Please use this identifier to cite or link to this item: http://41.63.8.17:80/jspui/handle/123456789/252
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dc.contributor.authorShawa, Abraham-
dc.date.accessioned2024-09-17T17:19:45Z-
dc.date.available2024-09-17T17:19:45Z-
dc.date.issued2023-
dc.identifier.urihttp://41.63.8.17:80/jspui/handle/123456789/252-
dc.description.abstractThe advent of the fifth generation (5G) of wireless technology has presented unprecedented challenges in network management due to its complex, heterogeneous nature involving multiple domains. Addressing these challenges, the paper at hand proposes an innovative orchestration framework designed for such diverse software-defined networks (SDNs) that are inherent in 5G systems. The objective of this framework is to ensure that service delivery is optimized across various network segments, achieving a seamless end-to-end communication experience for users. To orchestrate the network dynamically, the framework integrates machine learning algorithms that can predict network conditions and user demands. This predictive capability allows the network to adapt in real-time, effectively managing resources and maintaining service quality. The cross-layer approach of the framework is key; it merges insights from the physical infrastructure with that from the application layer to enable more accurate and holistic decision-making processes. One of the challenges in heterogeneous network environments is achieving interoperability between different SDN controllers. To overcome this, the paper introduces a set of application programming interfaces (APIs) that facilitate communication and coordination among various network controllers. This ensures that the orchestration framework can function across multiple domains without compatibility issues. The performance of the proposed orchestration framework was tested and showed considerable improvements in network efficiency. Notably, it was observed that there was a decrease in service latency and an increase in data throughput. Furthermore, the framework promoted better resource utilization, leading to cost benefits for network operators, as well as enhanced scalability, which is a critical requirement for modern networks.en_US
dc.language.isoenen_US
dc.publisherZCAS Universityen_US
dc.subjectReal-World Deploymenten_US
dc.subjectScalabilityen_US
dc.subjectApplication Programming Interfaces (APIs)en_US
dc.subjectNetwork Efficiencyen_US
dc.subjectEnd-to-End Communicationen_US
dc.subjectPredictive Analyticsen_US
dc.subjectResource Managementen_US
dc.subjectNetwork Interoperabilityen_US
dc.subjectQuality of Experience (QoE),en_US
dc.subjectQuality of Service (QoS),en_US
dc.subjectMachine Learning Algorithmsen_US
dc.subjectCross-Layer Approachen_US
dc.subjectMulti-Domain Service Optimizationen_US
dc.subjectSoftware-Defined Networking (SDN)en_US
dc.subjectHeterogeneous Networksen_US
dc.subjectDynamic Orchestrationen_US
dc.subject5G Networksen_US
dc.titleDynamic Orchestration of Heterogeneous Software-Defined Networks for Multi-Domain Service Optimization in End to End 5G Environments.en_US
dc.typeThesisen_US
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