Mobile Internet data traffic has experienced an exponential growth over the last few years due to the rise of demanding multimedia content and the increasing number of mobile devices. Seamless mobility support at the IP level is envisioned as a key architectural requirement in order to deal with the ever-increasing demand for data and to efficiently utilize a plethora of different wireless access networks. Current efforts from both industry and academia aim to evolve the mobility management protocols towards a more distributed operation to tackle shortcomings of fully centralized approaches. However, distributed solutions face several challenges that can result in lower performance which might affect real-time and multimedia applications. In this paper, we conduct an analytical and simulated evaluation of the main centralized and proposed Distributed Mobility Management (DMM) solutions. Our results show that, in some scenarios, when users move at high speed and/or when the mobile node is running long-lasting applications, the DMM approaches incur high signaling cost and long handover latency.

In this paper, we present a work based on the computational load distribution among the homogeneous nodes and the Hub/Sink of Wireless Sensor Networks (WSNs). The main contribution of the paper is an early decision support framework helping WSN designers to take decisions about computational load distribution for those WSNs where power consumption is a key issue (when we refer to “framework” in this work, we are considering it as a support tool to make decisions where the executive judgment can be included along with the set of mathematical tools of the WSN designer; this work shows the need to include the load distribution as an integral component of the WSN system for making early decisions regarding energy consumption). The framework takes advantage of the idea that balancing sensors nodes and Hub/Sink computational load can lead to improved energy consumption for the whole or at least the battery-powered nodes of the WSN. The approach is not trivial and it takes into account related issues such as the required data distribution, nodes, and Hub/Sink connectivity and availability due to their connectivity features and duty-cycle. For a practical demonstration, the proposed framework is applied to an agriculture case study, a sector very relevant in our region. In this kind of rural context, distances, low costs due to vegetable selling prices and the lack of continuous power supplies may lead to viable or inviable sensing solutions for the farmers. The proposed framework systematize and facilitates WSN designers the required complex calculations taking into account the most relevant variables regarding power consumption, avoiding full/partial/prototype implementations, and measurements of different computational load distribution potential solutions for a specific WSN.

The evolution of interconnected systems and the evolving demands in service requirements have led to data centers integrating multiple heterogeneous technologies that must coexist. Consequently, the resource management and the security of the infrastructure are becoming more complex than in traditional scenarios. In this context, technologies such as Software-Defined Networking (SDN) or Network Function Virtualization (NFV) are being embraced as mechanisms that facilitate communication management. The integration of both technologies into a single framework, termed Software-Defined NFV (SDNFV) introduces a multitude of tools for managing the security of the data center’s resources. This work delineates the primary characteristics of the evolution of these communication networks and their application to information security and communications within a data center. It presents an illustrative use case demonstrating the application of these next-generation technologies to detect and mitigate a security issue through virtualized network functions deployed in containers.

Social Complex Networks in communication networks are pivotal for comprehending the impact of human-like interactions on information flow and communication efficiency. These networks replicate social behavior patterns in the digital realm by modeling device interactions, considering friendship, influence, and information-sharing frequency. A key challenge in communication networks is their dynamic topologies, driven by dynamic user behaviors, fluctuating traffic patterns, and scalability needs. Analyzing these changes is essential for optimizing routing and enhancing the user experience. This paper introduces a network model tailored for Opportunistic Networks, characterized by intermittent device connections and disconnections, resulting in sporadic connectivity. The model analyzes node behavior, extracts vital properties, and ranks nodes by influence. Furthermore, it explores the evolution of node connections over time, gaining insights into changing roles and their impact on data exchange. Real-world datasets validate the model’s effectiveness. Applying it enables the development of refined routing protocols based on dynamic influence rankings. This approach fosters more efficient, adaptive communication systems that dynamically respond to evolving network conditions and user behaviors.

Public sector organizations are facing an escalating challenge with the increasing volume and complexity of cyberattacks, which disrupt essential public services and jeopardize citizen data and privacy. Effective cybersecurity management has become an urgent necessity. To combat these threats comprehensively, the active involvement of all functional areas is crucial, necessitating a heightened holistic cybersecurity awareness among tactical and operational teams responsible for implementing security measures. Public entities face various challenges in maintaining this awareness, including difficulties in building a skilled cybersecurity workforce, coordinating mixed internal and external teams, and adapting to the outsourcing trend, which includes cybersecurity operations centers (CyberSOCs). Our research began with an extensive literature analysis to expand our insights derived from previous works, followed by a Spanish case study in collaboration with a digitization-focused public organization. The study revealed common features shared by public organizations globally. Collaborating with this public entity, we developed strategies tailored to its characteristics and transferrable to other public organizations. As a result, we propose the “Wide-Scope CyberSOC” as an innovative outsourced solution to enhance holistic awareness among the cross-functional cybersecurity team and facilitate comprehensive cybersecurity adoption within public organizations. We have also documented essential requirements for public entities when contracting Wide-Scope CyberSOC services to ensure alignment with their specific needs, accompanied by a management framework for seamless operation.

The increase in frequency and complexity of cyberattacks has heightened concerns regarding cybersecurity and created an urgent need for organizations to take action. To effectively address this challenge, a comprehensive and integrated approach is required involving a cross-functional cybersecurity workforce that spans tactical and operational levels. In this context there can be various combinations of cybersecurity actions that affect different functional domains and that allow for meeting the established requirements. In these cases, agreement will be needed, but finding high-quality combinations requires analysis from all perspectives on a case-by-case basis. With a large number of cybersecurity factors to consider, the size of the search space of potential combinations becomes unmanageable without automation. To solve this issue, we propose Fast, Lightweight, and Efficient Cybersecurity Optimization (FLECO), an adaptive, constrained, and multi-objective genetic algorithm that reduces the time required to identify sets of high-quality cybersecurity actions. FLECO enables productive discussions on viable solutions by the cross-functional cybersecurity workforce within an organization, fostering managing meetings where decisions are taken and boosting the overall cybersecurity management process. Our proposal is novel in its application of evolutionary computing to solve a managerial issue in cybersecurity and enhance the tactical–operational cybersecurity management process.