The increasing adoption of Internet of Things (IoT) devices and growing demand for real-time applications have driven a shift in the computation paradigm from Cloud computing toward Edge computing, giving rise to theCloud-to-Things Continuum (C2TC). Many real-time IoT applications involve Mobile Nodes (MNs), such as mobile robots or autonomous vehicles, which may join or leave the system dynamically. In addition, future reconfigurable IoT systems will be characterized by multiple applications with heterogeneous requirements dynamically deployed or removed on the same infrastructure. To support such environment, dynamic management mechanisms are needed to ensure that the requirements of different real-time applications are guaranteed despite frequent system reconfigurations (e.g., application deployment and removal). This paper proposes DJ-NECORA, an online algorithm for joint allocation of networking and computing resources in C2TC, capable of guaranteeing the requirements of real-time applications while efficiently managing system reconfigurations and a varying number of MNs. DJ-NECORA is evaluated via simulations in a realistic scenario against two state-of-the-art solutions and an Ideal algorithm. Results show that DJ-NECORA manages system reconfigurations efficiently, provides better Quality of Service (QoS), and performs close to the Ideal algorithm.

In Industrial IoT (IIoT) environments and especially for applications relying on Mobile Nodes (MNs), ensuring communication security is a critical requirement, in order to prevent attacks that aim to obtain sensitive data or compromise MNs. In this paper, we focus on the security of IIoT systems based on the 6TiSCH architecture defined by the IETF, in the presence of node mobility. We propose a method for provisioning key material to MNs, enabling the enforcement of a trade-off between security and overhead. Specifically, we consider three security settings, characterized by different security levels and communication/storage overhead. For each setting, we evaluate the impact on performance through simulation. Finally, we provide a set of guidelines to help network operators in the selection of the setting to use.

Critical industrial applications call for very stringent delay and high reliability requirements. To support them, even in the presence of Mobile Nodes (MNs), the 5G cellular technology provides the Ultra-Reliable Low-Latency Communications (URLLC) service class, which guarantees packet delivery with a maximum delay of a few ms and a reliability of 99.999%. In this paper, we investigate how to provide similar performance guarantees using IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) based on short-range wireless communication. To this aim, we propose an original resource scheduling algorithm, namely Enhanced Shared-Downstream Dedicated-Upstream (E-SD-DU). In addition, the paper provides the readers with the original contribution of an analytical model to determine the MNs that can be supported while satisfying the specified application requirements (and the related deployment cost). The obtained results show that our scheduling algorithm can guarantee a delay of $\mathbf{1 0 ~ m s}$ with a reliability of $\mathbf{9 9. 9 9 9 \%}$.

In recent years, Industrial IoT environments increasingly rely on a wide variety of applications with different performance requirements, such as real-time latency and ultra-high reliability. In this context, the Cloud-to-Things Continuum (C2TC) enables dynamic coordination of distributed computing resources from edge to cloud, offering a scalable approach to meet these demands. However, guaranteeing application-specific QoS in dynamic conditions remains challenging due to varying resource availability and application loads. The mobility of nodes further complicates the resource allocation process, as it affects the performance of both computing and networking resources. Additionally, system reconfiguration is needed in response to environmental changes or evolving application requirements to maintain the desired Quality of Service (QoS). This paper focuses on efficient resource allocation in C2TC-based IoT systems for real-time mobile applications and discusses ongoing research efforts in this domain.

The rapid proliferation of IoT devices and the increasing demand for real-time applications have driven a shift from traditional Cloud computing to Edge computing, giving rise to the Cloud-to-Things Continuum (C2TC). Many real-time IoT applications involve Mobile Nodes (MNs), such as autonomous vehicles and mobile robots, and require low-latency and high reliability. The optimal organization of the C2TC is crucial to meeting diverse application requirements while ensuring efficient resource allocation. In this paper, we analyze different C2TC configurations, leveraging multiple edge computing layers to optimize real-time application performance. We employ J-NECORA, an analytical tool designed to determine the optimal allocation of applications within C2TC at the design stage. Our findings demonstrate that the best allocation strategy depends on system-specific parameters, and J-NECORA effectively facilitates the comparison of different configurations, enabling informed decision-making.

The proliferation of loT devices and the growing demand for real-time applications have driven a shift in the computation paradigm, from Cloud computing to Edge computing, creating the Cloud-to-Things Continuum (C2TC). Many real-time loT applications involve Mobile Nodes (MNs), which may dynamically join or leave. In addition, in future reconfigurable loT systems, applications with different requirements will coexist, and will be dynamically introduced or removed. All this asks for dynamic management mechanisms to ensure the requirements of different real-time applications, even when the system configuration changes over time. In this paper, we propose DJ-NECORA, an online algorithm for the joint allocation of networking and computing resources in C2TC that is capable of guaranteeing the requirements of real-time applications and efficiently managing possible changes in the system configuration. We evaluated DJ-NECORA through simulation in a realistic scenario. The results show that DJ-NECORA effectively handles application dynamics and, in some scenarios, outperforms offline resource allocation solutions by supporting 14% more MNs.

In the Industrial Internet of Things (IIoT) landscape, where the cloud-to-things continuum (C2TC) paradigm is now a reality, industrial applications need to cope with highly heterogeneous network and computing resources. Moreover, many industrial applications also involve mobile nodes (MNs). Efficient allocation of network and computing resources to meet the stringent requirements of such applications is often a very challenging task. In this article, we propose joint network and computing resource allocation (J-NECORA), a comprehensive analytical framework to derive the optimal joint allocation of network and computing resources in the C2TC, that guarantees the application requirements, even in the presence of MNs. If the optimal allocation does not exist, J-NECORA provides a best effort allocation that minimizes the delay. The proposed framework is highly modular and flexible, and can be easily customized to different scenarios. We validated its effectiveness through simulation experiments, focusing on a specific use case. For the considered scenarios, the performance predicted by our framework matches quite closely the simulation results.

The Synchronized Single-hop Multiple Gateway (SHMG) framework has been recently proposed to support mobility in 6TiSCH, the network architecture defined by the IETF for the Industrial Internet of Things (IIoT). SHMG includes a scheduling policy to allocate communication resources to Mobile Nodes (MNs) in order to satisfy the stringent requirements of industrial applications. Current scheduling algorithms, however, manage mobility by simply over-allocating communication resources, without taking into account the position of MNs. In this paper, we propose a Location-Aware Scheduling Algorithm with Rescheduling (LASA-R) that leverages the position of MNs, reported via periodic Position Notification (PN) messages, to optimize the allocation of communication resources. LASA-R also includes a conflict resolution mechanism to modify the schedule, as conflicts are detected. Finally, a mathematical methodology is developed to determine the optimal PN period. LASA-R is assessed through simulations. The results obtained show that it can guarantee a high reliability and a bounded latency, even with a very large number of MNs.

Wireless Sensor and Actuator Networks (WSANs) are an effective technology for improving the efficiency and productivity in many industrial domains, and are also the building blocks for the Industrial Internet of Things (IIoT). To support this trend, the IEEE has defined the 802.5.4Time-Slotted Channel Hopping (TSCH)protocol. Unfortunately, TSCH does not provide any mechanism to manage node mobility, while many current industrial applications involve Mobile Nodes (MNs), e.g., mobile robots or wearable devices carried by workers. In this article, we present a framework to efficiently manage mobility in TSCH networks, by proposing an enhanced version of the Synchronized Single-hop Multiple Gateway (SHMG) architecture. We first define a flexible scheduling algorithm, calledShared Downstream-Dedicated Upstream (SD-DU), that can be configured to adapt to different types of traffic in industrial applications. Then, we develop a mathematical framework to formalize the problem of Border Routers (BRs) placement to guarantee the complete coverage of the deployment area, in the presence of obstacles and unreliable communication. A methodology for network sizing is also proposed to calculate the maximum number of MNs that can be supported by the network without violating the application requirements. Finally, we evaluate the performance of the proposed solutions, both analytically and through simulations. Our results show that the proposed enhancements allow a very effective management of node mobility, by providing mobility transparency without a significant impact on performance.

The Synchronized Single-hop Multiple Gateway (SHMG) is a framework recently proposed to support mobility into 6TiSCH, the standard network architecture defined for Industrial Internet of Things (IIoT) deployments. SHMG supports industrial applications with stringent requirements by adopting the Shared-Downstream Dedicated-Upstream (SD-DU) scheduling policy, which allocates to Mobile Nodes (MNs) a set of dedicated transmission opportunities for uplink data. Such allocation is performed on all the Border Routers (BRs) of the network without considering the location of MNs. Transmission opportunities are reserved also in BRs far from the current location of the MN, resulting in a waste of resources that limits the maximum number of nodes supported by the network. To overcome this problem, we propose a Location-Aware Scheduling Algorithm (LASA) that takes into account the position of MNs to build and maintain an efficient communication schedule. Specifically, LASA tries to prevent conflicts arising due to node mobility, in a preventive manner, so as to minimize packet dropping. We evaluate LASA via simulation experiments. Our results show that LASA allows to increase the number of MNs by more than four times, with respect to SD-DU, yet guaranteeing a Packet Delivery Ratio higher than 98%.

The Internet Engineering Task Force (IETF) has defined the 6TiSCH architecture to enable the Industrial Internet of Things (IIoT). While many industrial applications involve mobile devices (e.g., mobile robots or wearable devices carried by workers), 6TiSCH does not provide any mechanism to manage node mobility. However, recently, a Synchronized Single-hop Mul-tiple Gateway (SHMG) architecture has been proposed to allow an efficient management of mobile nodes in 6TiSCH networks. The SHMG architecture is quite flexible and can be customized to meet the requirements of different IIoT applications. However, find the appropriate configuration to guarantee the application requirements, may not be trivial. In this paper, we present Mobile6TiSCH, a simulation tool based on OMNeT ++, that implements the SHMG architecture. The proposed tool is general and allows to evaluate the Quality of Service (QoS) achieved by mobile nodes, in different scenarios. As such, it can be used to evaluate different solutions in a simulated environment before implementing them in practice. We describe the organization and implementation of Mobile6TiSCH and show the simulation results to display its effectiveness.

The Internet Engineering Task Force (IETF) has defined the 6TiSCH architecture to enable the Industrial Inter-net of Things (IIoT). Unfortunately, 6TiSCH does not provide mechanisms to manage node mobility, while many industrial applications involve mobile devices (e.g., mobile robots or wearable devices carried by workers). In this paper, we consider the Synchronized Single-hop Multiple Gateway framework to manage mobility in 6TiSCH networks. For this framework, we address the problem of positioning Border Routers in a deployment area, which is similar to the "Art Gallery" problem, proposing an efficient deployment policy for Border Routers based on geometrical rules. Moreover, we define a flexible Scheduling Function that can be easily adapted to meet the requirements of various IIoT applications. We analyze the considered Scheduling Function in different scenarios with varying traffic patterns, and define an algorithm for sizing the system in such a way to guarantee the application requirements. Finally, we investigate the impact of mobility on the performance of the system. Our results show that the proposed solutions allow to manage node mobility very effectively, and without significant impact on the performance.