In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the ...movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform.
Due to the fast advancement of Internet technology, the popularity of Online Social Networks (OSN) over the Internet is increasing day by day. In the modern world, people are using OSN to communicate ...with others around the world who may or may not know each other. OSN has become the most convenient means to transmit media (news/content) and gather or spread information in the world. The posts (contents) on OSN affect and impact people, and minds at least for some time. These contents are important because they play a crucial role in taking the decision. The posts which are available on the OSN may be information or just misinformation. The misinformation may be a type of fake news or rumour. This is very difficult for people to differentiate whether the posts are information or rumour. Therefore, the development of techniques that can prevent the transmission of false information or rumours that might harm society in any way is critical. In this paper, a model is developed based on the epidemic approach, for examining and controlling fake information dissemination in OSN. The proposed model illustrates how different misinformation debunking measures impact and how misinformation spreads among different groups. In this article, we explain that the proposed model will be able to recognize and eradicate fake news from OSN. The model is written as a system of differential equations. Its equilibrium and stability are also carefully examined. The basic reproduction number ( R 0 ) is calculated, which is an important parameter in the study of message propagation in OSN. If R 0 < 1, the propagation of rumor in the OSN will be minimal; nevertheless, if R 0 > 1, the fake information/rumor will continue in OSN. The effects of disinformation of rumours in OSN in the real world are explored. In addition, the model covers the fake information/rumour dissemination control mechanism. The comparative study shows that the proposed model provides a better mechanism to prevent the dissemination of fake information in OSN in comparison to other previous models. Extensive theoretical study and computation analysis have also been used to validate the proposed model.
Nowadays, the growing global economy and demand for customized products are bringing the manufacturing industry from a sellers' market toward a buyers' market. In this context, the smart ...manufacturing enabled by Industry 4.0 is changing the whole production cycle of companies specialized on different kinds of products. On one hand, the advent of cloud computing and social media makes the customers' experience more and more inclusive, whereas on the other hand cyber-physical system technologies help industries to change in real time the cycle of production according to customers' needs. In this context, "retention" marketing strategies aimed not only at the acquisition of new customers but also at the profitability of existing ones allow industries to apply specific production strategies so as to maximize their revenues. This is possible by means of the analysis of various kinds of information coming from customers, products, purchases, and so on. In this paper, we focus on customer loyalty programs. In particular, we propose cloud-based software as a service architecture that store and analyses big data related to purchases and products' ranks in order to provide customers a list of recommended products. Experiments focus on a prototype of human to machine workflow for the pre-selection of customers deployed on both private and hybrid cloud scenarios.
Machine and deep learning techniques are fuelling a revolution in the health domain and are attracting the interest of many cross-disciplinary research groups all over the world ...
The malware spreading in Wireless Sensor Network (WSN) has lately attracted the attention of many researchers as a hot problem in nonlinear systems. WSN is a collection of sensor nodes that ...communicate with each other wirelessly. These nodes are linked in a decentralised and distributed structure, allowing for efficient data collection and communication. Due to their decentralised architecture and limited resources, WSN is vulnerable to security risks, including malware attacks. Malware can attack sensor nodes, causing them to malfunction and consume more energy. These attacks can spread from one infected node to others in the network, making it essential to protect WSN against malware attacks. In this paper, we focus on the analysis of a novel fractional epidemiology model, specifically the fractional order SEIVR epidemic model in the sense of Caputo's fractional derivative of order <inline-formula> <tex-math notation="LaTeX">0{ < {\alpha }{\leq }}1 </tex-math></inline-formula> with the goal of examining the efficacy of vaccination strategies and the heterogeneity of a scale-free network on epidemic spreading. First, using the next-generation technique and obtain the basic reproduction number of the proposed epidemic model, which is essential for determining both the locally asymptotically stable equilibrium point of the worm-free system and the unique existence of the endemic equilibrium point. To numerically solve the model, the Adam-Bashforth-Moulton predictor-corrector (ABM) method is applied. The fractional calculus enables us to deal directly with the "memory effect" of numerous phenomena, taking into account the system's dependence on previous stages. This method provides the results of a complex system. Additionally, research demonstrates that vaccine treatments are quite effective at preventing the spread of malware. The outcome of the study reveals that the applied ABM predictor-corrector method is computationally strong and effective to analyse fractional order dynamical systems in the SEIVR epidemic model for malware propagation in WSN. The results show that the order of the fractional derivative has a significant effect on the dynamic process. Also, from the result, it is obvious that the memory effect is zero for <inline-formula> <tex-math notation="LaTeX">{\alpha } </tex-math></inline-formula> = 1. When the fractional order <inline-formula> <tex-math notation="LaTeX">{\alpha } </tex-math></inline-formula> is decreased from 1, the memory effect appears, and its dynamics vary according to the time. This memory effect points out the difference between derivatives of fractional and integer orders. The theorems and their proofs are presented to validate the validity of the proposed model. To validate the proposed model, extensive theoretical study and computational analysis have also been applied.
With reference to the MeSmart project, the Municipality of Messina is making a great investments to deploy several types of cameras and digital devices across the city for carrying out different ...tasks related to mobility management, such as traffic flow monitoring, number plate recognition, video surveillance etc. To this aim, exploiting specific devices for each task increases infrastructure and management costs, reducing flexibility. On the contrary, using general-purpose devices customized to accomplish multiple tasks at the same time can be a more efficient solution. Another important approach that can improve the efficiency of mobility services is moving computation tasks at the Edge of the managed system instead of in remote centralized serves, so reducing delays in event detection and processing and making the system more scalable. In this paper, we investigate the adoption of Edge devices connected to high-resolution cameras to create a general-purpose solution for performing different tasks. In particular, we use the Function as a Service (FaaS) paradigm to easily configure the Edge device and set up new services. The key results of our work is deploying versatile, scalable and adaptable systems able to respond to smart city’s needs, even if such needs change over time. We tested the proposed solution setting up a vehicle counting solution based on OpenCV, and automatically deploying necessary functions into an Edge device. From experimental results, it results that computing performance at the Edge overtakes the performance of a device specifically designed for vehicle counting under certain conditions and thanks to our reconfigurable functions.
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.
Modern legal proceedings heavily rely on digital evidence as a basis for decisions in a variety of contexts, including criminal investigations and civil lawsuits. However, factors like data ...alteration, unauthorised access, or flaws in centralised storage can threaten the security and integrity of digital evidence. We suggest a decentralised methodology for using smart contracts to safeguard digital evidence in order to overcome these issues. The decentralised model makes use of smart contracts and blockchain technology to guarantee the integrity, transparency, and immutability of digital evidence. The approach does not require a centralised authority because it makes use of a distributed ledger, which lowers the possibility of data loss or manipulation. Multiple parties participating in the evidence lifecycle can build confidence and accountability thanks to smart contracts' programmable rules and automated enforcement mechanisms. In our study, we show the decentralised model's architecture and describe its essential elements, such as the blockchain network, smart contracts, and decentralised storage. We go over the advantages of employing this architecture, including enhanced auditability, decreased dependency on centralised institutions, and increased data security. Additionally, we discuss potential difficulties and constraints, like scalability and interoperability. We run a few simulations and experiments to test the suggested model's viability and effectiveness while comparing it to conventional centralised methods. The outcomes show that our decentralised paradigm offers improved security for digital evidence, guaranteeing its reliability, usability, and tamper-proofness. We also go through how the model is used in actual legal systems, law enforcement organisations, and digital forensics investigations.
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).
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