Dynamic semantic-based green bio-inspired approach for optimizing energy and cloud services qualities
Dynamic semantic-based green bio-inspired approach for optimizing energy and cloud services qualities
Abstract
Currently, everybody can access and leverage existing services on the Cloud from a wide variety of mobile devices at any time and from anywhere (at home, at work, in the car, etc). The massive use of new heterogeneous mobile devices and technologies for discovering and deploying cloud services has led a trade-off between costs and improved quality of services (eg, fast response time, low cost, improved security, the reduction of energy consumption, and considerable emissions of carbon). This trade-off has led most cloud service providers to call for new intelligent, faster, and energy-saving solutions. This paper aims to propose a new approach based on Semantic Web technologies and Ant Colony Optimization algorithm, which intends to reduce the energy consumption of a wide variety of cloud services. Our approach is generic and, therefore, offers to customers a flexible infrastructure where they can easily perform their preferences. The effectiveness and energy saving of our proposal have been validated and evaluated through multiple experiments on random and real-world data sets.
Currently, everybody can access and leverage existing services on the Cloud from a wide variety of mobile devices at any time and from anywhere (at home, at work, in the car, etc). The massive use of new heterogeneous mobile devices and technologies for discovering and deploying cloud services has led a trade-off between costs and improved quality of services (eg, fast response time, low cost, improved security, the reduction of energy consumption, and considerable emissions of carbon). This trade-off has led most cloud service providers to call for new intelligent, faster, and energy-saving solutions. This paper aims to propose a new approach based on Semantic Web technologies and Ant Colony Optimization algorithm, which intends to reduce the energy consumption of a wide variety of cloud services. Our approach is generic and, therefore, offers to customers a flexible infrastructure where they can easily perform their preferences. The effectiveness and energy saving of our proposal have been validated and evaluated through multiple experiments on random and real-world data sets.
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