3 algorithm and demonstrate the superior performance of Scale Star.
['Lingfang Zeng', 'Bharadwaj Veeravalli', 'Xiaorong Li']
I am writing a research paper on a idea ScaleStar: Budget Conscious Scheduling Precedence-Constrained Many-task Workflow Applications in Cloud
[{"from": "human", "value": "I am writing a research paper on a idea ScaleStar: Budget Conscious Scheduling Precedence-Constrained Many-task Workflow Applications in Cloud"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Traditionally, the \"best effort, cost free\" model of Supercomputers/Grids does not consider pricing. Clouds have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on \"pay-as-you-go\" model. Large scale many-task workflow (MTW) may be suited for execution on Clouds due to its scale-* requirement (scale up, scale out, and scale down). In the context of scheduling, MTW execution cost must be considered based on users' budget constraints. ,  address the problem of scheduling MTW on Clouds and present a budget-conscious scheduling algorithm, referred to as Scale Star (or Scale-*). Scale Star assigns the selected task to a virtual machine with higher comparative advantage which effectively balances the execution time-and-monetary cost goals. In addition, according to the actual charging model, an adjustment policy, refer to as {\\em DeSlack}, is proposed to remove part of slack without adversely affecting the overall make span and the total monetary cost.  evaluate Scale Star with an extensive set of simulations and compare with the most popular HEFT-based LOSS3 algorithm and demonstrate the superior performance of Scale Star."}]