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Background and objective: Telesurgery is as a promising solution to support and deliver advanced health care services to underserved areas. The primary endpoint of our study was to prove the concept of low-latency long-distance connectivity and to describe the feasibility of remote surgery. Methods: A prospective study was conducted from February 29 to March 1, 2024, in live animal models (porcine) connecting surgeons from Orlando (USA) to the animal laboratory in Shanghai (China) using 5G and Wi-Fi connections, in combination with continental and transpacific fiber. We performed ten radical nephrectomies and two partial nephrectomies in five animals using the MicroPort MedBot robotic platform. Intraoperative and telesurgery connection variables were reported with a descriptive statistical analysis. Key findings and limitations: No complications or conversions were reported. The mean animal weight was 38.2 (35–40) kg, the mean operative time was 32.7 (21–45) min, and the mean blood loss was 23.3 (20–30) ml. The mean latency was 296 (±50) ms. Findings from animal studies may not always translate directly to human outcomes. Conclusions and clinical implications: We described the feasibility of transpacific low-latency telesurgery in live porcine models with no intraoperative complications. Achieving optimal low-latency connectivity via telecommunication networks was essential for effectively performing the surgical procedures. However, we still need further investigation to achieve even lower latencies for human trials. We found that long-distance telesurgery is safe and feasible in animal models. However, it is a complex practice, and we still need further studies before translating these results to human trials. Patient summary: Our research has demonstrated the feasibility of low-latency long-distance telesurgery in live animal models. However, this type of telesurgery is a complex procedure, and further work is needed to translate these results to human trials.

The future of networking will be driven by the current emerging trends of combining the physical and virtual realities in cyberspace. Considering the ambient pandemic challenges, the role of virtual and augmented reality will definitely grow over time by transforming into the paradigm of the Metaverse of Things, where each person, thing or other entity will simultaneously exist within multiple synchronized realities. In this paper, we propose a novel framework for future metaverse applications composed of multiple synchronized data flows from multiple operators through multiple wearable devices and with different quality requirements. A new service quality model is proposed based on a customizable utility function for each individual data flow. The proposed approach is based on dynamic fine-grained data flow allocation and service selection using non-fungible tokens, which can be traded over the blockchain among users and operators in a decentralized mobile network environment.

It is widely expected that future networks of 6G and beyond will substantially improve on 5G. Technologies such as Internet of Skills and Industry 4.0 will become stable and viable, as a direct consequence of networks that offer sustained and reliable mobile performance levels. The primary challenges for future technologies are not just low-latency and high-bandwidth. The more critical problem Mobile Service Providers (MSPs) will face will be in balancing the inflated demands of network connections and customers’ trust in the network service. That is, being able to interconnect billions of unique devices while adhering to the agreed terms of Service Level Agreements (SLAs). To meet these targets, it is self-evident that MSPs cannot operate in a solitary environment. They must enable cooperation among themselves in a manner that ensures trust, both between themselves as well as with customers. In this study, we present the BEAT (Blockchain-Enabled Accountable and Transparent) Infrastructure Sharing architecture. BEAT exploits the inherent properties of permissioned type of distributed ledger technology (i.e., permissioned distributed ledgers) to deliver on accountability and transparency metrics whenever infrastructure needs to be shared between providers. We also propose a lightweight method that enables device-level accountability. BEAT has been designed to be deployable directly as only minor software upgrades to network devices such as routers. Our simulations on a resource-limited device show that BEAT adds only a few seconds of overhead processing time – with the latest state-of-the-art network devices, we can reasonably anticipate much lower overheads.

Cell selection in cellular networks is an important aspect that impacts the quality of service. The traditional cell selection mechanism is based on downlink received power. Despite the dense deployment of macrocells, mobile network operators are still confronting the daunting challenge of providing capacity and coverage. Deployment of a large number of small cells has emerged as a promising solution towards addressing this problem. However, this success expands the heterogeneous cellular networks where there is a significant disparity in the transmit power of the different base station types. Downlink and Uplink Decoupling (DUDe) can improve efficiency by associating the downlink cell based on the downlink received power and the uplink based on the pathloss. While the higher layer signalling has not been proposed in detail for the DUDe mechanism yet, we aim to propose a solution for the problem. This work addresses four different signalling mechanisms to realise decoupled up/downlinks connections in the radio access network for the next-generation communication systems with handling mobility. Our proposed signalling mechanisms cover uplink decoupling, downlink coupling, downlink decoupling, and uplink coupling scenarios. We analyse the proposed signalling mechanisms using ns3 simulation and present the impact of applying the DUDe mechanism, which mainly shows improvements for the uplink. For the selected mobility scenario, delay and lost packets are reduced by 30% and 26%, respectively. Delay and lost packets are reduced by 36% and 27% for the fix location scenario, respectively. The improvements imply that it reaches particular demand considering next-generation communication systems, with a massive number of smart devices demanding high quality of service requirements.

Mobile edge computing (MEC) is currently one of the key technologies that can facilitate the evolution of the future digitized economy. MEC can provide ubiquitous computational capabilities through the multitier deployment of servers to ensure lower latencies and tighter integration with 5G, the Internet of Things, blockchains and artificial intelligence. In this paper, we propose a new approach to optimizing hardware resource allocation for edge nodes in a multitier MEC hierarchy. In addition to a centralized unit, we consider active antenna units and distributed units equipped with edge nodes of different computational capacities. A parametric Bayesian optimizer is implemented for hardware resource allocation to increase the overall computational capacity of a 5G-based MEC system. Simulation results show that for given budget constraints, the proposed solution outperforms pseudorandom resource allocation in terms of the proportion of computational tasks completed. The achievable gains are in the range of 20-40 %, depending on the task complexity and selected budget threshold.

An important enabler of the Internet of Things (IoT) is the Narrow-Band Internet of Things (NB-IoT) technology, which is a 3GPP standards compliant connectivity solution. Quantum computing, another emerging technological paradigm, promises novel compute opportunities but is also able to compromise cybersecurity ciphers. Therefore, improved methods to mitigate such security threats are needed. In this research, we propose a location-aware cryptographic system that guarantees post-quantum IoT security. The ultimate value of a location-driven cryptosystem is to use the geographic location as a player’s identity and credential. Position-driven cryptography using lattices is efficient and lightweight, and it can be used to protect sensitive and confidential data in many critical situations that rely heavily on exchanging confidential data. At the best of our knowledge, this research starts the study of unconditional-quantum-resistant-location-driven cryptography by using the Lattice problem for the IoT in a pre-and post-quantum world. Unlike existing schemes, the proposed cryptosystem is the first secure and unrestricted position-based protocol that guards against any number of collusion attackers and against quantum attacks. It has a guaranteed authentication process, solves the problems of distributing public keys by removing a public key infrastructure (PKI), offers secure NB-IoT without SIM cards, and resists location spoofing attacks. Furthermore, it can be generalized to any network – not just NB-IoT.

Self-organized wireless networks based on unmanned aerial vehicles (UAVs) are receiving increasing attention due to their flexible deployment opportunities. Typically, UAVs are used as supplementary access points to existing ground infrastructure to extend network coverage and capacity. Therefore, finding the optimal position for each UAV is a crucial task that can be resolved by multiobjective optimization. In this paper, a self-organizing UAV swarm model is introduced as an evolutionary type of heuristic that can be adjusted in real time based on the network’s key performance indicators (KPIs). The exogenous dynamics of the wireless communication system are reflected by an end-user mobility model based on Ornstein-Uhlenbeck processes. To achieve versatility in the positioning of UAVs, a model of virtual forces is adopted to enable control of the movement of each UAV via a collection of persistent and mutable parameters of the system. Evolution is controlled by eleven strategic versions of parametric mutations, including a neutral benchmark process. The simulation results reveal that the suggested solution allows for a substantial increase in the KPI efficiency metrics relative to those of the nonmutated system. The results also addressed the presence of the Pareto front, where it is not possible to improve the selected KPIs without negatively affecting others. While existing research that focuses on evolutionary methods usually considers offline approaches, this work uses an online evolutionary approach that is able to solve the presented problem by taking the dynamic nature of the environment into account.

Wireless traffic produced by modern mobile devices displays high temporal and spatial dynamics as users spontaneously engage in collective applications where a significant portion of generated data remains localized. As a result, conventional service provisioning approaches may no longer be sufficient in beyond fifth generation (B5G) systems. The challenge of increased dynamics on the access networks can be mitigated with moving cells. However, the deployment time of these temporary serving entities may lag behind the service demand lifetime. Another viable solution to offload excessive cellular traffic is to rely upon locally available radio resources offered by user devices via direct mmWave-based mesh interworking. An important challenge in such systems is related to the incentivization of users to partake in collaborative resource sharing. To leverage multi-hop mesh capabilities, we propose the use of emerging blockchain technology that offers cryptographically-strong accounting while maintaining the anonymity of the participants. With system-level evaluations, we demonstrate that the utilization of mobile blockchain methods allows for a non-incremental improvement in the offloading gains. This demonstrates the potential of the outlined proposal for becoming a successful mechanism in the emerging B5G systems.

The Internet of Things (IoT) is an emerging networking paradigm connecting billions of devices securely to the Internet. Another emerging paradigm is quantum computing which - while opening new compute opportunities - was shown to jeopardise most cybersecurity protocols. In this study, we discuss techniques able to provide security in a post-quantum IoT. Specifically, we examine how the third-generation partnership project (3GPP) IoT security solutions fair in a post-quantum environment. Also, we analyse the security features of fifth-generation (5G) networks, propose improvements and discuss the manner in which a quantum computer can compromise security. Our results prove the existence of multiple vulnerabilities in the current IoT architecture and implementations. With advances in quantum computing having rendered the current security algorithms unsafe, more advanced techniques should be established to mitigate such risks. To this end, we present promising lattice-driven cryptographic techniques which we prove quantum resistance.

Consensus mechanisms are at the core of any Distributed Ledger Technology. They define how transactions are validated and verified, how the network resolves conflicts and protects against malicious intent, and how multiple devices on a distributed network with no central authority arrive at the same global view of the ledger. Experience with the consensus mechanisms employed in popular blockchain platforms have warranted years of research into more scalable and energy-efficient consensus mechanisms for a green society using constrained devices. Most of the “high-security” consensus mechanisms require the use of computational resources which are simply not available to devices with a constrained nature. Hence, the presence and activity of these devices do not contribute to the security of the ledger, irrespective of how numerous they are on the network. In this paper, we propose a novel consensus scheme, fully dependent on WiFi technology, suitable for constrained devices. Whilst in traditional Blockchain consensus mechanisms, constrained devices do not add to the security of the ledger, the security of our consensus mechanism increases with the number of connected devices.

The challenge of dynamic traffic demand in mobile networks is tackled by moving cells based on unmanned aerial vehicles. Considering the tremendous potential of unmanned aerial vehicles in the future, we propose a new heuristic algorithm for coverage optimization. The proposed algorithm is implemented based on a conditional generative adversarial neural network, with a unique multilayer sum-pooling loss function. To assess the performance of the proposed approach, we compare it with the optimal core-set algorithm and quasi-optimal spiral algorithm. Simulation results show that the proposed approach converges to the quasi-optimal solution with a negligible difference from the global optimum while maintaining a quadratic complexity regardless of the number of users.

The emergence of the Internet of Things (IoT) and the tactile internet presents high-quality connectivity strengthened by next-generation networking to cover a vast array of smart systems. Quantum computing is another powerful enabler of the next technological revolution, which will improve the world tremendously, and it will continue to grow to cover an extensive array of important functions, in addition to it receiving recently great interest in the scientific scene. Because quantum computers have the potential to overcome various issues related to traditional computing, major worldwide technical corporations are investing competitively in them. However, along with its novel potential, quantum computing is introducing threats to cybersecurity algorithms, as quantum computers are able to decipher many complex mathematical problems that classical computers cannot. This research paper proposes a robust and performance-effective lattice-driven cryptosystem in the context of face recognition that provides lightweight intelligent bio-latticed cryptography, which will aid in overcoming the cybersecurity challenges of smart world applications in the pre- and post-quantum era and with sixth-generation (6G) networks. Since facial features are symmetrically used to generate encryption keys on the fly without sending or storing private data, our proposal has the valuable attribute of dramatically combining symmetric and asymmetric cryptography operations in the proposed cryptosystem. Implementation-based evaluation results prove that the proposed protocol maintains high-performance in the context of delay, energy consumption, throughput and stability on cellular network topology in classical Narrowband-Internet of Things (NB-IoT) mode.

Tactile internet applications allow robotic devices to be remotely controlled over a communication medium with an unnoticeable time delay. In bilateral communication, the acceptable round trip latency is usually 1 ms up to 10 ms, depending on the application requirements. The communication network is estimated to generate 70% of the total latency, and master and slave devices produce the remaining 30%. Thus, this paper proposes a strategy to reduce 30% of the total latency produced by such devices. The strategy is to use FPGAs to minimize the execution time of device-associated algorithms. With this in mind, this work presents a new hardware reference model for modules that implement nonlinear positioning and force calculations and a tactile system formed by two robotic manipulators. In addition to presenting the implementation details, simulations and experimental tests are performed in order to validate the hardware proposed model. Results associated with the FPGA sampling rate, throughput, latency, and post-synthesis occupancy area are analyzed.

IEEE 802.11ah, a new amendment to the Wi-Fi standard, adapts Wi-Fi networks to the emerging Internet of Things (IoT). A key component of .11ah is the Restricted Access Window (RAW), a new channel access mechanism, which reduces contention when even thousands of IoT devices operate in the same area by assigning them different channel times. This paper shows that existing studies incorrectly understand the RAW behavior, oversimplify its modeling and thereby overestimate the real system throughput in several times, especially for short durations of the reserved RAW slots. The core contribution of this paper is a new mathematical model based on a completely different approach, which yields more accurate results and thereby enables better IoT system dimensioning. The developed model is suitable for many scenarios typical for IoT. It allows finding RAW parameters that optimize system performance in terms of throughput, power consumption, and packet loss ratio. The proposed solution is can be used for various traffic patterns: when each device transmits a single packet, a batch of packets of random size, or it has full-buffer traffic.

The Internet of Things (IoT) is a revolutionizing technology which aims to create an ecosystem of connected objects and embedded devices and provide ubiquitous connectivity between trillions of not only smart devices but also simple sensors and actuators. Although recent advancements in miniaturization of devices with higher computational capabilities and ultra-low power communication technologies have enabled the vast deployment of sensors and actuators everywhere, such an evolution calls for fundamental changes in hardware design, software, network architecture, data analytics, data storage, and power sources. A large portion of the IoT devices cannot be powered by batteries only anymore, as they will be installed in hard to reach areas and regular battery replacement and maintenance are infeasible. A viable solution is to scavenge and harvest energy from the environment and then provide enough energy to the devices to perform their operations. This will significantly increase the device life time and eliminate the need for the battery as an energy source. This survey aims at providing a comprehensive study on energy harvesting techniques as alternative and promising solutions to power the IoT devices. We present the main design challenges of the IoT devices in terms of energy and power and provide design considerations for a successful implementation of self-powered the IoT devices. We then specifically focus on piezoelectric energy harvesting as one of the most promising solutions to power the IoT devices and present the main challenges and research directions. We also shed lights on the hybrid energy harvesting for the IoT and security challenges of energy harvesting enabled the IoT systems.

The 3GPP standardization rapidly moves forward with studies of a wide-bandwidth waveform as well as an adaptation of the emerging 5G new radio (NR)-based access to the unlicensed spectrum (NR-U). One of the basic architectures for NR-U involves carrier aggregation of an anchor-licensed-NR carrier and a secondary carrier in unlicensed spectrum, which altogether allows for seamless traffic offloading in scenarios where multi-gigabit data rates are required. While today's research on NR-U addresses mostly physical- and protocol-layer aspects, a system-level performance of the NR-U offloading mechanisms has not been investigated thoroughly. In this paper, we develop a mathematical queuing-theoretic framework that is mindful of the specifics of millimeter-wave (mmWave) session dynamics and may serve as a flexible tool for the analysis of various strategies for the integrated use of licensed and unlicensed mmWave bands in terms of the session drop probability and system utilization. To illustrate this, we select three distinct strategies (based on sequential service, probabilistic offloading, or proportional splitting), and complement our mathematical models with a detailed performance evaluation in a representative massive augmented/virtual reality scenario. Based on this quantitative analysis of the selected schemes, we conclude that proportional splitting of traffic between the two mmWave bands leads to a better performance. We believe that the contributed mathematical analysis can become an important building block in further system development and service optimization across many usage scenarios.

Cellular operators have always relied on static deployments for providing wireless access. However, even the emerging fifth-generation (5G) networks may face difficulty in supporting the increased traffic demand with a rigid, fixed infrastructure without substantial over-provisioning. This is particularly true for spontaneous large-scale events that require service providers to augment the capacity of their networks quickly. Today, the use of aerial devices equipped with high-rate radio access capabilities has the potential to offer the much needed “on-demand” capacity boost. Conversely, it also threatens to rattle the long-standing business strategies of wireless operators, especially as the “gold rush” for cheaper millimeter wave (mmWave) spectrum lowers the market entry barriers. However, the intricate structure of this new market presently remains a mystery. This paper sheds light on competition and cooperation behavior of dissimilar aerial mmWave access suppliers, concurrently employing licensed and license-exempt frequency bands, by modeling a vertically differentiated market where customers have varying preferences in price and quality. To understand viable service provider strategies, we begin by constructing the Nash equilibrium for the initial market competition by employing the Bertrand and Cournot games. We then conduct a unique assessment of short-term market dynamics, where licensed-band service providers may cooperate to improve their competitive positions against the unlicensed-band counterparts intruding on the market. Our analysis studies the effects of various market interactions, price-driven demand evolution, and dynamic profit balance in this novel type of ecosystem.

The emerging Tactile Internet (TI) will enable control-oriented networks for remotely accessing or manipulating objects or devices. One major challenge in this context is how to achieve ultra-low-delay communication between the local operator and the remote object/device to guarantee the stability of the global control loop and to maximize the user's quality-of-experience (QoE). Being one of the major human-in-the-loop applications of the TI, haptic teleoperation inherits its delay-sensitive nature and requires the orchestration of communication and control approaches. In this paper, we focus on the radio access protocol, and its impact on the latency of wireless communication. We propose a novel soft resource reservation mechanism for the uplink scheduling of mobile networks that can significantly reduce the latency compared with the current legacy scheme. By leveraging the characteristics of teleoperation data traffic, and reserving resources accordingly, the proposed soft reservation scheme maintains the spectral efficiency while the human operator's QoE is improved. The simulation results confirm the efficiency of the proposed scheme.

A large number of new consumer and industrial applications are likely to change the classic operator's business models and provide a wide range of new markets to enter. This paper analyzes the most relevant 5G use cases that require ultra-low latency, from both technical and business perspectives. Low latency services pose challenging requirements to the network, and to fulfill them, operators need to invest in costly changes in their network. In this sense, it is not clear whether such investments are going to be amortized with these new business models. In light of this, specific applications and requirements are described and the potential market benefits for operators are analyzed. Conclusions show that the operators have clear opportunities to add value and position themselves strongly with the increasing number of services to be provided by 5G.

Narrowband-Internet of Things (NB-IoT) displays high-quality connectivity underpinned by fifth-generation (5G) networks to cover a wide array of IoT applications. The devices’ development and integration into different smart systems require permanent control, supervision, and the study of power consumption models to determine the performance of the network topology and allow for the measurement of the efficiency of the network topology’s application. This paper reports on an architecture and open-sourced simulation that was developed to study NB-IoT in Device-to-Device (D2D) mode, which includes the Physical (PHY), network, and application layers, as well as a queuing model, the model for uplink and downlink delays, the throughput, the overall NB-IoT D2D network performance, and the energy consumption based on the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. Our results prove that the suggested framework contributes to a reduction in power consumption, a minimization of queuing delays, a decrease in communication cost, a reduction in inter-cluster collisions, and the prevention of attacks from malicious nodes. Consequently, the framework manages the battery’s State of Charge (SOC), improves the battery’s State of Health (SOH), and maximizes the whole network lifetime. The proposed framework, the code of which has been open-sourced, can be effectively used for scientific research and development purposes to evaluate different parameters and improve the planning of NB-IoT networks.

The Internet of Things (IoT) will shortly be undergoing a major transformation from a sensor-driven paradigm to one that is heavily complemented by actuators, drones, and robots. The real-time situational awareness of such active systems requires sensed data to be transmitted in the uplink to edge-cloud, processed, and control instructions transmitted in the downlink. Since many of these applications will be mission critical, the most suitable connectivity family will be cellular due to the availability of licensed spectrum able to protect the offered communications service. However, while much focus in the past was on the uplink of machine-type communications, little attention has been paid to the end-to-end reliability, latency, and energy consumption comprising both up and downlinks. To address this gap, in this paper, we focus on the definition, design, and analysis of machine-type multicast service (MtMS). We discuss the different procedures that need to be redesigned for MtMS and we derive the most appropriate design drivers by analyzing different performance indicators, such as scalability, reliability, latency, and energy consumption. We also discuss the open issues to be considered in future research aimed at enhancing the capabilities of MtMS to support a wide variety of 5G IoT use cases.

The focus of this study is the optimal configuration of a wireless low-power duty-cycled network with respect to the minimal energy consumption. Precisely, the energy consumption of a truncated-ARQ scheme in realistic shadowing environments is examined for the reference IEEE 802.15.4e standard protocol and for its cooperative extension that is presented in the paper. We show how to choose between the direct or multihop forwarding and the cooperative version of the two. We determine the optimal forwarding strategy for both loose and strict reliability requirements. Low-power links are parametrised by the interdevice distance and the corresponding outage probability, for the fixed output transmission power. It is shown that significant amounts of energy can be saved when the most adequate scheme of the three is applied. All analytical results are validated in the network simulator ns-3.