Organizations have become increasingly dependent on information systems to perform their business as usual activities. Moreover, organizations have registered an increase in the number of cyber-attacks, namely: industrial espionage, confidential information leakage, digital theft or pure damage to corporate image and reputation. In order to try to mitigate these issues, organizations like the National Institute of Standards and Technology (NIST) have made an effort to establish a cybersecurity protection guide. This paper presents a baseline for developing a generic and flexible model for manipulating key factors inside organizations: Processes, Human Resources and Technology, and extrapolate the percentage of compliance with the NIST cybersecurity framework, measure the current cybersecurity risk and allocate financial investments towards specific compliance objectives and reduce the overlapping of existing resources.

Fifth generation (5G) and Beyond-5G (B5G) will be characterized by highly dense deployments, both on network plane and user plane. Internet of Things, massive sensor deployments and base stations will drive even more energy consumption. User behavior towards mobile service usage is witnessing a paradigm shift with heavy capacity, demanding services resulting in an increase of both screen time and data transfers, which leads to additional power consumption. Mobile network operators will face additional energetic challenges, mainly related to power consumption and network sustainability, starting right in the planning phase with concepts like energy efficiency and greenness by design coming into play. The main contribution of this work is a two-tier method to address such challenges leading to positively-offset carbon dioxide emissions related to mobile networks using a novel approach. The first tier contributes to overall power reduction and optimization based on energy efficient methods applied to 5G and B5G networks. The second tier aims to offset the remaining operational power usage by completely offsetting its carbon footprint through geosequestration. This way, we show that the objective of minimizing overall networks’ carbon footprint is achievable. Conclusions are drawn and it is shown that carbon sequestration initiatives or program adherence represent a negligible cost impact on overall network cost, with the added value of greener and more environmentally friendly network operation. This can also relieve the pressure on mobile network operators in order to maximize compliance with environmentally neutral activity.

Increasingly mobile data traffic and high quality service demand has driven fast standards development and new mobile technologies deployment. Traffic demand in 5G networks is expected to rise unprecedentedly, bringing mobile network operators (MNOs) additional challenges, and added pressure regarding carbon footprint reduction. This work aims to study the environmental and financial feasibility of MNOs becoming carbon neutral, by developing biotic carbon dioxide sequestration programs. If feasibility exists, it would be extended and applied to future networks and other environmental scenarios. It is shown that achieving carbon neutrality is possible for heterogeneous deployments, especially when low energy powered base stations like femtocells exist and that the financial costs of such aim might represent little or negligible additional cost expenditure, with the added value of greener and environmental friendly network operation.

Increasingly mobile data traffic and high quality service demand has driven standard developments and new mobile technologies deployment at an unprecedented level. Long Term Evolution (LTE) standard and its improved version LTE-Advanced (LTE-A) are two technology standards developed to cope with high levels of mobile data traffic demand. However, traffic and revenue disparity still is a reality, suggesting that traditional network deployment methods - based mainly on macro cellular sites - might prove to be cost ineffective in the long term. From another perspective, and increasingly important for mobile network operators, revenue is also a function of each mobile network deployment's sustainability. This work aims to comprehensively elaborate on those matters by presenting four specific scenarios with a comparative analysis of both macro and femtocell deployments (single and both technology networks). For each scenario, capacity, cost effectiveness and expected carbon emissions are the evaluated key indicators. This kind of analysis provides mobile networks operators with relevant information, enabling them to sustainably adapt business and provisioning models as well as network deployment strategies to current and future technological standards, while minimizing capital and operational expenditure (CAPEX/OPEX). The main contribution is that in short term, mixed macro and femtocell deployment scenarios are the most cost effective and sustainable option, while in mid to long term, as data traffic demand rises, femtocell deployments become the most sustainable, not only from economical and environmental points of view, but also from network coverage stand point.

This work focuses on providing enhanced capacity planning and resource management for 5G networks through bridging data science concepts with usual network planning processes. For this purpose, we propose using a subscriber-centric clustering approach, based on subscribers’ behavior, leading to the concept of intelligent 5G networks, ultimately resulting in relevant advantages and improvements to the cellular planning process. Such advanced data-science-related techniques provide powerful insights into subscribers’ characteristics that can be extremely useful for mobile network operators. We demonstrate the advantages of using such techniques, focusing on the particular case of subscribers’ behavior, which has not yet been the subject of relevant studies. In this sense, we extend previously developed work, contributing further by showing that by applying advanced clustering, two new behavioral clusters appear, whose traffic generation and capacity demand profiles are very relevant for network planning and resource management and, therefore, should be taken into account by mobile network operators. As far as we are aware, for network, capacity, and resource management planning processes, it is the first time that such groups have been considered. We also contribute by demonstrating that there are extensive advantages for both operators and subscribers by performing advanced subscriber clustering and analytics.