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| Reference | Policy/algorithm/strategy | Problem addressed | Improvement/achievement | Weakness/limitation |
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| [63] (2020) | Software-defined network orchestrator | Challenges and demands presented by OpenFlow. Controlled software-defined optical networks (SDONs) and the issue of matching between services and SDON. | Improved the performance of several services in SDON | — |
| [64] (2021) | Software-defined network orchestrator | Network performance based on blocking probability, jitter, delay metrics, and assignment of resource problems and challenges inside the controller. | Improved network resource allocation path. Improved blocking probability. Identifies the path that best suits each flow. | Limited resource utilisation. Needs further improvement with machine learning algorithms. The proposed algorithm is not dynamic and flexible. |
| [112] (2020) | Network service orchestration | Compare several single and multidomain attempts with each architecture’s advantages and disadvantages | To contribute to an overall awareness of common ideas and methods to NSO practice | Orchestration mechanisms are not massively scalable and difficult to integrate with external components. One or more orchestrators might be involved, open and flexible enough to deal with future applications. |
| [55] (2020) | Network service orchestration | Prove best performed MANO frameworks based on some defined KPIs and metrics | Based on findings proposed real applications deployed in production environments using more powerful NFVIs that support different virtualisation technologies (e.g., Kubernetes) | No real-time application. OSM proved mature and robust and Cloudify proved appropriate for deployments that have no strict requirements such as runtime, SLA contracts, and network slicing, while SONATA provides a complete tool chain for automated NS management in the dynamic 5G context era. |
| [55] (2019) | Software-defined network orchestrator/NFVO | For balancing of network load for easier distribution of resources | Improvement in the “utilisation of bandwidth” and the overall throughput reducing the delays | Quality factor, signal-to-noise ratio, bit error rate, and overall performance are limited to 45 km |
| [131] (2019) | Software-defined network orchestrator | To manage the throughput and bandwidth efficiently | Improved throughput of the network and well-met traffic standards | More complex and cost ineffective since multiple SDN controllers are to be used. High power and energy usage. |
| [132] (2018) | Software-defined network orchestrator and Bayesian classifier | Less service consciousness when operating along with an OpenFlow protocol and less efficiency in bandwidth scheduling. These service areas in SDON need improvement. | This study proposes the use of the platform “Bayesian classifier-based service-aware (BC-SA).” The BC-SA system has been implemented using the Bayes network paradigm for multiple services. This BC-SA technique was used by the SDON system to carry out more efficient planning of resources. | High latency and unreliable approach |
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