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To increase the flexibility and the dynamism of communication networks, Software Defined Networking (SDN) has emerged as the challenging approach to decouple control and data planes, using a logically centralized controller able to manage the underlying network resources. However, traditional network solutions can not be always used in SDN. In this paper, we deal with routing issued in the setup of dynamic SDNs spanning Fog/Edge and IoT systems for the support of new generation applications. In particular, we propose a modified version of the Dijkstra's routing algorithm that can optimize complex routing metrics and uses MapReduce to speed up the configuration of routers in the network. The system can optimize the packet routing in according to different parameters including, e.g., hops, latency, and energy efficiency policies. In order to validate our work, we performed evaluations on the revised MapReduce version of the Dijkstra routing algorithm considering a high scalable network topology with thousands of virtual nodes.

Osmotic Computing represents a glue solution able to manage the deployment and orchestration of interconnected microelements across heterogeneous physical and virtual infrastructures (e.g., IoT, Edge and Cloud nodes) according to the behavior of hardware and software components during the time. The adoption of Osmotic Computing is challenging, but addressing networking issues is a key research topic due to the emergence of new problems in terms of QoS requirements. In this paper, we analyze how to exploit well-known networking solutions, such as the Dijkstra’s algorithm, and Big Data oriented technologies, such as the Hadoop and MapReduce, to provide efficient newtorking functionalities in Osmotic Computing. In particular, our objective is to minimize the routing path computation time in the software defined network (SDN) at the basis of microelement networking, as well as to ensure a global view and a high level of dynamism of our network topology. To accomplish this task, we process routing tables through a MapReduce based implementation of the Dijkstra’s algorithm whenever a topology change occurs, and we export routing results into the SDN. Our experimental results show that our networking strategy drastically reduces the best path computation time whenever the network of microelements is very large.

Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability. Gait evaluation was performed by Kinect v2 in a cohort of young participant affected by ataxia syndrome. The dataset is composed of the spatio-temporal parameters calculated by the skeleton acquired by the Kinect sensor, by the diagnosis of each participant, and by the total score of the clinical scale SARA. These parameters have been previously validated and corrected as requested by the Bland-Altman test.

The emergency we are experiencing due to the coronavirus infection is changing the role of technologies in our daily life. In particular, movements of persons need to be monitored or driven for avoiding gathering of people, especially in small environments. In this paper, we present an efficient and cost-effective indoor navigation system for driving people inside large smart buildings. Our solution takes advantage of an emerging short-range wireless communication technology – IoT-based Bluetooth Low Energy (BLE), and exploits BLE Beacons across the environment to provide mobile users equipped with a smartphone hints on how to arrive at the destination. The main scientific contribution of our work is a new proximity-based navigation system that identifies the user position according to information sent by Beacons, processes the best path for indoor navigation at the edge computing infrastructure, and provides it to the user through the smartphone. We provide some experimental results to test the communication system considering both the Received Signal Strength Indicator (RSSI) and the Mean Opinion Score (MOS).

Where shall my new shiny application run? Hundreds of such questions are asked by software engineers who have many cloud services at their disposition, but increasingly also many other hosting options around managed edge devices and fog spectrums, including for functions and container hosting (FaaS/CaaS). Especially for composite applications prevalent in this field, the combinatorial deployment space is exploding. We claim that a systematic and automated approach is unavoidable in order to scale functional decomposition applications further so that each hosting facility is fully exploited. To support engineers while they transition from cloud-native to continuum-native, we provide a rule-based matchmaker called RBMM that combines several decision factors typically present in software description formats and applies rules to them. Using the MaestroNG orchestrator and OsmoticToolkit, we also contribute an integration of the matchmaker into an actual deployment environment.

In the last century, the automotive industry has arguably transformed society, being one of the most complex, sophisticated, and technologically advanced industries. Autonomous vehicles (AVs) are a main concept in the future of Intelligent Transportation Systems (ITS) since they provide an increase in safety and road efficiency. One of the most critical aspects of managing AVs is their behavior in proximity of intersections. Several research centers are developing algorithms to solve the intersections management, trying to avoid collisions and traffic congestion. As well as, given that many of these interactions transmit sensitive data such as identification, position, and speed of the vehicle, a high level of security and privacy insurance is a prerequisite for broad acceptation of these communication systems. In this paper, in order to address the issues those issues we propose a system that combines blockchain technology effectively to support the communication and the transaction between vehicles. The combination between FRFP and blockchain allows us to verify if all the AVs have the same ledger version (e.g the same priority list) to cross the intersection without collisions; as well as, in case of inconsistencies to establish an emergency situation to avoid any collision.

The rapid development of Cloud, Edge, Fog Computing and Internet of Things (IoT) technologies has played a key role in the Industry 4.0 evolution. In this context, the Osmotic Computing paradigm, theorized in 2016 as integration between a centralized Cloud layer and Edge and/or IoT layers, has further emphasized the Industry 4.0 objectives including productivity and Quality of Services (QoS). This emerging paradigm proposes a new elastic management model of microservices, where deployment and migration strategies are strongly related to the underlaying infrastructure requirements (i.e., load balancing, reliability, availability, and so on) and applications (i.e., anomalies detection, awareness of the context, proximity, QoS, and so on). Specifically, knowing that an Osmotic application must have a failover behavior (highly horizontally/vertically scalable, 24 hours 24 available, fault-tolerant and secure), this paper highlights the Osmotic ecosystem platform focusing on the implementation of a blue-green mechanism for the fast re-deployment of microservices, exploiting emerging technologies, such as Docker, Kubernetes, Agento and MongoDB. Experiments shows the time required to arrange, deploy and destroy microservices.

In recent years, great attention has been given to new Internet of Things (IoT) technologies. The IoT concept is nowadays intrinsic to traditional products and services. With its rapid development, more and more small smart devices are connected over the Internet in order to monitor, collect and exchange data in real-time to provide smart IoT-as-a-Services (IoTaaS). A few years ago, IoT devices exclusively sent data to a centralized Cloud data center; today it is possible to perform "on board" processing tasks at the Edge of the network and subsequently share or use the obtained results closer to users. This paper, focusing on a smart grid scenario, investigates the possibility of creating an IoTaaS for smart metering, including a microservice for IoT devices capable of acquiring and processing electrical data using the Fast Fourier Transform (FFT) algorithm. In particular, we experimentally use the smart metering IoTaaS running on a Raspberry Pi 3 device to perform a harmonic analysis of a frequency signal of the domestic electrical grid in order to characterize the non-linear loads associated to the electronic devices (e.g., smart TV, computers, etc) with the purpose of monitoring their status and preventing possible malfunctions and faults.

This article proposes a novel cost-effective, robust, reliable and flexible infrastructureless IoT multi-hop Wireless Mesh Network (IoT-WMN) for Public Safety and Disaster Response (PSDR). The proposed system is able to auto-detect an Emergency Relief State (ERS) due to a disaster and to auto-configure itself in order to remain up and running, regardless of the disaster nature, to help victims to be timely rescued. To achieve this goal, these networks must be installed quickly and transparently for users, as victims cannot be expected to perform configuration operations or certain multi-hop-enabled software installed on their devices. in case of ERS detection, the system sets up ad hoc connections self-organizing links according to a tandem-based WMN topology and self-configuring access points (APs) for wireless devices (e.g., mobile phones of disaster victims). Devices connected to ad hoc APs become APs in turn, thus extending the network coverage. Available devices of different stockholders (e.g., municipality, first aid organizations, volunteer groups,...) are federated in a whole cooperating system, where each device works at the same time as node, gateway and router.

Nowadays, the rapid development of emerging Cloud, Fog, Edge, and Internet of Things (IoT) technologies has accelerated the advancement trends forcing applications and information systems (IS) to evolve. In this hybrid and distributed ecosystem, the management of service heterogeneity is complex, as well as, the service provisioning based on the classification and allocation of suitable computational resources remains a challenge. Osmotic Computing (OC), a new promising paradigm that allows the service migrations ensuring beneficial resource utilization within Cloud, Edge, and Fog Computing environments, was introduced as a potential solution to these issues. Driven by the needs of complex management mitigation, greater agility, flexibility and scalability, this paper aims to propose an innovative OC ecosystem leveraging Functions-as-a-Service (FaaS); there is also introduced the concept of hybrid architectural style combining both microservices and serverless architectures. Furthermore, to support the FaaS-based OC ecosystem, an osmotic flow model for video surveillance in smart cities is presented. To validate the functionality and assess the performance and to further improve the understanding of the usability of the OC flow in real-world applications, several experiments have been carried out.

In recent years, the rapid development of Cloud, Edge and Internet of Things (IoT) technologies has accelerated the advancement trends forcing applications and information systems (IS) to evolve. In this new ecosystem, ISs are federated and usually highly distributed becoming complex and very dynamic that have to extend not only through the Cloud/Edge and IoT layers but also the federated organizational boundaries. In this context, Osmotic Computing (OC) is a new paradigm driven by the significant increase in capacity / capability of resources in highly distributed and federated environments, that solves problems related to the deployment, networking and security of microservices called MicroElements (MEL) that are composed and interconnected over Cloud/Edge and IoT infrastructures with specified levels of QoS and security constraints. In this federated collaborative system, each organization needs to have proper administration and security policies to maintain data security while allowing selective sharing of resources. Classical models of access control are not effective in protecting resources while allowing users to access to the resources within their privileges. Blockchain is an underlying technology that could help organizations to improve access control systems through consensus mechanisms, and underlying features of immutability, transparency, auditability, and cryptography. In this work, we propose a MELs orchestration approach through a Software Defined Membrane (SDMem) that leverages Blockchain facilities obeying the osmosis principles.

Every year, traffic collisions have increased rapidly in proportion to the increase in the number of vehicles, especially at intersections. The main cause is human error in recognition and decision-making. Autonomous Vehicles (AVs) and Autonomous Intersection Management (AIM) systems represent emerging challenges. AVs can take a great deal of different actions when approaching an intersection. Several research centers are developing algorithms to solve one of the crucial aspects of autonomous driving, i.e the intersections management, trying to avoid collisions and traffic congestion. In this context, security is the main concern, due to the high exposure to data and information between Vehicle-to-Vehicle (V2V) and Vehicle-to-Intersection (V2I) communications. Blockchain and smart contracts, one of most promising technologies emerged in recent years, represent a possible solution for the existing security issues. Smart contracts are the orchestration and choreography protocols that facilitate, verify and negotiated agreement between the consenting parties participating in the Blockchain network. In this paper, we propose a Multi-Agent AIM (MA-AIM) system based on V2I/I2V communication to securely manage vehicles crossing though an intersections by leveraging Blockchain facilities. A central Intersection Manager Agent (IMA) is implemented at each intersection while each vehicle is controlled by a Driver Agent (DA).

The Internet of Medical Things (IoMT) is a sweeping revolution in the healthcare industry, with IoT quickly establishing itself as a critical part of modern healthcare. The rapid proliferation of such IoMT devices can bring limitations to the current Cloud-IoT centric infrastructures which are not designed to handle huge volumes and velocity of data generated. To address this problem, it is necessary to revisit the network architecture, pushing some data, processing and services directly on the edge nodes of the network where the data originates, away from the centralized Cloud. In this context, Osmotic Computing (OC) aims to provide a new paradigm for the integration between a centralized Cloud layer and Edge/IoT layers. The deployment and migration strategies through the Cloud and Edge layers depend on the infrastructures and applications requirements. This scientific work promotes the basic principles behind the OC paradigm and proposes a closed-loop OC flow model applied to a gamified cognitive rehabilitation use case. Moreover, the use case introduces the development of a customized virtual reality system based on a serious game which allows the patient to carry out physical and cognitive rehabilitation therapies using a natural user interface based on Microsoft Kinect. eas

Nowadays, thanks to new technologies, we are observing an explosion of data in different fields, from clinical to environmental. In such a scenario, a well-known problem in Big Data is represented by the efficient management e visualization in order to extract insights. The aim of this scientific work is to propose an innovative platform for managing the oceanographic acquisitions. More specifically, we present two innovative visualization techniques: general overview and site specific observation. Experiments highlight the goodness of our approach in terms both of performance and user experience.

Nowadays, the possibility of using social media in the healthcare domain is attracting the attention of many clinical professionals all around the world. In this panorama, many Healthcare Social Network (HSN) platforms are emerging with the purpose to enhance patient care and education. However, many clinical operators are reluctant to use them because they do not fulfil their requirements and are looking at the possibility to develop their own HSN platforms in order to perform social science studies. In this context, one of the major issue is the management of generated big data presenting a huge amount of relations and for this reason, traditional Relational Database management Systems (RDBMSs) are not adequate. The objective of this preliminary scientific work is to prove that a NoSQL graph DBMS can address such an issue, paving the way toward future social science studies. Experiments results show that Neo4j, i.e., one of the major NoSQL graph DBMS, simplifies the management of HSN data also guaranteeing acceptable performances in the perspective of future social science studies.

In recent years, the rapid growth of new Cloud technologies acted as an enabling factor for the adoption of microservices based architecture that leverages container virtualization in order to build modular and robust systems. As the number of containers running on hosts increases, it becomes essential to have tools to manage them in a simple, straightforward manner and with a high level of abstraction. Osmotic Computing is an emerging research field that studies the migration, deployment and optimization of microservices from the Cloud to Fog, Edge, and Internet of Things (IoT) environments. However, in order to achieve Osmotic Computing environments, connectivity issues have to be addressed. This paper investigates these connectivity issues leveraging different network overlays. In particular, we analyze the performance of four network overlays that are OVN, Calico, Weave, and Flannel. Our results give a concrete overview in terms of overhead and performances for each proposed overlay solution, helping us to understand which the best overlay solution is. Specifically, we deployed CoAP and FTP microservices which helped us to carry out these benchmarks and collect the results in terms of transfer times.

During the last decade, the healthcare topic has moved on the top of the development agenda not only for private organizations but also for public administrations. The information technology advances in the healthcare sector have designed an innovative model, the so-called eHealth, that leverages the Cloud Computing paradigm. Even more, with the medical devices (seen as IoT devices) proliferation, there have been introduced new challenges for the Cloud-IoT centric infrastructure. In this context, traditional Health Information Technology (HIT) systems present several limitations, such as scalability, fault tolerance, interoperability, data management and so on. Starting from the experience reported at ISASI-CNR (ME), a healthcare and research center, in this paper, we motivate the need to move the traditional HIT systems into innovative infrastructures based on the Osmotic Computing paradigm. In particular, we introduce two real uses cases, Ataxia and Dyslexia projects.