Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved

Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved

Facilitating mmWave Mesh Reliability in PPDR Scenarios Utilizing Artificial Intelligence

The use of advanced AR/VR applications may benefit the efficiency of collaborative public protection and disaster relief (PPDR) missions by providing better situational awareness and deeper real-time immersion. The resultant bandwidth-hungry traffic calls for the use of capable millimeter-wave (mmWave) radio technologies, which are however susceptible to link blockage phenomena. The latter may significantly reduce the network reliability and thus degrade the performance of PPDR applications. Efficient mmWave-based mesh topologies need to, therefore, be constructed that employ advanced multi-connectivity mechanisms to improve the levels of connectivity. This work conceptualizes predictive blockage avoidance by leveraging emerging artificial intelligence (AI) capabilities. In particular, AI-aided blockage prediction permits the mesh network to reconfigure itself by establishing alternative connections proactively, thus reducing the chances of a harmful link interruption. An illustrative scenario related to a fire suppression mission is then addressed by demonstrating that the proposed approach dramatically improves the connection reliability in dynamic mmWave-based deployments.publishedVersionPeer reviewe

Priority-based Coexistence of eMBB and URLLC Traffic in Industrial 5G NR Deployments

One of the most attractive use-cases for the 5G mobile cellular system is industrial automation. To this end, the newly standardized New Radio (NR) technology offers the support of both ultra-reliable low-latency (URLLC) service and conventional enhanced mobile broadband (eMBB) service. Owning to extreme latency and reliability requirements, URLLC service needs to be provided an explicit prioritization. We consider the simultaneous support of these two services in an industrial environment, where manufacturing machinery utilizes URLLC service for motion control and synchronous operation while eMBB service is used for remote monitoring. By utilizing the tools of stochastic geometry and queuing theory, we formalize the model with preemptive priority service at NR base stations (BS). The considered key performance indicator is the density of NR BS. Our numerical results indicate that the proposed approach does provide perfect isolation for URLLC traffic even in a dynamically changing environment and the required reliability level for a given load may indeed be attained by the proper selection of NR BS density and NR BS antenna arrays.acceptedVersionPeer reviewe

Augmented Computing at the Edge Using Named Data Networking

Edge computing is considered vital to IoT evolution, enabling the timely execution of various computational tasks for constrained devices utilizing external resources. The conventional host-based network architectures become a bottleneck for further development of edge computing, primarily when serving latencysensitive applications. Further, existing approaches do not exploit complex data correlations in the network layer for optimization. This paper demonstrates that Named Data Networking (NDN) has the potential to enable efficient support for mobile users offloading their time-sensitive computing tasks to edge servers. For this purpose, the NDN protocol was enhanced with a server selection procedure, capable of adjusting for the varying resource availability on edge servers. The results of the experiments show clear support for using NDN in these scenarios, with individual gains coming not just from Interest aggregation and caching, which are NDN features, but also from dynamic server selection.acceptedVersionPeer reviewe

Performance of Priority-Based Traffic Coexistence Strategies in 5G mmWave Industrial Deployments

Recently standardized New Radio (NR) technology supports both ultra-reliable low-latency (URLLC) service and conventional enhanced mobile broadband (eMBB) service. Owing to extreme latency and reliability requirements an explicit prioritization needs to be provided to URLLC service when these traffic types are mixed up at the air interface. In this work, we consider simultaneous support of these two services in an industrial environment, where production line equipment utilizes URLLC service for reorganization and synchronous operation while eMBB service is used for remote monitoring. By utilizing the tools of stochastic geometry and queuing theory, we formalize the model with pre-emptive priority service at NR base station (BS) with and without direct device-to-device (D2D) communications. Our numerical results indicate that the priority-based implementation of URLLC and eMBB coexistence allows us to isolate the former traffic efficiently and requires no external control. D2D-aware strategy, where the BS explicitly reserves some resources for direct communications, drastically outperforms those, where no explicit reservation is utilized, as well as the baseline strategy where all the traffic goes through the BS. This strategy can achieve 10−5 of URLLC drop probability when the baseline strategy produces just 5\times 10^-3 , leading to three orders of magnitude reduction in drop probability and without significant impact produced on eMBB session drop probability. The developed model can be utilized to estimate the NR BS density required to support prescribed performance guarantees for all the considered strategies.publishedVersionPeer reviewe

Applying blockchain technology for user incentivization in mmWave-Based mesh networks

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.publishedVersionPeer reviewe

Performance of Priority-Based Traffic Coexistence Strategies in 5G mmWave Industrial Deployments

Recently standardized New Radio (NR) technology supports both ultra-reliable low-latency (URLLC) service and conventional enhanced mobile broadband (eMBB) service. Owing to extreme latency and reliability requirements an explicit prioritization needs to be provided to URLLC service when these traffic types are mixed up at the air interface. In this work, we consider simultaneous support of these two services in an industrial environment, where production line equipment utilizes URLLC service for reorganization and synchronous operation while eMBB service is used for remote monitoring. By utilizing the tools of stochastic geometry and queuing theory, we formalize the model with pre-emptive priority service at NR base station (BS) with and without direct device-to-device (D2D) communications. Our numerical results indicate that the priority-based implementation of URLLC and eMBB coexistence allows us to isolate the former traffic efficiently and requires no external control. D2D-aware strategy, where the BS explicitly reserves some resources for direct communications, drastically outperforms those, where no explicit reservation is utilized, as well as the baseline strategy where all the traffic goes through the BS. This strategy can achieve 10−5 of URLLC drop probability when the baseline strategy produces just 5\times 10^-3 , leading to three orders of magnitude reduction in drop probability and without significant impact produced on eMBB session drop probability. The developed model can be utilized to estimate the NR BS density required to support prescribed performance guarantees for all the considered strategies

Characterizing throughput and convergence time in dynamic multi-connectivity 5G deployments

Fifth-generation (5G) mobile communications are expected to integrate multiple radio access technologies (RATs) within a unified access network by allowing the user equipment (UE) to utilize them concurrently. As a consequence, mobile users face even more heterogeneous connectivity options, which creates challenges for efficient decision-making when selecting a network dynamically. In this work, with the tools of queuing theory, integral geometry, and optimization theory, we develop a novel mobility-centric analytical methodology for multi-RAT deployments. Particularly, we first contribute a framework for optimal data rate allocation in the network-assisted regime. Then, we characterize the convergence time of the distributed optimization algorithms based on reinforcement learning to reduce the signaling overheads. Our findings suggest that network-assisted strategies may improve the UE throughput by up to 60% depending on the considered deployment, where the gains increase with a higher density of millimeter-wave New Radio (NR) base stations. A user-centric solution based on reinforcement learning mechanisms is capable of approaching the performance of the network-assisted scheme. However, the associated convergence time may be prohibitive, on the order of several minutes. To improve the latter, we further propose and evaluate a transfer learning-based algorithm that allows to decrease the convergence time by up to 10 times, thus becoming a simple solution for rate-optimized operation in future 5G NR deployments.publishedVersionPeer reviewe

Characterizing Resource Allocation Trade-Offs in 5G NR Serving Multicast and Unicast Traffic

The use of highly directional antenna radiation patterns for both the access point (AP) and the user equipment (UE) in the emerging millimeter-wave (mmWave)-based New Radio (NR) systems is inherently beneficial for unicast transmissions by providing an extension of the coverage range and eventually resulting in lower required NR AP densities. On the other hand, efficient resource utilization for serving multicast sessions demands narrower antenna directivities, which yields a trade-off between these two types of traffic that eventually affects the system deployment choices. In this work, with the tools from queuing theory and stochastic geometry, we develop an analytical framework capturing both the distance- and traffic-related aspects of the NR AP serving a mixture of multicast and unicast traffic. Our numerical results indicate that the service process of unicast sessions is severely compromised when (i) the fraction of unicast sessions is significant, (ii) the spatial session arrival intensity is high, or (iii) the service time of the multicast sessions is longer than that of the unicast sessions. To balance the multicast and unicast session drop probabilities, an explicit prioritization is required. Furthermore, for a given fraction of multicast sessions, lower antenna directivity at the NR AP characterized by a smaller NR AP inter-site distance (ISD) leads to a better performance in terms of multicast and unicast session drop probabilities. Aiming to increase the ISD, while also maintaining the drop probability at the target level, the serving of multicast sessions is possible over the unicast mechanisms, but it results in worse performance for the practical NR AP antenna configurations. However, this approach may become feasible as arrays with higher numbers of antenna elements begin to be available. Our developed mathematical framework can be employed to estimate the parameters of the NR AP when handling a mixture of multicast and unicast sessions as well as drive a lower bound on the density of the NR APs, which is needed to serve a certain mixture of multicast and unicast traffic types with their target performance requirements.acceptedVersionPeer reviewe