# A Modular Web-Based Software Solution for Mobile Networks Planning, Operation and Optimization
## 7 Conclusions and Future Work  
This paper presents a web-based modular solution that allows users to carry out assigned tasks of network OAM in an efficient and user-friendly manner. Its modular architecture provides access to multiple MNO data sources with the associated visualizations, and data management processes. Additionally, it is developed to operate a set of RAN algorithms while allowing the addition of future algorithms. With this software solution, users can easily overview the state of the network, either by focusing on a particular geographical area, or by looking at a particular site and/or cell, as well as considering overall KPIs. After, data analysis decisions can be made to optimize the network behavior. This process of decision-based optimization is mostly supported by the outcome of simulations that users may require to be run. The solution provides a simulation module containing nine RAN algorithms, for that purpose.  
From the two use case studies presented in Section 6, we have demonstrated how a radio engineer can benefit from the proposed web-based solution, to conduct complex OAM tasks in a user friendly and efficient manner. From firstly data extraction, including multiples data sources and domains, in a particular context, to extracting benefit (detailed network diagnosis, or network optimization/simulations) by making use of high-quality RAN algorithms, the solution should represent a step forward in mobile networks' optimization. Besides the presented use case studies, the combination of all RAN algorithms, with the multiple data sources, and the functionalities implemented in the web-based solution, enables a wide range of tasks within an operator OAM life cycle, by exploiting the intuitive design of the solution.  
Finally, regarding the visualizations we get, it is worth pointing out the novel visual representation of cells in a site, which has proven to be very user-friendly and effective.  
In the future, we expect to pursuit various research paths in order to enhance the solution. In particular, the following ones deserve consideration:  
* Evaluate and improve the software solution performance and efficiency.
* The extension to 5G for all algorithms, with the inclusion of more 5G data sources.
* The transition from a model based on a relational database to a NOSQL model, in order to scale the volume of stored data as well as its variety.
* The solution interface adaptation (especially web services) to carry out all processing in the cloud (or in a big data related structure), thus allowing to process a larger volume of data in a relatively short period of time.
* The expansion of the web-based solution to the transmission and core network domains by including new data sources and incorporating new algorithms.  
Conceptualization, A.L., J.O., P.S., M.S. and P.V.; Funding acquisition, P.S. and P.V.; Methodology, A.L., J.O. and M.S.; Project administration, P.S. and P.V.; Software, A.L., J.O. and M.S.; Writing--original draft, A.L. and M.S; Writing--review & editing, J.O., P.S. and P.V. All authors have read and agreed to the published version of the manuscript.  
This work was funded by COMPETE/FEDER, under the project AI4 GREEN 16/SI/2019--I&DT Empresarial (Projetos Copromocao), through the international project CELTC-NEXT/EUREKA (C2018/1-5).  
The authors would like to thank to Instituto de Telecomunicacoes (IT) and to Celfinet for the support and contributions to this work.  
The authors declare no conflict of interest.