Service-based Architecture Research Articles

Enhancing quality of life for the hearing-impaired: a holistic approach through the MoSIoT framework

AbstractThis article unveils MoSIoT (Modeling Scenarios of the Internet of Things), an innovative framework meticulously designed to simulate IoT systems, addressing the nuanced needs of individuals with hearing impairments. Grounded in the quality-of-life framework proposed by Verdugo et al., MoSIoT has been enriched and evolved to integrate and manage a spectrum of deafness technologies, thereby marking a significant enhancement in the overall quality of life for the affected individuals. The focal point of this work is the advocacy for accessibility and well-being through technology-driven and inclusive solutions. The presented case study provides a comprehensive insight into the transformative impact of MoSIoT, highlighting improvements in key quality of life dimensions such as “Interpersonal Relationships”, “Emotional Well-Being”, and “Personal Development”. These enhancements underscore the pivotal role of continuous innovation and inclusive design in the evolution of assistive technologies. The article delves into the intricacies of the system’s implementation, exploring its service-based architecture, which ensures modularity, scalability, and adaptability to diverse user needs and technological advancements. Furthermore, the potential for future research and development in this field is discussed, emphasizing the endless possibilities and avenues for enhancing assistive technology and promoting an inclusive and accessible future for individuals with disabilities.

Towards a quantum-safe 5G: Quantum Key Distribution in core networks

The Service-Based Architecture (SBA) of the fifth generation (5G) of cellular networks introduced great advancements in flexibility, efficiency, and performance of modern networks, thanks to the distribution and softwarization of core network entities called Network Functions (NFs). Due to the distributed nature of 5G systems, these NFs are usually located in different sites to provide better Quality of Service (QoS) or specific services, which poses a great challenge regarding security. However, even though the 3GPP standard identifies security requirements by leveraging Transport Layer Security (TLS) authentication and OAuth2.0 authorization, current experimental and commercial deployments often disregard these aspects for the sake of simplicity and performance. In fact, even though data and communication protection is crucial, the implementation of security protocols and mechanisms complicates the deployments and may reduce the efficiency of 5G systems. This paper presents a novel solution that implements TLS for authentication and encryption leveraging entanglement-based Quantum Key Distribution (QKD), ensuring that all the communications between NFs in the 5G core network are secured by QKD keys, and are therefore quantum-safe. Additionally, this paper presents a QKD key repository using the Network Repository Function (NRF), which stores and relays TLS session keys to authenticated consumer NFs to access producer NFs in a fast but quantum-safe process. The solution was validated in a real hardware environment, and obtained results demonstrate that the proposed solution enhances the security of the SBA communications in an efficient way, reducing an 85% the service request time compared to the traditional TLS-based procedure, as well as 29.96% fewer bytes transmitted throughout the process.

A service-based approach to cryoEM facility processing pipelines at eBIC.

Electron cryo-microscopy image-processing workflows are typically composed of elements that may, broadly speaking, be categorized as high-throughput workloads which transition to high-performance workloads as preprocessed data are aggregated. The high-throughput elements are of particular importance in the context of live processing, where an optimal response is highly coupled to the temporal profile of the data collection. In other words, each movie should be processed as quickly as possible at the earliest opportunity. The high level of disconnected parallelization in the high-throughput problem directly allows a completely scalable solution across a distributed computer system, with the only technical obstacle being an efficient and reliable implementation. The cloud computing frameworks primarily developed for the deployment of high-availability web applications provide an environment with a number of appealing features for such high-throughput processing tasks. Here, an implementation of an early-stage processing pipeline for electron cryotomography experiments using a service-based architecture deployed on a Kubernetes cluster is discussed in order to demonstrate the benefits of this approach and how it may be extended to scenarios of considerably increased complexity.

A Vulnerability Assessment of Open-Source Implementations of Fifth-Generation Core Network Functions

The paper presents an experimental security assessment within two widely used open-source 5G projects, namely Open5GS and OAI (Open-Air Interface). The examination concentrates on two network functions (NFs) that are externally exposed within the core network architecture, i.e., the Access and Mobility Management Function (AMF) and the Network Repository Function/Network Exposure Function (NRF/NEF) of the Service-Based Architecture (SBA). Focusing on the Service-Based Interface (SBI) of these exposed NFs, the analysis not only identifies potential security gaps but also underscores the crucial role of Mobile Network Operators (MNOs) in implementing robust security measures. Furthermore, given the shift towards Network Function Virtualization (NFV), this paper emphasizes the importance of secure development practices to enhance the integrity of 5G network functions. In essence, this paper underscores the significance of scrutinizing security vulnerabilities in open-source 5G projects, particularly within the core network’s SBI and externally exposed NFs. The research outcomes provide valuable insights for MNOs, enabling them to establish effective security measures and promote secure development practices to safeguard the integrity of 5G network functions. Additionally, the empirical investigation aids in identifying potential vulnerabilities in open-source 5G projects, paving the way for future enhancements and standard releases.

A web service-based architecture for virtual labs in academic institutions

Web service-based architecture for virtual labs is a cloud-based architecture that intended to be used in academic institutions as a reliable alternative for the existing physical labs. This study would try to come up with a systematic architecture that would present a good alternative for the current situation in labs of academic institutions. The scenario of the proposed solutions would include the client and server-side concerns related to the procedures and processes in the academic labs. This proposed model will adapt Ruby for programming the clients and the server side, SOAP as a message exchange standard that supports the service communication, WSDL as a service interface, and WS-BPEL to define service composition.

PP5GS—An Efficient Procedure-Based and Stateless Architecture for Next-Generation Core Networks

The introduction of the Service-Based Architecture (SBA) for the 5G Core Networks has drastically changed the way these networks are designed and operated. Aiming for higher flexibility and agility, the adoption of SBA is the first step towards cloud-native deployments of 5G Core. However, the high degree of functional decomposition in SBA has implications in terms of increased inter-NF signaling traffic during the execution of control plane procedures, as well as an increased complexity in orchestrating a system with tight inter-NF dependencies. In this work, we introduce PP5GS as a stateless 5G Core architecture that implements a procedure-based functional decomposition of the 5G Core NFs. We develop Per-Procedure NFs for four different control plane procedures and perform extensive evaluations in a private cloud environment orchestrated with Kubernetes. The results show that PP5GS requires up to 34% and 55% less computing resources compared to the baseline stateful and stateless systems, respectively, while generating at least 40% less signaling traffic. Moreover, complex control plane procedures can complete up to 50% faster. Lastly, the results show that PP5GS is a more feasible architecture in leveraging edge-offloading of 5G Core NFs.

CharM — Evaluating a model for characterizing service-based architectures

Service-based architecture is an approach that emerged to overcome software development challenges such as difficulty to scale, low productivity, and strong dependence between elements. Microservice, an architectural style that follows this approach, offers advantages such as scalability, agility, resilience, and reuse. This architectural style has been well accepted and used in industry and has been the target of several academic studies. However, analyzing the state-of-the-art and -practice, we can notice a fuzzy limit when trying to classify and characterize the architecture of service-based systems. Furthermore, it is possible to realize that it is difficult to analyze the trade-offs to make decisions regarding the design and evolution of this kind of system. Some concrete examples of these decisions are related to how big the services should be, how they communicate, and how the data should be divided/shared. Based on this context, we developed the CharM, a model for characterizing the architecture of service-based systems that adopts microservices guidelines. To achieve this goal, we followed the guidelines of the Design Science Research in five iterations, composed of an ad-hoc literature review, discussions with experts, two case studies, and a survey. As a contribution, the CharM is an easily understandable model that helps professionals with different profiles to understand, document, and maintain the architecture of service-based systems.

Service-Based Management Architecture for On-Demand Creation, Configuration, and Control of a Network Slice Subnet

Service-Based Management Architecture for On-Demand Creation, Configuration, and Control of a Network Slice Subnet

Modes and Models for Satellite Integration in 5G Networks

5G communication models, based on service-based architectures, network function virtualization, and separation between data and control planes move the attention to network capabilities and functions rather than physical resources. Consequently, 5G-based services can easily rely on satellites to optimize performance or broaden their scope, even transparently to end users. The 3GPP efforts reflect this cutting-edge trend by introducing Non-Terrestrial Network support (in particular satellite), since Rel-16. Nevertheless, the definition of the specific role of the satellite is in continuous evolution and scattered in different 3GPP specification documents, so that actual and future satellite involvement is not easily appreciable. Starting from the state-of-the-art of satellite-related 3GPP standardization and taking into account the outputs of some research projects, this article presents a unified view of the possible satellite integration options in 5G networks.

Improved Management of Issue Dependencies in Issue Trackers of Large Collaborative Projects

Issue trackers, such as Jira, have become the prevalent collaborative tools in software engineering for managing issues, such as requirements, development tasks, and software bugs. However, issue trackers inherently focus on the lifecycle of single issues, although issues have and express dependencies on other issues that constitute issue dependency networks in large complex collaborative projects. The objective of this study is to develop supportive solutions for the improved management of dependent issues in an issue tracker. This study follows the Design Science methodology, consisting of eliciting drawbacks and constructing and evaluating a solution and system. The study was carried out in the context of The Qt Company's Jira, which exemplifies an actively used, almost two-decade-old issue tracker with over 100,000 issues. The drawbacks capture how users operate with issue trackers to handle issue information in large, collaborative, and long-lived projects. The basis of the solution is to keep issues and dependencies as separate objects and automatically construct an issue graph. Dependency detections complement the issue graph by proposing missing dependencies, while consistency checks and diagnoses identify conflicting issue priorities and release assignments. Jira's plugin and service-based system architecture realize the functional and quality concerns of the system implementation. We show how to adopt the intelligent supporting techniques of an issue tracker in a complex use context and a large data-set. The solution considers an integrated and holistic system view, practical applicability and utility, and the practical characteristics of issue data, such as inherent incompleteness.

A Security Assessment of HTTP/2 Usage in 5G Service-Based Architecture

Fifth generation (5G) networks are designed to bring enhanced network operational efficiency to serve a wide range of emerging services. Toward this purpose, 5G adopts a service-based architecture (SBA) that features web-based technologies such as Hypertext Transfer Protocol version 2 (HTTP/2) used for signaling and application programming interfaces (APIs) for service delivery. Several works in the literature have reported that the shift toward the aforementioned technologies brings potential cybersecurity challenges to the 5G network. In this article, we discuss different security features introduced by 5G SBA and explore these security challenges and their solutions in this new architecture. We carefully examine HTTP/2 features, standards, and custom headers, and discuss their security implications in 5G SBA. We comment on the applicability of some known HTTP/2 attacks in 5G SBA in light of the standardized APIs, and discuss the security opportunities and research directions brought by this protocol and its related technologies.

Series Editorial: Mobile Communications and Networks

The evolution of mobile communication is taking 5G forward to achieve its target metrics, and at the same time, providing a sense of what would be possible with 6G. The evolution is enabled by both the advancements of the existing technology areas and the emergence of newer areas. This issue of the Mobile Communications and Networks Series presents seven different articles to the readers covering both emerging and existing areas. For example, the issue covers emerging topics like reconfigurable intelligent surface and edge intelligence. Similarly, advancements of a few existing topics are also covered, like near field communication for large-scale antenna array, network performance, security aspects of HTTP/2 in 5G service-based architecture, and open radio access network (O-RAN)-enabled heterogenous networks for enhanced video service. The intention is to meet the needs of wider interest groups with the outcome of concurrent research on mobile communication taking place all over the world.

An Information System Supporting Insurance Use Cases by Automated Anomaly Detection

The increasing availability of vast quantities of data from various sources significantly impacts the insurance industry, although this industry has always been data driven. It accelerates manual processes and enables new products or business models. On the other hand, it also burdens insurance analysts and other users that need to cope with this development parallel to other global changes. A novel information system (IS) for artificial intelligence (AI)-supported big data analysis, introduced within this paper, shall help to overcome user overload and to empower human data analysts in the insurance industry. The IS research’s focus lies neither in novel algorithms nor datasets but in concepts that combine AI and big data analysis for synergies, such as usability enhancements. For this purpose, this paper systematically designs and implements an AI2VIS4BigData reference model to help information systems conform to automatically detect anomalies and increase its users’ confidence and efficiency. Practical relevance is assured by an interview with an insurance analyst to verify the demand for the developed system and derive all requirements from two insurance industry user stories. A core contribution is the introduction of the IS. Another significant contribution is an extension of the AI2VIS4BigData service-based architecture and user interface (UI) concept on AI and machine learning (ML)-based user empowerment and data transformation. The implemented prototype was applied to synthetic data to enable the evaluation of the system. The quantitative and qualitative evaluations confirm the system’s usability and applicability to the insurance domain yet reveal the need for improvements toward bigger quantities of data and further evaluations with a more extensive user group.

Random-Delay-Corrected Deep Reinforcement Learning Framework for Real-World Online Closed-Loop Network Automation

The future mobile communication networks (beyond 5th generation (5G)) are evolving toward the service-based architecture where network functions are fine-grained, thereby meeting the dynamic requirements of diverse and differentiated vertical applications. Consequently, the complexity of network management becomes higher, and artificial intelligence (AI) technologies can improve AI-native network automation with their ability to solve complex problems. Specifically, deep reinforcement learning (DRL) technologies are considered the key to intelligent network automation with a feedback mechanism similar to that of online closed-loop architecture. However, the 0-delay assumptions of the standard Markov decision process (MDP) of traditional DRL algorithms cannot directly be adopted into real-world networks because there exist random delays between the agent and the environment that will affect the performance significantly. To address this problem, this paper proposes a random-delay-corrected framework. We first abstract the scenario and model it as a partial history-dependent MDP (PH-MDP), and prove that it can be transformed to be the standard MDP solved by the traditional DRL algorithms. Then, we propose a random-delay-corrected DRL framework with a forward model and a delay-corrected trajectory sampling to obtain samples by continuous interactions to train the agent. Finally, we propose a delayed-deep-Q-network (delayed-DQN) algorithm based on the framework. For the evaluation, we develop a real-world cloud-native 5G core network prototype whose management architecture follows an online closed-loop mechanism. A use case on the top of the prototype namely delayed-DQN-enabled access and mobility management function (AMF) scaling is implemented for specific evaluations. Several experiments are designed and the results show that our proposed methodologies perform better in the random-delayed networks than other methods (e.g., the standard DQN algorithm).

Design and Validation of an Open Source Cloud Native Mobile Network

Network technologies are embracing the cloud-native paradigm, following the current best practices in cloud computing. Cloud-native technologies might be applied to different types of network functions in a mobile network, but they are particularly relevant nowadays for core network functions, as the recent standard introduces the service-based architecture that matches modern cloud-native technologies such as Docker and Kubernetes. In parallel, a number of open source software initiatives already provide researchers and practitioners with usable software that implements the key functionality of a mobile network (for both LTE and 5G). These software solutions, however, are monolithic and not integrated into state-of-the-art cloud-native frameworks. In this article, we fill this gap by describing the implementation of a cloud-native mobile network, which supports channel emulation and provides an affordable and scalable way of testing orchestration algorithms with standardized VIM interfaces. Our experimental evaluation shows the applicability of our solution, which is released as open source and illustrates its flexibility.

A Novel Machine Learning-Based Scheme for Spectrum Sharing in Virtualized 5G Networks

Network virtualization allows the coexistence of multiple network slices over a shared physical infrastructure, each delivering a service with own requirements in terms of quality of service, coverage, and time span. Spectrum is an expensive commodity, so it must be managed among these slices in the most efficient way. However, current spectrum sharing techniques are too rigid to address all combinations of service requirements and properly exploit the new air interface flexibility and network deployment options introduced by the Fifth Generation (5G) mobile networks. In this paper, we extend the state of the art first by proposing a novel spectrum sharing scheme that supports an unlimited number of radio networks. Second, we propose a 5G compliant novel service-based network management architecture to integrate Machine Learning (ML) algorithms for Radio Resource Management (RRM), including spectrum sharing. Finally, we propose a new three-stage ML framework that exploits forecasting, clustering and reinforcement learning algorithms to implement the proposed spectrum sharing scheme. Our proposed solution can allow an arbitrary number of 5G network slices to share spectrum more effectively and more dynamically either with each other or with other radio networks.

Improving datacenter utilization through containerized service-based architecture

The modern datacenter's computing capabilities have far outstripped the applications running within and have become a hidden cost of doing business due to how software is architected and deployed. Resources are over-allocated to monolithic applications that sit idle for large parts of the day. If applications were architected and deployed differently, shared services could be used for multiple applications as needed. When combined with powerful orchestration software, containerized microservices can both deploy and dynamically scale applications from very small to very large within moments—scaling the application not only across a single datacenter but across all datacenters where the application(s) are deployed.In this paper, we analyze data from an application(s) deployed both as a single monolithic codebase and as a containerized application using microservice-based architecture to calculate the performance and computing resource waste are both architected and deployed. A modern approach is offered as a solution as a path from how to go from a monolithic codebase to a more efficient, reliable, scalable, and less costly deployment model.

Cognitive intelligence based 6G distributed network architecture

5G is envisioned to guarantee high transmission rate, ultra-low latency, high reliability and massive connections. To satisfy the above requirements, the 5G architecture is designed with the properties of using service-based architecture, cloud-native oriented, adopting IT-based API interfaces and introduction of the Network Repository Function. However, with the wide commercialization of 5G network and the exploration towards 6G, the 5G architecture exposes the disadvantages of high architecture complexity, difficult inter-interface communication, low cognitive capability, bad instantaneity, and deficient intelligence. To overcome these limitations, this paper investigates 6G network architecture, and proposes a cognitive intelligence based distributed 6G network architecture. This architecture consists of a physical network layer and an intelligent decision layer. The two layers coordinate through flexible service interfaces, supporting function decoupling and joint evolution of intelligence services and network services. With the above design, the proposed 6G architecture can be updated autonomously to deal with the future unpredicted complex services.

Industrial IoT in 5G-and-Beyond Networks: Vision, Architecture, and Design Trends

Cellular networks are envisioned to be a cornerstone in future industrial Internet of Things (IIoT) wireless connectivity in terms of fulfilling the industrial-grade coverage, capacity, robustness, and timeliness requirements. This vision has led to the design of vertical-centric service-based architecture of 5G radio access and core networks. The design incorporates the capabilities to include 5G-AI-Edge ecosystem for computing, intelligence, and flexible deployment and integration options (e.g., centralized and distributed, physical, and virtual) while eliminating the privacy/security concerns of mission-critical systems. In this article, driven by the industrial interest in enabling large-scale wireless IIoT deployments for operational agility, flexible, and cost-efficient production, we present the state-of-the-art 5G architecture, transformative technologies, and recent design trends, which we also selectively supplemented with new results. We also identify several research challenges in these promising design trends that beyond-5G systems must overcome to support rapidly unfolding transition in creating value-centric industrial wireless networks.

ML-SLD: A message-level stateless design for cloud-native 5G core network

The Internet of Things (IoTs) has become an essential component of the 5th Generation (5G) network and beyond, accelerating the transition to digital society. The increasing signaling traffic generated by billions of IoT devices has placed significant strain on the 5G Core network (5GC) control plane. To address this issue, the 3rd Generation Partnership Project (3GPP) first proposed a Service-Based Architecture (SBA), intending to create a flexible, scalable, and agile cloud-native 5GC. However, considering the coupling of protocol states and functions, there are still many challenges to fully utilize the benefits of the cloud computing and orchestrate the 5GC in a cloud-native manner. We propose a Message-Level StateLess Design (ML-SLD) to provide a cloud-native 5GC from an architectural standpoint in this paper. Firstly, we propose an innovative mechanism for servitization of the N2 interface to maintain the connection between Radio Access Network (RAN) and the 5GC, avoiding interruptions and dropouts of large-scale user data. Furthermore, we propose an On-demand Message Forwarding (OMF) algorithm to reduce the impact of cloud fluctuations on the performance of cloud-native 5GC. Finally, we create a prototype that is based on the OpenAirInterface (OAI) 5G core network projects, with all Network Functions (NFs) packaged in dockers and deployed in a kubernetes-based cloud environment. Several experiments have been built with UERANSIM and Chaosblade simulation tools. The findings demonstrate the viability and efficiency of our proposed methods.