الفهرس | Only 14 pages are availabe for public view |
Abstract Networks nowadays are playing an integral role in how people interact and communicate, as well as how businesses operate and offer services to end customers. With the growth of user demands and high data rates, the ability to manage this data traffic and utilize the network resources has become a pivotal aspect for future networks (e.g., Fifth Generation (5G)). The evolution to 5G system and services is a key enabler of the networked society paradigm where all persons and things will be connected everywhere, every time, using any type of devices and technology. The 5G technology is presently in its early research stages and expected to merge various types of advanced paradigms which make 5G technology more powerful, one of these paradigms is Software-Defined Networking (SDN). SDN is a recent technology that established a new method for creating and administering networks. It is a new architecture which has been designed to enable more agile and cost effective networks. It has a significant role in network optimization and performance improvement and has been seen as a promising approach for the vision of 5G networks, which will likely play a crucial role in the 5G networks design. A critical understanding of this emerging paradigm is necessary to address many challenges of the future SDN-enabled 5G technology such as network security, controller design, resource management, network monitoring and measuring, etc. In this thesis, we propose SDN-based resource management algorithms for future 5G networks specially server load balancing. Since the traditional load balancers suffer from inflexibility and difficulty to manage network flows and they are very expensive hardware dedicated devices, SDN offers an inexpensive, a flexible, and a promising solution for traditional load balancer limitations. The main SDN concept is separating both the data and control planes allowing network programmability and centralized control for the network. Since the current traditional network cannot endure more user needs, we apply different load balancing strategies to distribute the user requests among a number of servers. iii This thesis aims to develop OpenFlow-based approaches for dynamic server load balancing in SDN environment. Hence, we propose “Bandwidth-based”, “CPU-based”, and “CPU-Memory-based” load balancing techniques using Ryu OpenFlow controller that distributes the network requests among multiple servers based on the servers’ state. The performance of the proposed schemes is evaluated and compared with different traditional load balancing strategies (Random-based, Round-robin, and Connections-based) under a mininet emulation and a Raspberry Pi-based implementation. Emulation and hardware implementation results show that the proposed schemes achieve more reliability and higher resource utilization compared to the traditional load balancing strategies; in addition, they have a lower response time and higher throughput. The proposed schemes exhibit more scalability and low-cost characteristics. |