Virtual Infrastructure Planning for a Workflow with Multiple Overlapping Deadline Constraints in Cloud

Cloud providers offer various types of virtual infrastructures

(e.g. Virtual Machines, Dockers) to consumers in

a pay-as-you go manner. For an application represented by a

complex workflow, it is difficult for the consumer to decide what

type of infrastructure they need to meet the Quality-of-Service

(QoS) requirements and achieve objectives like monetary cost

optimisation. We call such problem as the virtual infrastructure

planning problem in cloud. Most existing studies focus on only

one single deadline-constrained workflow planning. The single

deadline constraint usually refers to a global deadline since

the start execution of a workflow to its finish. However, such

simple model cannot allow a time critical application to specify

internal deadlines inside the workflow. To allow such flexibility

for consumers, we propose a multi-deadline model and consider

the virtual infrastructure planning problem for workflow with

multi-deadline constraints. To solve the problem efficiently, we

propose a Multiple-Deadline overlapping-based Infrastructure

Planning (MDIP) algorithm. In MDIP, we define the criticality

of tasks by analysing the deadline coverages. Then we rank the

tasks in the workflow by their criticality and assign them with

VM type of better performance. To evaluate the effectiveness

of our algorithm, we compare it with a meta-heuristic solution

(Genetic Algorithm-based) and a hybrid solution combining

critical path and genetic algorithm. Simulated experiments show

our approach can achieve better results than existing solutions

and more efficient than GA-based solution.