New Generation Of Services Research Articles

A Survey on Privacy of Personal and Non-Personal Data in B5G/6G Networks

The upcoming Beyond 5G (B5G) and 6G networks are expected to provide enhanced capabilities such as ultra-high data rates, dense connectivity, and high scalability. It opens many possibilities for a new generation of services driven by Artificial Intelligence (AI) and billions of interconnected smart devices. However, with this expected massive upgrade, the privacy of people, organisations, and states is becoming a rising concern. The recent introduction of privacy laws and regulations for personal and non-personal data signals that global awareness is emerging in the current privacy landscape. Yet, many gaps need to be identified in the case of two data types. If not detected, then they can lead to significant privacy leakages and attacks that will affect billions of people and organisations who utilise B5G/6G. This survey is a comprehensive study of personal and non-personal data privacy in B5G/6G to identify the current progress and future directions to ensure data privacy. We provide a detailed comparison of the two data types and a set of related privacy goals for B5G/6G. Next, we bring data privacy issues with possible solutions. This article also provides future directions to preserve personal and non-personal data privacy in future networks.

Security and Privacy Issues in IoT-Based Big Data Cloud Systems in a Digital Twin Scenario

Due to its unique type of services, Cloud Computing could operate as a “base technology” for other technologies; this attracts researchers to develop sustainable Cloud systems. It is a new generation of services that offers an opportunity for users to access and manage their information, applications, and data regardless of place and time. Nevertheless, there is a type of service that can include large amounts of data, called Big Data, and it consists of the rapid use of the Internet of Things (IoT) to produce large data sets. In this work, initially, we present Cloud Computing (CC) and Big Data (BD) exported from IoT, focusing on the security and management challenges of both. Notably, we combine the two aforementioned technologies to examine their related characteristics and discover new perspectives and opportunities for their integration and to achieve a sustainable environment called a Digital Twin scenario. Subsequently, we present how Cloud Computing contributes to IoT-based Big Data, aiming to fill a scientific gap in the sector of their integration regarding security and privacy. Finally, we additionally survey the security challenges of the integrated model of BD and CC and then propose a novel security algorithm for sustainable Cloud systems in a Digital Twin scenario. The experimental results presented are based on the use of the encryption algorithms AES, RC5, and RSA, and our proposed model extends the advances of CC and IoT-based BD, offering a highly novel and scalable service platform to achieve better privacy and security services.

Cognitive Load Balancing Approach for 6G MEC Serving IoT Mashups

The sixth generation (6G) of communication networks represents more of a revolution than an evolution of the previous generations, providing new directions and innovative approaches to face the network challenges of the future. A crucial aspect is to make the best use of available resources for the support of an entirely new generation of services. From this viewpoint, the Web of Things (WoT), which enables Things to become Web Things to chain, use and re-use in IoT mashups, allows interoperability among IoT platforms. At the same time, Multi-access Edge Computing (MEC) brings computing and data storage to the edge of the network, which creates the so-called distributed and collective edge intelligence. Such intelligence is created in order to deal with the huge amount of data to be collected, analyzed and processed, from real word contexts, such as smart cities, which are evolving into dynamic and networked systems of people and things. To better exploit this architecture, it is crucial to break monolithic applications into modular microservices, which can be executed independently. Here, we propose an approach based on complex network theory and two weighted and interdependent multiplex networks to address the Microservices-compliant Load Balancing (McLB) problem in MEC infrastructure. Our findings show that the multiplex network representation represents an extra dimension of analysis, allowing to capture the complexity in WoT mashup organization and its impact on the organizational aspect of MEC servers. The impact of this extracted knowledge on the cognitive organization of MEC is quantified, through the use of heuristics that are engineered to guarantee load balancing and, consequently, QoS.

Learning-Based Coordination Model for On-the-Fly Self-Composing Services Using Semantic Matching

Forecasts announce that the number of connected objects will exceed 20 billion by 2025. Objects, such as sensors, drones or autonomous cars participate in pervasive applications of various domains ranging from smart cities, quality of life, transportation, energy, business or entertainment. These inter-connected devices provide storage, computing and activation capabilities currently under-exploited. To this end, we defined “Spatial services”, a new generation of services seamlessly supporting users in their everyday life by providing information or specific actions. Spatial services leverage IoT, exploit devices capabilities (sensing, acting), the data they locally store at different time and geographic locations, and arise from the spontaneous interactions among those devices. Thanks to a learning-based coordination model, and without any pre-designed composition, reliable and pertinent spatial services dynamically and fully automatically arise from the self-composition of available services provided by connected devices. In this paper, we show how we extended our learning-based coordination model with semantic matching, enhancing syntactic self-composition with semantic reasoning. The implementation of our coordination model results in a learning-based semantic middleware. We validated our approach on various experiments: deployments of the middleware in various settings; instantiation of a specific scenario and various other case studies; experiments with hundreds of synthetic services; and specific experiments for setting up key learning parameters. We also show how the learning-based coordination model using semantic matching favours service composition, by exploiting three ontological constructions (is-a, isComposedOf, and equivalentTo), de facto removing the syntactic barrier preventing pertinent compositions to arise. Spatial services arise from the interactions of various objects, provide complex and highly adaptive services to users in seamless way, and are pertinent in a variety of domains such as smart cities or emergency situations.

Innovative technological advancements to improve cognitive and social skills of students with neurodevelopmental disorders

BACKGROUND: A major concern that is being increasingly addressed in modern educational environments is the ability to present equal accessibility opportunities to students with neurodevelopmental conditions and disorders as for typically developing children. OBJECTIVE: The main objective of the paper is to employ innovative technological advancements merged with evidence-based practices in order to teach, improve and generalise social skills for children with neurodevelopmental disorders, specifically children with High Functioning Autism (HFA) as well as children with Attention Deficit Disorder (ADD). METHODS: The development of a personalized solution adapted to the needs of each student is proposed. The platform will be composed of three main modules (Content Management, Emotional Analysis and Personalization). The target group is students of the Primary Years Program and Middle Years Program. EXPECTED RESULTS: Improved communicational and interactional capability of people with disabilities and facilitate social innovation; more affordable technologies and products that support interactions for people with disabilities, and new generation of services that are highly adaptable and personalisable to individual contexts. CONCLUSIONS: In order to achieve the optimum output/result of the system the procedure need to be implemented and reviewed by all involved parties.

Сloud Based IT Learning Infrastructure to Support New Generation of Services

Сloud Based IT Learning Infrastructure to Support New Generation of Services

Test Bed of Semantic Interaction of Smart Objects in the Web of Things

Semantic interaction in the Internet of Things (IoT) is an important concept within current IoT development, given that smart things require further autonomy with greater processing, storage, and communication capacities. The problem is now becoming one of how to get these things to interact and collaborate with each other; to form intelligent environments amongst themselves and thus generate better services for users. This article explores a solution approach that consists in providing collaborative behavior to smart things, through the incorporation of an ontology and an architecture. It makes possible things that can communicate and collaborate with each other, allowing the generation of new services of interaction according to user needs. For this task, a real test bed of smart things was created, in which the proposed solution was deployed (Smart Room). Finally, it was concluded that the creation of these types of test bed is feasible, taking into account that response times and the information delivered by the different managed processes are acceptable. New challenges were encountered, however, such as problems of critical region in test beds with conflicting services and management of multiple users.

Connecting the Persistent Identifier Ecosystem: Building the Technical and Human Infrastructure for Open Research

The persistent identifier (PID) landscape extends to cover objects, individuals and organisations engaged in the process of research. Established services such as DataCite, Crossref, ORCID and ISNI are providing a foundation for a trusted ecosystem and a new generation of services. Scalable identifier systems will support researchers and capture research activity in a holistic way, across the entire lifecycle. Challenges remain – siloed services are not interoperable; important types of objects are not adequately covered, many processes remain manual, and adoption, while strong, is not consistent across disciplines. This article draws on the work of the EU-funded THOR project to take stock of the current state of interoperability across the PID landscape and to discuss the next steps towards an integrated research record. Examples illustrate how this interconnectivity is facilitated technically, as well as social and human challenges in fostering adoption. User stories highlight how this network of persistent identifier services is facilitating good practice in open research and where its limitations lie.

The Queensland Health Rural Generalist Pathway: providing a medical workforce for the bush

Click here to hear an intoduction by the authorsIntroduction: Queensland Health's Rural Generalist Pathway is a supported career pathway for junior doctors to train in rural and remote medicine. The pathway joins evidence with policy to achieve professional recognition, credentialing, and industrial recognition.Methods: This article describes the principles underpinning the notion of rural generalism, the background to the establishment of the Rural Generalist Pathway in Queensland, Australia, how the pathway has been developed to meet the needs of Queensland's rural and remote communities, the implementation of the pathway, and the implications for other jurisdictions.Results: In 2007, 30 trainees commenced on the pathway, with total enrolment now of 182 in 2012. Trainees commence at the start of internship, completing their prevocational training component in postgraduate years 1 to 2. After prevocational certification they undertake advanced specialised training in a range of specialties, and then complete vocational training in a rural location, usually in their 4th to 5th postgraduate years. Trainees complete their general practice training through a Regional Training Provider, and achieve vocational registration by completion of appropriate fellowship assessment requirements. The pathway is managed by a geographically dispersed team of educators, clinicians and managers. The Rural Generalist team provide training and career advice, advocate for trainees and assist with negotiating posts. They map progress of trainees through the Vocational Indicative Planning process and arrange other educational activities including Rural Generalist workshops. Applications are often oversubscribed, with the intake growing to 41 in 2012, located at 10 intern training hospitals. In total 90 trainees have completed advanced specialised training as at the end of 2012.Conclusion: The Rural Generalist Pathway includes a challenging prevocational start to the career, the opportunity to specialise in a procedural skill or skills of interest and obtain general practice vocational training in a rural setting and appears to be proving an attractive choice for medical graduates seeking a challenging and varied career. Early evidence suggests that by recognizing and rewarding the worth of rural and remote practice, this strategy is creating its own supply line. From its initial roll-out in Queensland, rural generalist training continues to generate increased interest and enthusiasm across all Australian states and territories wishing to join this new wave of generalist practice. This new generation of health professionals for a new generation of services has the potential to provide the rural medical workforce the bush needs.Key words: Australia, generalism, pathway, Queensland, rural generalist, rural medical education, vocational training.

CRAB3: Establishing a new generation of services for distributed analysis at CMS

In CMS Computing the highest priorities for analysis tools are the improvement of the end users’ ability to produce and publish reliable samples and analysis results as well as a transition to a sustainable development and operations model. To achieve these goals CMS decided to incorporate analysis processing into the same framework as data and simulation processing. This strategy foresees that all workload tools (TierO, Tier1, production, analysis) share a common core with long term maintainability as well as the standardization of the operator interfaces. The re-engineered analysis workload manager, called CRAB3, makes use of newer technologies, such as RESTFul based web services and NoSQL Databases, aiming to increase the scalability and reliability of the system. As opposed to CRAB2, in CRAB3 all work is centrally injected and managed in a global queue. A pool of agents, which can be geographically distributed, consumes work from the central services serving the user tasks. The new architecture of CRAB substantially changes the deployment model and operations activities. In this paper we present the implementation of CRAB3, emphasizing how the new architecture improves the workflow automation and simplifies maintainability. In particular, we will highlight the impact of the new design on daily operations.

Telehealth: the hospital in your home

The traditional hospital-based service is beginning to change and services are beginning to be delivered through other, more modern, electronic methods. This paper outlines the new generation of services called ‘telehealth’ and suggests that the home is now becoming an extension of the hospital/GP surgery for many people with long-term conditions who are using telehealth devices to support and manage their conditions. The paper also provides a brief overview of other electronic services that are becoming established within the health field.

Assessment of high-performance smart metering for the web service enabled smart grid era (abstracts only)

The electricity network is undergoing a significant change towards a more adaptive, intelligent, self-managing, collaborative and information-driven grid. According to the smart grid vision, any electronic device connected to it will be able to communicate its consumed or produced energy almost in real time. Based on the analysis of this newly acquired information, a new generation of services and decision support systems can be realized, enabling more intelligent decisions, and ultimately a more efficient energy system. Therefore, high-performance acquisition of smart metering information from large scale distributed infrastructures is of key importance for the upcoming Internet-based enterprise services and mash-up applications. We have used open source software to build a web service-based advanced metering infrastructure of simulated smart meters, concentrators, and a smart metering platform, all interconnected via web services. We measure in a methodological fashion the performance of the various components of the architecture and evaluate their limitations. Finally we identify key performance indicators that need to be considered when deploying large-scale smart metering systems, and discuss on challenges and directions that arise.

A three-layered model to implement data privacy policies

An increasing number of business-to-business and business-to-customer services are accomplished by means of web technologies and mobile devices. As a consequence, sensitive data are continuously exposed to the risk of being delivered to final users or intermediary actors taking part to the data transactions, who could not have the proper access rights to obtain those data. These new generation of services are often characterized by high dynamism and untrustworthiness: existing technologies for managing and applying data privacy policies could be unsuccessful when dealing with this kind of contexts, as they could require too many resources, degrade the data quality to an unacceptable level, be too pervasive for data sources or data requestors. Moreover, industrial and research community is beginning to perceive the need to embed the mechanisms for preserving data privacy within the software product and process, as it comes to light from the recent literature. This paper proposes an approach to manage data privacy, inspired to the front-end trust filter paradigm, which aims at guaranteeing high flexibility, reducing the resources required, and limiting the pervasiveness into applications and devices involved into the data exchange. Our approach has the potential to curtail the change impact due to the dynamism and to foster the reuse of strategies, and their implementations, also across organizations.

Virtual, wireless mannah: a co-opetitive analysis of the broadband satellite industry

The emerging satellite communication constellations differ substantially from prior generations of systems. For years, satellite systems have offered broadcast and interactive services, but with major limitations. The new generation of services promise to overcome the traditional barriers, such as terminal weight and size, equipment and service cost, and degree of mobility. Instead, the new systems will provide completely new capabilities which expand the flexibility for the user and the range of potential applications. However, the introduction of such a “next-generation” communications system is often plagued by difficulties in forecasting market demand, as customer themselves may not accurately forecast their own needs for such services. Using the concept of “co-opetition” derived from game theory, we propose concrete steps which broadband satellite operators can use to foster market growth for these services.