Green Solution for Cloud Computing with Load Balancing and Power Consumption Management

Cloud computing a relatively recent term builds on decades of research in virtualization, distributed computing, utility computing, and networking, web and s/w services. The consequence of network based cloud computing model which is rapidly increasing in delivering computing as a utility to users worldwide is that cloud data centers have high deployment and operational costs, as well as significant carbon footprints for the environment. So attention should be paid to the need of managing energy consumption across the entire Information and Communication Technology (ICT) sector because of its large amount of CO2 emission. Despite ecological issues, the interest of the low power research has critical economical needs. We need to develop Green Cloud Computing (GCC) solutions that reduces these deployment and operational costs and thus save energy, hence, reduces adverse environmental impacts. In this paper, we aim to implement practically a Green Scheduling Algorithm integrating a neural network predictor for optimizing server power consumption in Cloud computing environments by sending unused servers in sleeping mode. For this we have planned to use Bee Colony Optimization, Ant Colony Optimization where needed. Keywordsgreen cloud, virtual machine, bee colony optimization, ant colony optimization etc.