VNF placement optimization at the edge and cloud

Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions t

Agile management of 5G core network based on SDN/NFV technology

In the 5G era, radio IP capacity is expected to reach 20 Gbit/s per sector, and ultra-large content traffic will travel across the faster wireless/wireline access network and packet core network. Also massive and mission-critical IoT is the main differentiator of 5G services. These types of real-time and large-bandwidth consuming services require radio latency of less than 1ms, and end-to-end latency of less than a few ms. By distributing 5G core nodes closer to cell sites, backhaul traffic volume and latency can be significantly reduced by having mobile devices downloading content immediately from a closer content server. In this paper, we propose a novel solution based on SDN (Software Defined Network) and NFV (Network Function Virtualization) technology in order to achieve an agile management of distributed 5G core network functionalities and services with PoC implementation targeted for Pyungchang Winter Olympics

Energy Efficient Network Function Virtualisation in 5G Networks

Once the dust settled around 4G, 5G mobile networks become the buzz word in the world of communication systems. The recent surge of bandwidth-greedy applications and the proliferation of smart phones and other wireless connected devices has led to an enormous increase in mobile traffic. Therefore, 5G networks have to deal with a huge number of connected devices of different types and applications, including devices running life-critical applications, and facilitate access to mobile resources easily. Therefore given the increase in traffic and number of connected devices, intelligent and energy efficient architectures are needed to adequately and sustainably meet these requirements. In this thesis network function virtualisation is investigated as a promising paradigm that can contribute to energy consumption reduction in 5G networks. The work carried out in this thesis considers the energy efficiency mainly in terms of processing power consumption and network power consumption. Furthermore, it considers the energy consumption reduction that can be achieved by optimising the locations of virtual machines running the mobile 5G network functions. It also evaluates the consolidation and pooling of the mobile resources. A framework was introduced to virtualise the mobile core network functions and baseband processing functions. Mixed integer linear programming optimisation models and heuristics were developed minimise the total power consumption. The impact of virtualisation in the 5G front haul and back haul passive optical network was investigated by developing MILP models to optimise the location of virtual machines. A further consideration is caching the contents close to the user and its impact on the total power consumption. The impact of a number of factor on the power consumption were investigated such as the total number of active users, the backhaul to the fronthaul traffic ratio, reduction/expansion in the traffic due to baseband processing, and the communication between virtual machines. Finally, the integration of network function virtualisation and content caching were introduced and their impact on improving the energy efficiency was investigated