Nature Inspired Algorithms in Cloud Computing: A Survey
نویسندگان
چکیده
منابع مشابه
Nature Inspired Algorithms for Load Balancing in Cloud Computing
Load balancing and Consolidation of Virtual Machines is a way which is effective to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate Virtual Machines from an overloaded host is an aspect of dynamic Virtual Machine consolidation that directly influences the utilization of resource and Quality of Service which the system i...
متن کاملNature Inspired Algorithms for Load Balancing in Cloud Computing
Load balancing and Consolidation of Virtual Machines is a way which is effective to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate Virtual Machines from an overloaded host is an aspect of dynamic Virtual Machine consolidation that directly influences the utilization of resource and Quality of Service which the system i...
متن کاملNature Inspired Algorithms for Load Balancing in Cloud Computing
Load balancing and Consolidation of Virtual Machines is a way which is effective to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate Virtual Machines from an overloaded host is an aspect of dynamic Virtual Machine consolidation that directly influences the utilization of resource and Quality of Service which the system i...
متن کاملNature Inspired Algorithms for Load Balancing in Cloud Computing
Load balancing and Consolidation of Virtual Machines is a way which is effective to improve the utilization of resources and energy efficiency in Cloud data centers. Determining when it is best to reallocate Virtual Machines from an overloaded host is an aspect of dynamic Virtual Machine consolidation that directly influences the utilization of resource and Quality of Service which the system i...
متن کاملNature-Inspired Optimization Algorithms
The performance of any algorithm will largely depend on the setting of its algorithmdependent parameters. The optimal setting should allow the algorithm to achieve the best performance for solving a range of optimization problems. However, such parameter tuning is itself a tough optimization problem. In this chapter, we present a framework for self-tuning algorithms so that an algorithm to be t...
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ژورنال
عنوان ژورنال: International Journal of Intelligent Information Systems
سال: 2016
ISSN: 2328-7675
DOI: 10.11648/j.ijiis.20160505.11