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Radio resource and its management is one of the key areas of research where technologies, infrastructure and challenges are rapidly changing as 5G system architecture demands a paradigm shift. The previous generation communication technologies require customizations and upgrades as 5G will remain inclusive for significantly long duration. Radio resource management (RRM) schemes that are evolved during LTE/LTE-A network environment period will remain relevant for 5G, however, these schemes must become more intelligent and adaptive for future as features and requirements of network and users will be diverse and highly demanding. In this paper, a comprehensive view is provided upon various aspects of RRM, its challenges and existing schemes. The existing RRM schemes are presented with their respective architecture which has significant impact on the approaches. The problem of RRM is multi-dimensional and different dimensions are presented with their respective solutions such as interference or energy management. In this paper study of legacy and state of the art RRM schemes is presented with their features and inefficiencies in the modern telecommunication era of heterogeneous, ultra-dense, very low latency and highly reliable mobile network. In addition to this various comparison among approaches and schemes are presented for analyzing the solutions. The need of RRM solution is critical and this paper aim is to outline the challenges, existing solutions and directions for research to find and develop smarter and more adaptive schemes for future.

We investigate numerically the chaotic dynamics of optically pumped quantum-dot (QD) spin vertically coupled surface emitting lasers (VCSELs) accounting for both ground state (GS) and excited state (ES) energy levels through the elaboration of the spin-flip model (SFM). The intensity dynamics associated with ES and GS transitions are studied by means of the largest Lyapunov exponent (LLE) and stability maps in terms of operational parameters (pump ellipticity and pump intensity), as well as material parameters (ES–GS intraband relaxation rate, spin relaxation rate and birefringence), are produced. It is established that although both ES and GS dynamics exhibit the same kind of nonlinear dynamics for a given set of control parameters, the ES and GS dynamics are weakly uncorrelated. This can be the basis for the realization of various functionalities including reservoir computing.

Subclinical mastitis is a common and economically significant disease that affects dairy sheep production. Thermal imaging presents a promising avenue for non-invasive detection, but existing methodologies often rely on simplistic temperature differentials, potentially leading to inaccurate assessments. This study proposes an advanced algorithmic approach integrating thermal imaging processing with statistical texture analysis and t-distributed stochastic neighbor embedding (t-SNE). Our method achieves a high classification accuracy of 84% using the support vector machines (SVM) algorithm. Furthermore, we introduce another commonly employed evaluation metric, correlating thermal images with commercial California mastitis test (CMT) results after establishing threshold conditions on statistical features, yielding a sensitivity (the true positive rate) of 80% and a specificity (the true negative rate) of 92.5%. The evaluation metrics underscore the efficacy of our approach in detecting subclinical mastitis in dairy sheep, offering a robust tool for improved management practices.

The fifth generation (5G) of mobile networks is designed to mark the beginning of the hyper-connected society through a broad set of novel features and disruptive characteristics, delivering massive connectivity, coverage and availability paired with unprecedented speed, throughput and capacity. Such a highly capable networking paradigm, facilitated by its integrated segments and available subsystems, will propel numerous cutting-edge, innovative and versatile services, spanning every possible business vertical. Augmented, response-capable healthcare services have already been identified as one of the prime objectives of both vendors and customers; therefore, addressing controversies and shortcomings related to the specific field is considered a priority for all stakeholders. The scope of this paper is to present the architectural elements of 5G which enable efficient, remote healthcare services along with emergency health monitoring and response capability. In addition, we propose a holistic scheme based on technical enablers such as Internet-of-Things (IoT) and Fog Computing, for mitigating common issues and current limitations which may compromise the proclaimed service delivery.

Spin-polarized vertical-cavity surface-emitting lasers (spin-VCSELs) have emerged as promising candidates for next-generation high-speed photonic systems due to their unique polarization dynamics. Here, we numerically simulate the generation of high-repetition-rate polarized optical pulses in a solitary dual-state quantum-dot (QD) spin-VCSEL by applying return to zero pulse modulation of the pump ellipticity ( P ). Unlike conventional modulation schemes relying on current variation or optical injection, our approach exploits the inherent dependence of the lasing threshold on P . By maintaining a steady injection current and dynamically switching P between different ellipticities, we induce a controlled transition between the non-lasing and lasing states, effectively generating optical pulses with controlled polarization. This mechanism enables pulse repetition rates reaching up to 15 GHz, paving the way for novel ultrafast modulation schemes in spintronic photonic devices. Our findings open new perspectives for energy-efficient, semiconductor lasers-based, high-speed optical communication and neuromorphic photonic processing by taking advantage of spin-dependent nonlinear dynamics in VCSELs.

In this paper, we look into smart water metering infrastructures that enable continuous, on-demand and bidirectional data exchange between metering devices, water flow equipment, utilities and end-users. We focus on the design, development and deployment of such infrastructures as part of larger, smart city, infrastructures. Until now, such critical smart city infrastructures have been developed following a cloud-centric paradigm where all the data are collected and processed centrally using cloud services to create real business value. Cloud-centric approaches need to address several performance issues at all levels of the network, as massive metering datasets are transferred to distant machine clouds while respecting issues like security and data privacy. Our solution uses the fog computing paradigm to provide a system where the computational resources already available throughout the network infrastructure are utilized to facilitate greatly the analysis of fine-grained water consumption data collected by the smart meters, thus significantly reducing the overall load to network and cloud resources. Details of the system’s design are presented along with a pilot deployment in a real-world environment. The performance of the system is evaluated in terms of network utilization and computational performance. Our findings indicate that the fog computing paradigm can be applied to a smart grid deployment to reduce effectively the data volume exchanged between the different layers of the architecture and provide better overall computational, security and privacy capabilities to the system.

Spin-Vertical Cavity Surface Emitting Lasers (spin-VCSELs) are undergoing increasing research effort for new paradigms in high-speed optical communications and photon-enabled computing. To date research in spin-VCSELs has mostly focused on Quantum-Well (QW) devices. However, novel Quantum-Dot (QD) spin-VCSELs, offer enhanced parameter controls permitting the effective, dynamical and ultrafast manipulation of their light emissions polarization. In the present contribution we investigate in detail the operation of QD spin-VCSELs subject to polarization modulation for their use as ultrafast light sources in optical communication systems. We reveal that QD spin-VCSELs outperform their QW counterparts in terms of modulation efficiency, yielding a nearly two-fold improvement. We also analyse the impact of key device parameters in QD spin-VCSELs (e.g. photon decay rate and intra-dot relaxation rate) on the large signal modulation performance with regard to optical modulation amplitude and eye-diagram opening penalty. We show that in addition to exhibiting enhanced polarization modulation performance for data rates up to 250Gbps, QD spin-VCSELs enable operation in dual (ground and excited state) emission thus allowing future exciting routes for multiplexing of information in optical communication links.

Recent technological improvements in vehicle manufacturing may greatly improve safety however, the individuals' driving behaviour still remains a factor of paramount importance with aggressiveness, lack of focus and carelessness being the main cause of the majority of traffic incidents. The imminent deployment of 5G networking infrastructure, paired with the advent of Fog computing and the establishment of the Internet of Things (IoT) as a reliable and cost-effective service delivery framework may provide the means for the deployment of an accurate driving monitoring solution which could be utilized to further understand the underlying reasons of peculiar road behaviour, as well as its correlation to the driver's physiological state, the vehicle condition and certain environmental parameters. This paper presents some of the fundamental attributes of Fog computing along with the functional requirements of a driving behaviour monitoring framework, followed by its high level architecture blueprint and the description of the prototype implementation process.

As road transportation has been identified as a major contributor of environmental pollution, motivating individuals to adopt a more eco-friendly driving style could have a substantial ecological as well as financial benefit. With gamification being an effective tool towards guiding targeted behavioural changes, the development of realistic frameworks delivering a high end user experience, becomes a topic of active research. This paper presents a series of enhancements introduced to an eco-driving gamification platform by the integration of additional wearable and vehicle-oriented sensing data sources, leading to a much more realistic evaluation of the context of a driving session.

Peer-to-peer (P2P) networking is a distributed application that partitions resources and tasks between equally privileged, equipotent peers. P2PSIP offers peer-to-peer session management without the need for centralized servers. The distributed nature of peer-to-peer networks introduces new challenges in terms of security. Attacks can target the structure and/or the functionality of the overlay network which is the cornerstone of a P2PSIP communication system. In this chapter, the most common types of attacks that the P2PSIP protocol is prone to, along with the respective countermeasures taken in the context of the protocol, are examined. Furthermore, we present some novel mechanisms that enhance the security strength of P2PSIP, while at the same time adapting its operation in distributed networking environments. We propose a formation and maintenance scheme for the P2PSIP RELOAD overlay network, using cryptographically protected messages between the peers that can be used either complimentary to or independently of the existing security mechanisms of P2PSIP.