Software-Defined Networking (SDN)

Background: Software-Defined Networking (SDN) is widely considered a new paradigm shift in today’s telecommunication evolving method of centralized control, program interface, and dynamic resource configuration. Members of such a network can be reached through single-hop or multi-hop communication and is, however, still faced with inexhaustible challenges in scalability, security, energy consumption as well as Quality of Service (QoS). Objective: Specifically, the article will seek to compare both SDN enabled network as well as legacy networks as regards to established parameters like scalability, security, power consumption, traffic control and path finding. The research aims to fill these gaps by employing state-of-art methods and offer useful recommendations of SDN implementation. Methods: Both simulation and analytical modeling were used to evaluate the proposed SDN architectures under different loads. Metrics were assessed with the congestion control based on the neural network, optimization involved the multiple objectives, and security assessment via game theory. Analyses for statistical significance further supported the performance enhancements determined. Results: The results show 44% improved latency, 33% better energy consumption, and better load balancing in SDN-enabled network. Neural network-based mechanisms were able to reroute 95% of the time under low traffic conditions, while distributed controller-based strategy had high scalability and security. Conclusion: This study points to the capacity of SDN to revolutionize the contemporary telecommunication with strong techniques for comprehensive problems. For the future work it is recommended to conduct validations in operational conditions, and include underdevelopment technologies into the system hierarchy to improve its flexibility and operation characteristics.

Background: Satellite systems which orbit in Low Earth Orbit (LEO) are one of the innovative solutions to enable the connectivity in segregated geophysical parts of the world which are left out of the digital society, as they provide almost instantaneous, high-speed connections. Despite progress made there are barriers to deployment including lack of scalability, high costs, traffic management, and environmental vulnerability. Objective: The aim of the present study is enhancing the overall throughput and concurrently – steaking the LEO satellite networks reliable operation in various applications with usage of the effective traffic control and adaptive routing techniques meanwhile taking into account the costs and other factors. Methods: Quantitative and qualitative research was used in this study in which both theoretical and simulations of LEO satellite networks were used. The traffic engineering was done using Software-defined networking (SDN), whereas bio-inspired routing, including bee colony optimization algorithms, were evaluated for adaptive routing. Parameters like latency, throughout, packet loss, and costs that are exhibited to change with conditions like atmospheric interferences were also considered. Results: The results proved that the current latency can be cut by up to 60%, packet lost by up to 90%, with operating expenses slashed beyond 85% and resource utilization beyond 85%. Improved routing techniques improved transmission reliability over dynamic network loads; simulations have validated the environmental suitability of LEO networks. Conclusion: The article offers a coherent framework for the appropriate design of LEO satellite networks and discusses their ability to address the digital divide and guarantee economic, effective, and highly accessible computing access globally.