PROJECT TITLE :

Dynamic Resource Provisioning for Energy Efficient Cloud Radio Access Networks - 2017

ABSTRACT:

Energy saving is critical for the cloud radio access networks (C-RANs), that are composed by massive radio access units (RAUs) and energy-intensive computing units (CUs) that host varied virtual machines (VMs). We tend to attempt to reduce the energy consumption of C-RANs, by leveraging the RAU sleep scheduling and VM consolidation strategies. We tend to formulate the energy saving downside in C-RANs as a joint resource provisioning (JRP) downside of the RAUs and CUs. Since the active RAU selection is coupled with the VM consolidation, the JRP downside shares some similarities with a special bin-packing downside. In this downside, the amount of items and also the sizes of items are correlated and are both adjustable. No existing methodology will be used to resolve this drawback directly. Therefore, we have a tendency to propose an efficient low-complexity algorithm along with a context-aware strategy to dynamically select active RAUs and consolidate VMs to CUs. In this approach, we have a tendency to can significantly reduce the energy consumption of C-RANs, whereas don't incur an excessive amount of overhead because of VM migrations. Our proposed theme is sensible for a large-size network, and its effectiveness is demonstrated by the simulation results.