In this thesis, components and parameters based power models (PMs) are produced to measure the power consumption (PC) of cloud radio access network (CRAN) architecture. In components PM, the power figure of each component within C-RAN is evaluated. After, this model is parametrised such that the computation complexity of each component is converted to a straightforward, but accurate method, called parameterised PM. This model compares cooling and total PC of traditional LTE architecture with C-RAN. This comparison considered different parameters such as, utilised bandwidth, number of antenna, base band units (BBUs) and remote radio heads (RRHs). This model draws about 33% reduction in power. Next, this PC model is updated to serve and exhibit the cost of integrating software defined networks (SDNs) with C-RAN. Alongside, modelling the power cost of the control plane units in the core network (CN), such as serving gateway (SGW), packet gateway (PGW) and mobility management entity (MME). Although there is power cost, the proposed model shows the directions to mitigate it. Consequently, a simplified PM is proposed for virtualisation based C-RAN. In this model, the power cost of server virtualisation by hosting several virtual machines (VMs) is shown, in a time and cost effective way. The total reduction in the PC was about 75%, due to short-cutting the number of active servers in the network. Alongside, the latency cost due to such technique is modelled. Finally, to enable efficient virtualisation technology, live migrating the VMs amongst the servers is vital. However, this advantageous situation is concurrent with VM's migration time and power cost. Therefore, a model is proposed to calculate the power cost of VM's live migration, and shows the effect of such decision upon the total PC of the network/C-RAN. The proposed work converts the complexity of other proposed PMs, to a simplified and costless method. Concurrently, the time cost is added to the imposed virtualisation's time cost to formulate the total delay expected prior to these techniques' execution.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:764835 |
| Date | January 2017 |
| Creators | Alhumaima, Raad |
| Contributors | Al-Raweshidy, H. ; Nilavalan, R. |
| Publisher | Brunel University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://bura.brunel.ac.uk/handle/2438/15605 |
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