200 research outputs found

    Toward Dynamic Social-Aware Networking Beyond Fifth Generation

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    The rise of the intelligent information world presents significant challenges for the telecommunication industry in meeting the service-level requirements of future applications and incorporating societal and behavioral awareness into the Internet of Things (IoT) objects. Social Digital Twins (SDTs), or Digital Twins augmented with social capabilities, have the potential to revolutionize digital transformation and meet the connectivity, computing, and storage needs of IoT devices in dynamic Fifth-Generation (5G) and Beyond Fifth-Generation (B5G) networks. This research focuses on enabling dynamic social-aware B5G networking. The main contributions of this work include(i) the design of a reference architecture for the orchestration of SDTs at the network edge to accelerate the service discovery procedure across the Social Internet of Things (SIoT); (ii) a methodology to evaluate the highly dynamic system performance considering jointly communication and computing resources; (iii) a set of practical conclusions and outcomes helpful in designing future digital twin-enabled B5G networks. Specifically, we propose an orchestration for SDTs and an SIoT-Edge framework aligned with the Multi-access Edge Computing (MEC) architecture ratified by the European Telecommunications Standards Institute (ETSI). We formulate the optimal placement of SDTs as a Quadratic Assignment Problem (QAP) and propose a graph-based approximation scheme considering the different types of IoT devices, their social features, mobility patterns, and the limited computing resources of edge servers. We also study the appropriate intervals for re-optimizing the SDT deployment at the network edge. The results demonstrate that accounting for social features in SDT placement offers considerable improvements in the SIoT browsing procedure. Moreover, recent advancements in wireless communications, edge computing, and intelligent device technologies are expected to promote the growth of SIoT with pervasive sensing and computing capabilities, ensuring seamless connections among SIoT objects. We then offer a performance evaluation methodology for eXtended Reality (XR) services in edge-assisted wireless networks and propose fluid approximations to characterize the XR content evolution. The approach captures the time and space dynamics of the content distribution process during its transient phase, including time-varying loads, which are affected by arrival, transition, and departure processes. We examine the effects of XR user mobility on both communication and computing patterns. The results demonstrate that communication and computing planes are the key barriers to meeting the requirement for real-time transmissions. Furthermore, due to the trend toward immersive, interactive, and contextualized experiences, new use cases affect user mobility patterns and, therefore, system performance.Cotutelle -yhteisväitöskirj

    Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

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    Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ

    PIS: IoT & Industry 4.0 Challenges

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    International audienceIn the era of Industry 4.0, digital manufacturing is evolving into smart manufacturing. This evolution impacts companies in three main areas: organization, people, and technologies. This chapter analyzes the Internet of Things (IoT) and Cyber-Physical Systems (CPS)—key technologies transforming the physical world into a digitalized physical world. IoT and CPS provide factories with sensing capabilities, perform data and context capture and allow them to act/react to optimize the value chain. We survey the recent state-of-the-art development of the Industrial Internet of Things (IIoT)—also known as IoT and CPS in the context of Industry 4.0, from a protocol, architecture, and standard point-of-view. We also explore key challenges and future research directions for extensive industrial adoption of these technologies

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

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    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    Service Provisioning in Edge-Cloud Continuum Emerging Applications for Mobile Devices

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    Disruptive applications for mobile devices can be enhanced by Edge computing facilities. In this context, Edge Computing (EC) is a proposed architecture to meet the mobility requirements imposed by these applications in a wide range of domains, such as the Internet of Things, Immersive Media, and Connected and Autonomous Vehicles. EC architecture aims to introduce computing capabilities in the path between the user and the Cloud to execute tasks closer to where they are consumed, thus mitigating issues related to latency, context awareness, and mobility support. In this survey, we describe which are the leading technologies to support the deployment of EC infrastructure. Thereafter, we discuss the applications that can take advantage of EC and how they were proposed in the literature. Finally, after examining enabling technologies and related applications, we identify some open challenges to fully achieve the potential of EC, and also research opportunities on upcoming paradigms for service provisioning. This survey is a guide to comprehend the recent advances on the provisioning of mobile applications, as well as foresee the expected next stages of evolution for these applications

    Seamless connectivity:investigating implementation challenges of multibroker MQTT platform for smart environmental monitoring

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    Abstract. This thesis explores the performance and efficiency of MQTT-based infrastructure Internet of Things (IoT) sensor networks for smart environment. The study focuses on the impact of network latency and broker switching in distributed multi-broker MQTT platforms. The research involves three case studies: a cloud-based multi-broker deployment, a Local Area Network (LAN)-based multi-broker deployment, and a multi-layer LAN network-based multi-broker deployment. The research is guided by three objectives: quantifying and analyzing the latency of multi-broker MQTT platforms; investigating the benefits of distributed brokers for edge users; and assessing the impact of switching latency at applications. This thesis ultimately seeks to answer three key questions related to network and switching latency, the merits of distributed brokers, and the influence of switching latency on the reliability of end-user applications

    Socially Beneficial Metaverse: Framework, Technologies, Applications, and Challenges

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    In recent years, the maturation of emerging technologies such as Virtual Reality, Digital twins, and Blockchain has accelerated the realization of the metaverse. As a virtual world independent of the real world, the metaverse will provide users with a variety of virtual activities that bring great convenience to society. In addition, the metaverse can facilitate digital twins, which offers transformative possibilities for the industry. Thus, the metaverse has attracted the attention of the industry, and a huge amount of capital is about to be invested. However, the development of the metaverse is still in its infancy and little research has been undertaken so far. We describe the development of the metaverse. Next, we introduce the architecture of the socially beneficial metaverse (SB-Metaverse) and we focus on the technologies that support the operation of SB-Metaverse. In addition, we also present the applications of SB-Metaverse. Finally, we discuss several challenges faced by SB-Metaverse which must be addressed in the future.Comment: 28 pages, 6 figures, 3 table

    Edge Intelligence Simulator:a platform for simulating intelligent edge orchestration solutions

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    Abstract. To support the stringent requirements of the future intelligent and interactive applications, intelligence needs to become an essential part of the resource management in the edge environment. Developing intelligent orchestration solutions is a challenging and arduous task, where the evaluation and comparison of the proposed solution is a focal point. Simulation is commonly used to evaluate and compare proposed solutions. However, there does not currently exist openly available simulators that would have a specific focus on supporting the research on intelligent edge orchestration methods. This thesis presents a simulation platform called Edge Intelligence Simulator (EISim), the purpose of which is to facilitate the research on intelligent edge orchestration solutions. In its current form, the platform supports simulating deep reinforcement learning based solutions and different orchestration control topologies in scenarios related to task offloading and resource pricing on edge. The platform also includes additional tools for creating simulation environments, running simulations for agent training and evaluation, and plotting results. This thesis gives a comprehensive overview of the state of the art in edge and fog simulation, orchestration, offloading, and resource pricing, which provides a basis for the design of EISim. The methods and tools that form the foundation of the current EISim implementation are also presented, along with a detailed description of the EISim architecture, default implementations, use, and additional tools. Finally, EISim with its default implementations is validated and evaluated through a large-scale simulation study with 24 simulation scenarios. The results of the simulation study verify the end-to-end performance of EISim and show its capability to produce sensible results. The results also illustrate how EISim can help the researcher in controlling and monitoring the training of intelligent agents, as well as in evaluating solutions against different control topologies.Reunaälysimulaattori : alusta älykkäiden reunalaskennan orkestrointiratkaisujen simulointiin. Tiivistelmä. Älykkäiden ratkaisujen täytyy tulla olennaiseksi osaksi reunaympäristön resurssien hallinnointia, jotta tulevaisuuden vuorovaikutteisten ja älykkäiden sovellusten suoritusta voidaan tukea tasolla, joka täyttää sovellusten tiukat suoritusvaatimukset. Älykkäiden orkestrointiratkaisujen kehitys on vaativa ja työläs prosessi, jonka keskiöön kuuluu olennaisesti menetelmien testaaminen ja vertailu muita menetelmiä vasten. Simulointia käytetään tyypillisesti menetelmien arviointiin ja vertailuun, mutta tällä hetkellä ei ole avoimesti saatavilla simulaattoreita, jotka eritoten keskittyisivät tukemaan älykkäiden reunaorkestrointiratkaisujen kehitystä. Tässä opinnäytetyössä esitellään simulaatioalusta nimeltään Edge Intelligence Simulator (EISim; Reunaälysimulaattori), jonka tarkoitus on helpottaa älykkäiden reunaorkestrointiratkaisujen tutkimusta. Nykymuodossaan se tukee vahvistusoppimispohjaisten ratkaisujen sekä erityyppisten orkestroinnin kontrollitopologioiden simulointia skenaarioissa, jotka liittyvät laskennan siirtoon ja resurssien hinnoitteluun reunaympäristössä. Alustan mukana tulee myös lisätyökaluja, joita voi käyttää simulaatioympäristöjen luomiseen, simulaatioiden ajamiseen agenttien koulutusta ja arviointia varten, sekä simulaatiotulosten visualisoimiseen. Tämä opinnäytetyö sisältää kattavan katsauksen reunaympäristön simuloinnin, reunaorkestroinnin, laskennan siirron ja resurssien hinnoittelun nykytilaan kirjallisuudessa, mikä tarjoaa kunnollisen lähtökohdan EISimin toteutukselle. Opinnäytetyö esittelee menetelmät ja työkalut, joihin EISimin tämänhetkinen toteutus perustuu, sekä antaa yksityiskohtaisen kuvauksen EISimin arkkitehtuurista, oletustoteutuksista, käytöstä ja lisätyökaluista. EISimin validointia ja arviointia varten esitellään laaja simulaatiotutkimus, jossa EISimin oletustoteutuksia simuloidaan 24 simulaatioskenaariossa. Simulaatiotutkimuksen tulokset todentavat EISimin kokonaisvaltaisen toimintakyvyn, sekä osoittavat EISimin kyvyn tuottaa järkeviä tuloksia. Tulokset myös havainnollistavat, miten EISim voi auttaa tutkijoita älykkäiden agenttien koulutuksessa ja ratkaisujen arvioinnissa eri kontrollitopologioita vasten

    Mobility-aware fog computing in dynamic networks with mobile nodes: A survey

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    Fog computing is an evolving paradigm that addresses the latency-oriented performance and spatio-temporal issues of the cloud services by providing an extension to the cloud computing and storage services in the vicinity of the service requester. In dynamic networks, where both the mobile fog nodes and the end users exhibit time-varying characteristics, including dynamic network topology changes, there is a need of mobility-aware fog computing, which is very challenging due to various dynamisms, and yet systematically uncovered. This paper presents a comprehensive survey on the fog computing compliant with the OpenFog (IEEE 1934) standardised concept, where the mobility of fog nodes constitutes an integral part. A review of the state-of-the-art research in fog computing implemented with mobile nodes is conducted. The review includes the identification of several models of fog computing concept established on the principles of opportunistic networking, social communities, temporal networks, and vehicular ad-hoc networks. Relevant to these models, the contributing research studies are critically examined to provide an insight into the open issues and future research directions in mobile fog computing research
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