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Resource Allocation and Bandwidth Optimization in SDN-Based Cellular Network

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In the most recent years, Fifth Generation (5G) communication is a leading networking paradigm that entails a huge set of capabilities and opportunities. 5G is realized with the aim of hyper-connected devices and omnipresent connectivity among everything with immense data rate and ultra-low latency. This hyperactive networking requires a flexible network architecture that facilitates diversified users’ demands on the fly. Hence, flexibility is the main building block for 5G architectures with major challenges in the designing of new network architecture. Toward 5G realization, Software Defined Networking (SDN) and Network Function Virtualization (NFV) are contemplated as main enablers for the exploration and development of on-demand deployment and network services in a short period. The core idea of SDN is a distinct control plane and data/forwarding plane which performs network orchestration from a logically/physically central controller. Network services and applications are executed on the controller through open Application Programming Interfaces (APIs) which helps in facile inception of new services/applications on the commodity hardware. SDN with the integration of NFV provides end-to-end resources provision and service orchestration for flexible deployment of 5G services. The wireless resources are scarce in nature and need fair allocation for network customer satisfaction. The efficient resource allocation in a growing network is a major challenge. This dissertation focuses on fair resource allocation and bandwidth management in SDN based cellular network. In this dissertation, a framework for dynamic resource allocation and bandwidth management is presented that leverages SDN and NFV in the cellular network. The proposed framework i.e., Novel Policy framework for Resource Allocation (NPRA) framework pulls the benefits of virtualization for resource orchestration in SDN based cellular network. A hierarchical virtualization for resource allocation and bandwidth management is presented in the core and Radio Access Network (RAN) by running multiple logical networks called slices. These logical network slices are centrally abstracted on the SDN controller in the core network and the wireless virtualizer module is used for the wireless resources’ allocation to the respective slices. This thesis mainly consists of two parts. In the first part, a detailed overview of SDN and SDN based cellular architecture is presented and extensive literature is reviewed. In the second part, a detailed NPRA architecture is discussed along with its key components which include traffic load balancing, resource optimization, and traffic flow classification. NPRA framework provides an optimal resource allocation in terms of bandwidth management to fulfill the 5G data rate requirement with the help of SDN and NFV. The aim has been achieved to provide an optimized and efficient resource allocation for the virtualized networks based on their Quality of Services (QoS) requirements. In this dissertation, an integrated framework of SDN and NFV is proposed. Network traffic engineering is performed on in-band data traffic and optimization problem is considered as a non-linear optimization problem. The experimental results show that when network flow classification is obtained using machine learning algorithms, a performance efficiency of 99.63% in the case of Long-Short Term Memory (LSTM) is achieved. Whereas, this performance efficiency is around 95% and 92.55% for Convolutional Neural Network (CNN) and Deep Neural Network (DNN), respectively.
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