George T. Karetsos

Flood Early Warning Systems (FEWSs) increasingly combine heterogeneous observation streams, computational models, and interoperable information infrastructures. This survey reviews how Internet of Things (IoT)-based sensing, communication protocols, data pre-processing, machine learning, data assimilation, and operational platforms contribute to flood monitoring and early warning. Rather than presenting a new forecasting model or claiming end-to-end experimental validation, the paper synthesizes cross-layer integration patterns between observation networks, computational methods, uncertainty-aware decision-support, and standards-based middleware. Particular attention is given to the interface between in situ IoT observations and data-driven or physics-informed modelling approaches, including data assimilation and hyper-local flood simulation. A FIWARE/NGSI-LD hydrometeorological monitoring deployment is included as an infrastructure and interoperability case study, demonstrating the continuous collection and ingestion of sensor observations into the platform, semantic normalization, temporal persistence, and standards-based access to monitoring data.

Vehicle-to-everything (V2X) communications has gained a lot of interest in recent years and inevitably became part of the 5th-Generation New Radio (5G-NR) technologies, namely the sub-6GHz 5G and millimeter wave (mmWave) 5G. Also, the 3rd-Generation Partnership Project (3GPP) has defined reliability, end-to-end latency, data rate and range as the most important quality of service (QoS) parameters, which become crucial in highway propagation environments where the vehicles are moving at high speeds. These parameters are mostly improved by channel coding, which is a mechanism for limiting errors and improving the communication quality. Therefore, in this paper, we investigate the impact of use of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5G-NR polar codes and low-density parity-check codes (LDPC) in 5G V2X highway propagation environments and analyze the QoS parameters for both sub-6GHz 5G and mmWave 5G technologies. Our analysis shows that turbo-based coding schemes can be a future candidate for small data frame 5G V2X highway communications, since they present superior performance in most of the aforementioned QoS parameters.

Channel coding is a fundamental procedure in wireless telecommunication systems and has a strong impact on the data transmission quality. This effect becomes more important when the transmission must be characterised by low latency and low bit error rate, as in the case of vehicle-to-everything (V2X) services. Thus, V2X services must use powerful and efficient coding schemes. In this paper, we thoroughly examine the performance of the most important channel coding schemes in V2X services. More specifically, the impact of use of 4th-Generation Long-Term Evolution (4G-LTE) turbo codes, 5th-Generation New Radio (5G-NR) polar codes and low-density parity-check codes (LDPC) in V2X communication systems is researched. For this purpose, we employ stochastic propagation models that simulate the cases of line of sight (LOS), non-line of sight (NLOS) and line of sight with vehicle blockage (NLOSv) communication. Different communication scenarios are investigated in urban and highway environments using the 3rd-Generation Partnership Project (3GPP) parameters for the stochastic models. Based on these propagation models, we investigate the performance of the communication channels in terms of bit error rate (BER) and frame error rate (FER) performance for different levels of signal to noise ratio (SNR) for all the aforementioned coding schemes and three small V2X-compatible data frames. Our analysis shows that turbo-based coding schemes have superior BER and FER performance than 5G coding schemes for the vast majority of the considered simulation scenarios. This fact, combined with the low-complexity requirements of turbo schemes for small data frames, makes them more suitable for small-frame 5G V2X services.

Summary: Vehicular ad hoc networks (VANETs) are receiving increased attention, and several routing protocols have been proposed already by the research community. In such a framework, social aspects and human mobility are important performance enablers, which however are mostly overlooked. In this work, we propose the socially aware CLWPR (SCALE) protocol, significantly enhancing cross‐layer weighted position‐based routing (CLWPR), a routing protocol for urban VANET environments, combining social properties such as trust, influence, and users' individual mobility patterns to its core design in order to support an efficient content dissemination scheme. The design principles of SCALE that rely on both online and offline social metrics quantifying relationships on social networking platforms and opportunistic contacts of nodes due to physical proximity, respectively, are presented, while nodes with close online and offline social relationship are favored as next forwarder nodes. Subsequently we provide the performance evaluation of SCALE against other routing protocols in distributed vehicular networks, employing representative urban scenarios with synthetic and real traffic. It is shown that the proposed approach presents improved performance in terms of Packet Delivery Ratio (PDR) and throughput when compared with other similar protocols by an average of 37% in scenarios with synthetic dataset and 58% with real dataset for PDR and by an average of 45% in scenarios with synthetic dataset and 61% with real dataset for throughput.

Reduction of energy consumption is becoming a crucial aspect of wireless communications, due to the need of lowering CO2 emissions and enhancing mobile network operators OPEX. In this work we consider a heterogeneous mobile network topology with coexisting macrocellular and microcellular Base Stations (BSs). By employing two energy optimization heuristics we determine operational profiles for the network BSs under various traffic loads and examine their impact on handoff signaling rate and achievable throughput. The obtained simulation results exhibit that the proposed BS operational profiles yield quite satisfactory energy saving gains compared to Full Operational Topology (FOT) networks in all examined scenarios, without degradation of the network's handoff signaling rate and achievable throughput of the mobile subscribers.

We propose a clustering scheme for wireless sensor nodes in hierarchical wireless sensor networking architectures that employs mobile relay nodes in order to achieve energy conservation and network lifetime prolongation. The key aspects of our scheme are relay node relocation and reclustering when failures are detected. The performance of the proposed approach is evaluated via simulations for various topology layouts based on the sensor node population and number of mobile relay nodes employed. The results show significant energy savings in particular for topologies with large numbers of sensors.