Local edge computing for radiological image reconstruction and computer-assisted detection: A feasibility study

Computational requirements for data processing at different stages of the radiology value chain are increasing. Cone beam computed tomography (CBCT) is a diagnostic imaging technique used in dental and extremity imaging, involving a highly demanding image reconstruction task. In turn, artificial intelligence (AI) assisted diagnostics are becoming increasingly popular, thus increasing the use of computation resources. Furthermore, the need for fully independent imaging units outside radiology departments and with remotely performed diagnostics emphasize the need for wireless connectivity between the imaging unit and hospital infrastructure. In this feasibility study, we propose an approach based on a distributed edge-cloud computing platform, consisting of small-scale local edge nodes, edge servers with traditional cloud resources to perform data processing tasks in radiology. We are interested in the use of local computing resources with Graphics Processing Units (GPUs), in our case Jetson Xavier NX, for hosting the algorithms for two use-cases, namely image reconstruction in cone beam computed tomography and AI-assisted cancer detection from mammographic images. Particularly, we wanted to determine the technical requirements for local edge computing platform for these two tasks and whether CBCT image reconstruction and breast cancer detection tasks are possible in a diagnostically acceptable time frame. We validated the use-cases and the proposed edge computing platform in two stages. First, the algorithms were validated use-case-wise by comparing the computing performance of the edge nodes against a reference setup (regular workstation). Second, we performed qualitative evaluation on the edge computing platform by running the algorithms as nanoservices. Our results, obtained through real-life prototyping, indicate that it is possible and technically feasible to run both reconstruction and AI-assisted image analysis functions in a diagnostically acceptable computing time. Furthermore, based on the qualitative evaluation, we confirmed that the local edge computing capacity can be scaled up and down during runtime by adding or removing edge devices without the need for manual reconfigurations. We also found all previously implemented software components to be transferable as such. Overall, the results are promising and help in developing future applications, e.g., in mobile imaging scenarios, where such a platform is beneficial

Secure edge services for future smart environments

Abstract The recent developments in communications technologies, such as Internet of Things (IoT) and 5G together with various enabling technologies, will lead us to the next major transition in terms of accessing digital services. For example, one of such transition is the availability of gadget-free services for the users from nearby smart environment and can be termed as ‘gadget-free hyperconnected world’. Similarly, Industry 4.0 is another major digital transformation that ensures the intelligence, digitization and automation in the various industrial applications. Such smart environment applications set strict requirements in terms of low-latency along with scalability, security and privacy. The edge computing is required if low-latency requirements exist, in order to avoid latency overhead from routing to a centralized (cloud) server. For the success of this vision, it is highly important to place suitable and strong security solutions in the edge-based smart environment to ensure the overall security. This thesis contributes to two different use cases from the context of smart environment, i) smart healthcare environment, ii) smart home construction and proposes novel contributions to improvement of security for edge based smart IoT applications. Firstly, biometrics-based anonymous and lightweight authentication schemes were developed for the single and multiple gadget-free users in smart IoT healthcare environment. The compliance of the security schemes is proven through performance evaluations and by analysing the security properties. Second, a conceptual security mechanism was formulated for three-tier IoT edge architectures to ensure secure smart node bootstrapping and user’s service accessibility mechanisms. The performance evaluation of the proposed IoT edge architecture is evaluated to assess the feasibility of the system. Finally, edge computing and blockchain integrated IIoT framework ‘BlockEdge’ is proposed for the smart home construction use case. The feasibility of the approach is verified by evaluating the performance and resource-efficiency of BlockEdge in terms of latency, power consumption and network load. Furthermore, this thesis also investigates the potential security requirements, challenges and their solutions for the BlockEdge based IIoT framework.Tiivistelmä Viestintäteknologian viimeaikainen kehitys mm. esineiden internetin (IoT, Internet of Things) ja 5G teknologioiden alueella on johtamassa seuraavaan keskeiseen siirtymävaiheeseen digitaalisten palvelujen käytön kannalta. Esimerkkinä tästä on päätelaitteettomien (gadget free) palvelujen saatavuus älykkäissä ympäristöissä, jota voidaan myös kutsua päätelaitevapaaksi verkostoituneeksi ympäristöksi. Industry 4.0 on puolestaan toinen merkittävä muutosprosessi, jota toteutetaan lisätyn älykkyyden, digitalisoinnin ja automaation erilaisten teollisten sovellusten edesauttamana. Tällaiset älykkäiden ympäristöjen sovellukset edellyttävät matalaa viivettä, suurta skaalautuvuutta, tietoturvaa ja yksityisyydensuojaa. Reunalaskentaa tarvitaan mm. matalan viiveen vaatimusten täyttämiseen, mm. välttämällä tarpeetonta reititystä keskitettyihin (pilvi)palvelimiin. Tämän vision onnistumisen kannalta on erittäin tärkeää sijoittaa sopivia ja vahvoja tietoturvaratkaisuja reunalaskentapohjaiseen älykkääseen ympäristöön kokonaisturvallisuuden varmistamiseksi. Tässä väitöskirjatyössä on tutkittu kahta erilaista älykkäisiin ympäristöihin sijoittuvaa käyttötapausta i) älykästä terveydenhuoltoympäristöä ja ii) älykästä rakentamista, ja ehdotetaan miten reunapohjaisten älykkäiden IoT-sovellusten tietoturvaa voidaan parantaa tällaisissa ympäristöissä. Ensiksi työssä kehitettiin biometriikkaan perustuvat anonyymit ja kevyet todennusjärjestelmät yhden ja usean päätelaitevapaan käyttäjän tarpeisiin älykkäiden IoT terveydenhuoltopalvelujen mahdollistamiseksi. Tietoturvaratkaisujen soveltuvuus on todennettu arvioimalla turvallisuusominaisuuksia ja järjestelmän suorituskykyä. Toiseksi, työssä on kehitetty tietoturvamekanismi kolmitasoineen IoT reunalaskenta-arkkitehtuuriin, jolla voidaan mahdollistaa käyttäjän turvallinen liittyminen palveluihin. Ehdotetun IoT reunalaskenta-arkkitehtuurin suorituskykyä mitattiin järjestelmän käyttökelpoisuuden arvioimiseksi. Lopuksi reunalaskenta ja lohkoketjut on integroitu työssä esitettyyn ”BlockEdge”-konseptiin teollisen internetin (IIoT) viitekehyksessä, jota voidaan hyödyntää mm. älykkään rakentamisen palvelujen rakentamisessa. Työssä arvioidaan ratkaisun käyttökelpoisuutta suorituskyvyn ja resurssitehokkuuden, viiveiden, energiakulutuksen sekä verkkoliikenteen suhteen. Lisäksi työssä arvioidaan kyseisten ratkaisujen tietoturvavaatimuksia, haasteita ja niiden ratkaisuja

Securing edge services for future smart healthcare and industrial IoT applications

Abstract Secure and intelligent environments are crucial for fostering future IoT applications such as digital healthcare and Industry 4.0. Such smart environments must enable needed digital services to the respective users ubiquitously and fulfill critical requirements such as ensuring security, privacy, and low latency. This paper summarizes the dissertation work [1] through three major contributions, i) a lightweight biometrics-based user authentication mechanism in the smart and gadget-less healthcare environment, ii) a conceptual three-tier mechanism for secure nodes bootstrapping and secure users access for digital services, and iii) a Blockchain and Edge computing based network architecture for IIoT use case to fulfill the needed requirements such as low-latency, trust management, and security among others. The performance evaluation of the proposed framework is carried out, and the obtained results highlight valuable insight of this work for enabling a secure future hyperconnected environment for various applications

Resource-aware dynamic service deployment for Local IoT edge computing:healthcare use case

Abstract Edge Computing is a novel computing paradigm moving server resources closer to end-devices. In the context of IoT, Edge Computing is a centric technology for enabling reliable, context-aware and low-latency services for several application areas such as smart healthcare, smart industry and smart cities. In our previous work, we have proposed a three-tier IoT Edge architecture and a virtual decentralized service platform based on lightweight microservices, called nanoservices, running on it. Together, these proposals form a basis for virtualizing the available local computational capacity and utilizing it to provide localized resource-efficient IoT services based on the applications’ need. Furthermore, locally-deployed functions are resilient to access network problems and can limit the propagation of sensitive user data for improved privacy. In this paper, we propose an automatic service and resource discovery mechanism for efficient on-the-fly deployment of nanoservices on local IoT nodes. As use case, we have selected a healthcare remote monitoring scenario, which requires high service reliability and availability in a highly dynamic environment. Based on the selected use case, we propose a real-world prototype implementation of the proposed mechanism on Raspberry Pi platform. We evaluate the performance and resource-efficiency of the proposed resource matching function with two alternative deployment approaches: containerized and non-containerized deployment. The results show that the containerized deployment is more resource-efficient, while the resource discovery and matching process takes approximately 6–17 seconds, where containerization adds only 1–1.5 seconds. This can be considered a feasible price for streamlined service management, scalability, resource-efficiency and fault-tolerance

Identity privacy preserving biometric based authentication scheme for Naked healthcare environment

Abstract Recent developments in Internet of Things (IoT) technologies have already put a huge impact on the medical and health sector. Thus, the patient treatment can be performed in more efficient ways compared with traditional methods. Secure identification is a key system requirement for patients to acquire these health related services. Fast and convenient identification is important in the case of critical and elderly or disabled patients who required frequent health services. In this paper, we are presenting concept of the Naked environment where patients can get health services from smart and intelligent surroundings of hospital without using explicit gadgets. Patients would have direct interaction with the environment and get identified through it. We propose a biometric based authentication scheme for the Naked hospital environment that also protects the patients identity privacy. In addition, we show that this authentication scheme can resist various well known attacks such as insider attacks, replay attacks and identity privacy among others

Performance and efficiency optimization of multi-layer IoT edge architecture

Abstract The recent IoT applications set strict requirements in terms of latency, scalability, security and privacy. The current IoT systems, where computation is done at data centers, provide typically very high computational and storage capacity but long routes between computational capacity and sensors/actuators make them unsuitable for latency-critical applications and services. Mobile Edge Computing (MEC) can address these problems by bringing computational capacity within or next to the base stations of access networks. Furthermore, to cope with access network problems, the capability of providing the most critical processes at the local network layer is also important. Therefore, in this paper, we compare the traditional cloud-IoT model, a MEC-based edge-cloud-IoT model, and a local edge-cloud-IoT model with respect to their performance and efficiency, using iFogSim simulator. The results complement our previous findings that utilizing the three-tier edge-IoT architecture, capable of optimally utilizing the computational capacity of each of the three tiers, is an effective measure to reduce energy consumption, improve end-to-end latency and minimize operational costs in latency-critical IoT applications

Distributed network and service architecture for future digital healthcare

According to World Health Organization (WHO), the worldwide prevalence of chronic diseases increases fast and new threats, such as Covid-19 pandemic, continue to emerge, while the aging population continues decaying the dependency ratio. These challenges will cause a huge pressure on the efficacy and cost-efficiency of healthcare systems worldwide. Thanks to the emerging technologies, such as novel medical imaging and monitoring instrumentation, and Internet of Medical Things (IoMT), more accurate and versatile patient data than ever is available for medical use. To transform the technology advancements into better outcome and improved efficiency of healthcare, seamless interoperation of the underlying key technologies needs to be ensured. Novel IoT and communication technologies, edge computing and virtualization have a major role in this transformation. In this article, we explore the combined use of these technologies for managing complex tasks of connecting patients, personnel, hospital systems, electronic health records and medical instrumentation. We summarize our joint effort of four recent scientific articles that together demonstrate the potential of the edge-cloud continuum as the base approach for providing efficient and secure distributed e-health and e-welfare services. Finally, we provide an outlook for future research needs

From gadget to gadget-free hyperconnected world:conceptual analysis of user privacy challenges

Abstract Currently, gadgets are the most common and frequent ways of acquiring digital services. However, due to recent advancements in smart sensing and communication technologies, it seems that, this trend might get change in coming days. Future is hinting us towards a gadget-free hyperconnected society, where each object can sense, gather and process the information and can be able to take context based decisions. The vision behind this novel concept is to provide users, digital services anywhere and anytime, without using explicit gadgets or even wearables. Smart surrounding will be able to provide digital services to users according to their requirements. Also with the addition of 5G technology, this vision will get more strengthen and thus novel services will come into action. This will generate massive amount of critical data and eventually dealing with privacy in such ambient and gadget-free environment will be one of the major concerns for users. Therefore, this paper presents privacy challenges from user’s perspectives, that can potentially arise in such gadget-free environment. An initial and tentative conceptual privacy framework is also discussed in the light of the user’s privacy issues. Furthermore, we provide an overview of transformation requirements needed in transition from the gadget to gadget-free world

Distributed network and service architecture for future digital healthcare

Abstract According to World Health Organization (WHO), the worldwide prevalence of chronic diseases increases fast and new threats, such as Covid-19 pandemic, continue to emerge, while the aging population continues decaying the dependency ratio. These challenges will cause a huge pressure on the efficacy and cost-efficiency of healthcare systems worldwide. Thanks to the emerging technologies, such as novel medical imaging and monitoring instrumentation, and Internet of Medical Things (IoMT), more accurate and versatile patient data than ever is available for medical use. To transform the technology advancements into better outcome and improved efficiency of healthcare, seamless interoperation of the underlying key technologies needs to be ensured. Novel IoT and communication technologies, edge computing and virtualization have a major role in this transformation. In this article, we explore the combined use of these technologies for managing complex tasks of connecting patients, personnel, hospital systems, electronic health records and medical instrumentation. We summarize our joint effort of four recent scientific articles that together demonstrate the potential of the edge-cloud continuum as the base approach for providing efficient and secure distributed e-health and e-welfare services. Finally, we provide an outlook for future research needs

Health-BlockEdge:blockchain-edge framework for reliable low-latency digital healthcare applications

Abstract The rapid evolution of technology allows the healthcare sector to adopt intelligent, context-aware, secure, and ubiquitous healthcare services. Together with the global trend of an aging population, it has become highly important to propose value-creating, yet cost-efficient digital solutions for healthcare systems. These solutions should provide effective means of healthcare services in both the hospital and home care scenarios. In this paper, we focused on the latter case, where the goal was to provide easy-to-use, reliable, and secure remote monitoring and aid for elderly persons at their home. We proposed a framework to integrate the capabilities of edge computing and blockchain technology to address some of the key requirements of smart remote healthcare systems, such as long operating times, low cost, resilience to network problems, security, and trust in highly dynamic network conditions. In order to assess the feasibility of our approach, we evaluated the performance of our framework in terms of latency, power consumption, network utilization, and computational load, compared to a scenario where no blockchain was used