A Review on the Role of Nano-Communication in Future Healthcare Systems: A Big Data Analytics Perspective

This paper presents a first-time review of the open literature focused on the significance of big data generated within nano-sensors and nano-communication networks intended for future healthcare and biomedical applications. It is aimed towards the development of modern smart healthcare systems enabled with P4, i.e. predictive, preventive, personalized and participatory capabilities to perform diagnostics, monitoring, and treatment. The analytical capabilities that can be produced from the substantial amount of data gathered in such networks will aid in exploiting the practical intelligence and learning capabilities that could be further integrated with conventional medical and health data leading to more efficient decision making. We have also proposed a big data analytics framework for gathering intelligence, form the healthcare big data, required by futuristic smart healthcare to address relevant problems and exploit possible opportunities in future applications. Finally, the open challenges, future directions for researchers in the evolving healthcare domain, are presented

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

Prediction-based techniques for the optimization of mobile networks

Mención Internacional en el título de doctorMobile cellular networks are complex system whose behavior is characterized by the superposition of several random phenomena, most of which, related to human activities, such as mobility, communications and network usage. However, when observed in their totality, the many individual components merge into more deterministic patterns and trends start to be identifiable and predictable. In this thesis we analyze a recent branch of network optimization that is commonly referred to as anticipatory networking and that entails the combination of prediction solutions and network optimization schemes. The main intuition behind anticipatory networking is that knowing in advance what is going on in the network can help understanding potentially severe problems and mitigate their impact by applying solution when they are still in their initial states. Conversely, network forecast might also indicate a future improvement in the overall network condition (i.e. load reduction or better signal quality reported from users). In such a case, resources can be assigned more sparingly requiring users to rely on buffered information while waiting for the better condition when it will be more convenient to grant more resources. In the beginning of this thesis we will survey the current anticipatory networking panorama and the many prediction and optimization solutions proposed so far. In the main body of the work, we will propose our novel solutions to the problem, the tools and methodologies we designed to evaluate them and to perform a real world evaluation of our schemes. By the end of this work it will be clear that not only is anticipatory networking a very promising theoretical framework, but also that it is feasible and it can deliver substantial benefit to current and next generation mobile networks. In fact, with both our theoretical and practical results we show evidences that more than one third of the resources can be saved and even larger gain can be achieved for data rate enhancements.Programa Oficial de Doctorado en Ingeniería TelemáticaPresidente: Albert Banchs Roca.- Presidente: Pablo Serrano Yañez-Mingot.- Secretario: Jorge Ortín Gracia.- Vocal: Guevara Noubi

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Airborne Network Data Availability Using Peer to Peer Database Replication on a Distributed Hash Table

The concept of distributing one complex task to several smaller, simpler Unmanned Aerial Vehicles (UAVs) as opposed to one complex UAV is the way of the future for a vast number of surveillance and data collection tasks. One objective for this type of application is to be able to maintain an operational picture of the overall environment. Due to high bandwidth costs, centralizing all data may not be possible, necessitating a distributed storage system such as mobile Distributed Hash Table (DHT). A difficulty with this maintenance is that for an Airborne Network (AN), nodes are vehicles and travel at high rates of speed. Since the nodes travel at high speeds they may be out of contact with other nodes and their data becomes unavailable. To address this the DHT must include a data replication strategy to ensure data availability. This research investigates the percentage of data available throughout the network by balancing data replication and network bandwidth. The DHT used is Pastry with data replication using Beehive, running over an 802.11 wireless environment, simulated in Network Simulator 3. Results show that high levels of replication perform well until nodes are too tightly packed inside a given area which results in too much contention for limited bandwidth

Securing the Internet of Things Communication Using Named Data Networking Approaches

The rapid advancement in sensors and their use in devices has led to the drastic increase of Internet-of-Things (IoT) device applications and usage. A fundamental requirement of an IoT-enabled ecosystem is the device’s ability to communicate with other devices, humans etc. IoT devices are usually highly resource constrained and come with varying capabilities and features. Hence, a host-based communication approach defined by the TCP/IP architecture relying on securing the communication channel between the hosts displays drawbacks especially when working in a highly chaotic environment (common with IoT applications). The discrepancies between requirements of the application and the network supporting the communication demands for a fundamental change in securing the communication in IoT applications. This research along with identifying the fundamental security problems in IoT device lifecycle in the context of secure communication also explores the use of a data-centric approach advocated by a modern architecture called Named Data Networking (NDN). The use of NDN modifies the basis of communication and security by defining data-centric security where the data chunks are secured directly and retrieved using specialized requests in a pull-based approach. This work also identifies the advantages of using semantically-rich names as the basis for IoT communication in the current client-driven environment and reinforces it with best-practices from the existing host-based approaches for such networks. We present in this thesis a number of solutions built to automate and securely onboard IoT devices; encryption, decryption and access control solutions based on semantically rich names and attribute-based schemes. We also provide the design details of solutions to sup- port trustworthy and conditionally private communication among highly resource constrained devices through specialized signing techniques and automated certificate generation and distribution with minimal use of the network resources. We also explore the design solutions for rapid trust establishment and vertically securing communication in applications including smart-grid operations and vehicular communication along with automated and lightweight certificate generation and management techniques. Through all these design details and exploration, we identify the applicability of the data-centric security techniques presented by NDN in securing IoT communication and address the shortcoming of the existing approaches in this area