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 $\mathbf{9 9. 9 9 9 \%}$.

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.

Function-as-a-Service (FaaS) is a serverless computing model that enables applications to be composed of self-contained functions triggered by events. The edge-cloud con-tinuum extends this paradigm by allowing function deployment closer to users and loT devices, reducing communication latency. However, large-scale FaaS deployment at the edge demands energy-efficient resource management to ensure cost reduction and sustainability. To address this challenge, we present$E^{2}FIS$: Energy-Efficient Function Invocation Scheduling, a framework that optimizes resource management and minimizes energy consumption in edge FaaS platforms.$E^{2}FIS$formulates function scheduling as a Mixed Integer Linear Programming (MILP) problem, minimizing energy consumption by consolidating work-loads while ensuring execution deadlines are met. Through simu-lations with real-world traces and experiments on the Serverledge FaaS platform,$E^{2}FIS$demonstrates to outperform the Earliest Deadline First (EDF) baseline, reducing energy consumption up to 92 % while maintaining timely function execution.

In the era of Smart Cities, video surveillance stands as a pivotal tool for enhancing urban security, optimizing resource management, and improving the quality of urban life. When video surveillance is seamlessly integrated with image analysis systems, raw visual data are transformed into actionable insights, significantly enhancing the capability of Smart Cities to ensure public safety and optimize urban operations. Image analysis systems mainly rely on the cloud: images are offloaded to a cloud infrastructure to be processed, analyzed and segmented for inference. The analysis of images in external systems, however, is not always recommended, due to privacy/security concerns, e.g., human action recognition. In this paper, we investigate the opportunity to adopt edge computing to implement such systems, where images are analyzed directly on-premises. To investigate the suitability of this approach, we carried out an extensive experimentation using two large-scale Fed4Fire+ testbeds, namely, Grid’5000 and Virtual Wall. Specifically, we considered different cloud-edge configurations using different inference models, and evaluated the impact of those models on performance and resource utilization. Based on these results, we provide a set of guidelines for the adoption of different models depending on the requirements of the specific application.

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.

Monitoring flash floods and providing just-in-time notification to city officials for taking appropriate action and prompt intervention is crucial for any smart city located in flood-prone areas around the world. Flood monitoring systems that exploit image analysis via Machine Learning (ML) techniques have been already proposed in literature. Such systems, however, adopt a cloud-based approach that generates significant data traffic and could be susceptible to failures due to network outages. In such a framework, images are continuously offloaded from cameras deployed in flood-prone areas of the city towards a cloud infrastructure where a service is deployed to analyze the images and detect the rise of water in rivers or city canals in a timely way. In this paper, we present the activities of the project EdgeFlooding, which aims at investigating the opportunity of adopting a distributed approach based on edge computing for the implementation of more resilient and reliable flash flood monitoring systems, that helps mitigate the limitations of the cloud-based systems. We have developed a prototype of an edge computing flood monitoring system based on micro-services, and we run an extensive set of experiments exploiting one European Fed4Fire+ testbed, i.e., the Grid'5000 testbed. The aim of those experiments is to assess whether a distributed edge/cloud computing approach is feasible for the implementation of future flood or environmental monitoring systems.

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.

The IETF is defining the 6TiSCH Architecture for the Industrial Internet of Things (IIoT) to provide low-latency, low jitter, and high-reliability communication. The 6TiSCH architecture identifies different ways to manage communication resources, namely static, centralized, autonomous, distributed, and hop-by-hop approaches. The distributed approach has gained more attention thanks to its capabilities of self-configuration and adaptation to different network conditions. In distributed scheduling, each node runs a Scheduling Function (SF) to dynamically compute the number of resources to allocate, and leverages the 6top protocol (6P) to negotiate them with its neighbors. In this paper, we focus on the distributed mode and provide an overview of our ongoing research activity on this topic.

Railways monitoring and control are currently performed by different heterogeneous vertical systems working in isolation without or with limited cooperation among them. Such configuration, widely adopted in practical deployments today, is in contrast with the integrated vision of systems that are at the foundation of the smart-city concept. In order to overcome the current fractured ecosystem that monitors and controls railways functionalities, the adoption of a novel integrated approach is mandatory to create an all-in-one railway system. To this aim, new IoT-based communication technologies, like wireless or Power Line Communication technologies, are considered the main enablers to integrate in a very rapid and easy manner existing vertical systems. In this work, we analyse the architecture of future railways systems based on a mix of wireless and Power Line Communication technologies. In our analysis, we aim at studying possible failure management strategies on rail-road switches to improve the level of reliability, crucial requirement for systems that demand maximum resiliency as they manage a critical function of the infrastructure. In particular, we propose a set of solutions aimed at detecting and handling network and sensor failures to ensure continuity in the execution of the basic control functions. The proposed approach is evaluated by means of simulations and demonstrated to be effective in ensuring a good level of performance even when failures occur.

The 6TiSCH architecture has been gaining attraction as a promising solution to ensure reliability and security for communication in applications for the Industrial Internet of Things (IIoT). While many different aspects of the architecture have been investigated in literature, an in-depth analysis of the security features included in its design is still missing. In this paper, we assess the security vulnerabilities of the 6top protocol, a core component of the 6TiSCH architecture for enabling network nodes to negotiate communication resources. Our analysis highlights two possible attacks against the 6top protocol that can impair network performance and reliability in a significant manner. To prove the feasibility of the attacks in practice, we implemented both of them on the Contiki-NG Operating System and tested their effectiveness on a simple deployment with three Zolertia RE-Mote sensor nodes. Also, we carried out a set of simulations using Cooja in order to assess their impact on larger networks. Our results show that both attacks reduce reliability in the overall network and increase energy consumption of the network nodes.

The IETF is currently defining the 6TiSCH architecture for the Industrial Internet of Things to ensure reliable and timely communication. 6TiSCH relies on the IEEE TSCH MAC protocol and defines different scheduling approaches for managing TSCH cells, including a distributed ( neighbor-to-neighbor ) scheduling scheme, where cells are allocated by nodes in a cooperative way. Each node leverages a Scheduling Function (SF) to compute the required number of cells, and the 6top (6P) protocol to negotiate them with neighbors. Currently, the Minimal Scheduling Function (MSF) is under consideration for standardization. However, multiple SFs are expected to be used in real deployments, in order to accommodate the requirements of different use cases. In this article, we carry out a comprehensive analysis of 6TiSCH distributed scheduling to assess its performance under realistic conditions. Firstly, we derive an analytical model to assess the 6P protocol, and we show that 6P transactions take a long time to complete and may also fail. Then, we evaluate the performance of MSF and other distributed SFs through simulations and real experiments. The results show that their performance is affected by the failure of 6P transactions and the instability of the routing protocol, which may lead to congestion from which the network is unable to recover. Finally, we propose a new SF (E-OTF) and show, through simulations and real experiments, that it can effectively improve the overall performance, by allowing nodes to quickly recover from congestion.

The IETF is currently defining the 6TiSCH architecture for the Industrial Internet of Things to provide reliable and timely communication. 6TiSCH includes a distributed management mode, in which network resources are computed autonomously by nodes and allocated in a cooperative way. Specifically, nodes use the 6top protocol to negotiate network resources with their neighbors. In this paper, we investigate the performance of 6top protocol through a set of experimental measurements on a testbed. We show that the time required to complete a 6top transaction in a real environment is not negligible, as often assumed in many studies. In addition, a significant percentage of 6top transactions fails, with a negative impact the performance of the application. We investigate the reasons for such failures and propose some guidelines to reduce their number.

The Internet of Things (IoT) is enabling a new generation of innovative services based on the seamless integration of smart objects into information systems. Such IoT devices generate an uninterrupted flow of information that can be transmitted through an untrusted network and stored on an untrusted infrastructure. The latter raises new security and privacy challenges that require novel cryptographic methods. Attribute-Based Encryption (ABE) is a new type of public-key encryption that enforces a fine-grained access control on encrypted data based on flexible access policies. The feasibility of ABE adoption in fully-fledged computing systems, i.e. smartphones or embedded systems, has been demonstrated in recent works. In this paper we assess the feasibility of the adoption of ABE in typical IoT constrained devices, characterized by limited capabilities in terms of computing, storage and power. Specifically, an implementation of three ABE schemes for ESP32, a low-cost popular platform to deploy IoT devices, is developed and evaluated in terms of encryption/decryption time and energy consumption. The performance evaluation shows that the adoption of ABE on constrained devices is feasible, although it has a cost that increases with the number of attributes. The analysis in particular highlights how ABE has a significant impact in the lifetime of battery-powered devices, which is impaired significantly when a high number of attributes is adopted.

The IEEE 802.15.4g standard is a wireless technology that can potentially enhance the capabilities of the Internet of Things. Originally conceived for Wireless Smart Utility Networks, it can be used in a number of potential application domains, both in urban and rural environments, as it provides low-power and low-cost communication over long distances, thus enabling Low-Power Wide Area Networks. In this paper, we show the results of a set of experiments carried out in real environments to measure the communication range in outdoor deployments. In our experiments, we used Zolertia remote sensor nodes and considered different scenarios, namely rural, semi-rural, and urban environments. The results obtained show that in the urban context, due to the presence of buildings, trees and other obstacles that prevent the signal propagation, the communication range is under 200m, while in a rural (open) environment it is possible to achieve longer distances, in the order of 800m.

The possibility of interconnecting any kind of device to the Internet is driving the adoption of the Internet of Things (IoT) paradigm also in a city environment. Many IoT applications are making the Smart City concept real, offering advanced services to citizens and city administrators. This evolution relies upon a seamless exchange of information among different systems. Exchanged data includes personal and/or critical information, thus requiring proper handling in order to avoid security and privacy issues. At the same time, recent developments in robotics are fostering the realization of autonomous agents (e.g., cars, buses, drones) that do not require human intervention. In the city of the future, many services will rely on autonomous agents. Also, autonomous agents (e.g., robots) will become more human alike, and will be able to show emotions. Therefore, they will replace humans in many city activities. In this paper, we first overview the expected evolution of IoT applications and, then, we briefly analyze the security, social, and ethical issues that are foreseen in a Smart City context.

Future Smart Cities will be enabled by a pervasive fabric of sensors and actuators, seamlessly integrated within information systems. This large-scale Internet of Things (IoT) will bring a new level of challenges to existing communication networks and wireless standards. In order to analyze these issues and study possible solutions, a quick and rapid experimentation is of paramount importance to ensure that IoT protocols and network architectures can handle such challenges. In this paper, we present the ECOAP project that aims at evaluating the performance of the Constrained Application Protocol (CoAP), the application protocol defined to interconnect IoT devices with information systems. The project will carry out an evaluation of CoAP through the WiSHFUL platform, a platform for large-scale experimentation of network systems. The project will focus on assessing different congestion control strategies in order to evaluate the scalability of the protocol in future large-scale scenarios.

The IETF 6TiSCH Working Group (WG) is currently standardizing a novel architecture to integrate IEEE 802.15.4e TSCH Wireless Networks into the Internet of Things. Within the proposed 6TiSCH architecture, a Scheduling Function (SF) is used to manage the allocation of communication resources (i.e., TSCH timeslots). Although many SFs have been proposed in literature, the 6 TiSCH WG is considering the On-The-Fly (OTF) Bandwidth Reservation Algorithm as the reference SF. In this paper, we carry out an extensive simulation analysis of OTF to evaluate if, in its current definition, it can ensure the low latency and high reliability requirements of critical applications targeted by TSCH. Specifically, we investigate how its performance is affected by the RPL protocol and the 6top protocol used for routing and distributed resource negotiation, respectively. Our results show that the OTF performance is significantly affected by (i) frequent changes in the preferred parent selected by RPL, and (ii) failures in resource negotiation. These events typically lead to congestion, from which the network can hardly recover. To overcome such limitations, we propose a modified version of the Bandwidth Reservation Algorithm, named Enhanced-OTF. We show that proposed modifications can effectively improve the overall network performance by allowing network nodes to recover from congestion in a short time.

Wireless Sensor Networks (WSNs) will represent a crucial enabling technology to interconnect sensors and actuators in future smart cities. Since many applications will demand for reliable and low-latency communication, current standardization efforts are focusing in the definition of novel wireless standard architectures, e.g., the 6TiSCH architecture, to improve reliability and introduce support for quality of service. In this paper, we evaluate the performance of the 6TiSCH architecture during the initial network formation. Specifically, the performance of the 6top protocol, defined in 6TiSCH for distributed negotiation of resources, is evaluated. Simulations highlighted how the initial negotiation of resources is influenced by the routing protocol and the link-quality estimation mechanism adopted. The performance evaluation allowed to draw a set of guidelines for network configuration to guarantee the reliability of the initial allocation of resources.