Multi-Swarm Co-Evolution Based Hybrid Intelligent Optimization for Bi-Objective Multi-Workflow Scheduling in the Cloud

Keyphrases

• Bi-objective 100%
• Hybrid Intelligent Optimization 100%
• Multi-swarm 100%
• Multi-workflow Scheduling 100%
• Cloud Service Provider 25%
• Cloud Computing 25%
• Scientific Applications 25%
• Local Optimum 25%
• Search Performance 25%
• Scheduling Algorithm 25%
• Multiple Applications 25%
• Genetic Algorithm 25%
• Multiple Users 25%
• Evolution Mechanism 25%
• Non-dominated Solutions 25%
• Makespan 25%
• Update Mechanism 25%
• QoS Requirements 25%
• Metropolis 25%
• Deadline Constraint 25%
• Global Convergence 25%
• Simulated Annealing 25%
• Global Search 25%
• Particle Swarm Optimizer 25%
• Workflow Scheduling 25%
• Convergence Performance 25%
• Cooperative Method 25%
• Elite Solutions 25%
• Hybrid Intelligent Optimization Algorithm 25%
• Multiple Workflows Scheduling 25%
• Demand Scheduling 25%
• Guiding Information 25%
• Acceptance Rules 25%
• QoS Demand 25%

Computer Science

• Quality of Service 100%
• Cloud Computing 50%
• Optimization Algorithm 50%
• Experimental Result 50%
• Cloud Service Provider 50%
• Scientific Application 50%
• Genetic Algorithm 50%
• Multiple Application 50%
• Scheduling Algorithm 50%
• Simulated Annealing 50%
• particle swarm optimizer 50%
• Convergence Performance 50%
• Total Makespan 50%