Essentiality of managing the resource information in the coordinated fog-to-cloud paradigm

This is the peer reviewed version of the following article: Sengupta, S, Garcia, J, Masip‐Bruin, X. Essentiality of managing the resource information in the coordinated fog‐to‐cloud paradigm. Int J Commun Syst. 2019, which has been published in final form at https://doi.org/10.1002/dac.4286. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Fog-to-cloud (F2C) computing is an emerging computational platform. By combing the cloud, fog, and IoT, it provides an excellent framework for managing and coordinating the resources in any smart computing domain. Efficient management of these kinds of diverse resources is one of the critical tasks in the F2C system. Also, it must be considered that different types of services are offered by any smart system. So, before managing these resources and enabling the various types of services, it is essential to have some comprehensive informational catalogue of resources and services. Hence, after identifying the resource and service-task taxonomy, our main aim in this paper is finding out a solution for properly organizing this information over the F2C system. For that purpose, we are proposing a modified F2C framework where all the information is distributively stored near to the edge of the network. Finally, by presenting some experimental results, we evaluate and validate the performance of our proposing framework.This work has been supported by the Spanish Ministry of Science, Innovation and Universities and by the European Regional Development Fund (FEDER) under contract RTI2018-094532-B-I00 and by the H2020 European Union mF2C project with reference 730929.Peer ReviewedPostprint (published version

Adaptive learning-based resource management strategy in fog-to-cloud

Technology in the twenty-first century is rapidly developing and driving us into a new smart computing world, and emerging lots of new computing architectures. Fog-to-Cloud (F2C) is among one of them, which emerges to ensure the commitment for bringing the higher computing facilities near to the edge of the network and also help the large-scale computing system to be more intelligent. As the F2C is in its infantile state, therefore one of the biggest challenges for this computing paradigm is to efficiently manage the computing resources. Mainly, to address this challenge, in this work, we have given our sole interest for designing the initial architectural framework to build a proper, adaptive and efficient resource management mechanism in F2C. F2C has been proposed as a combined, coordinated and hierarchical computing platform, where a vast number of heterogeneous computing devices are participating. Notably, their versatility creates a massive challenge for effectively handling them. Even following any large-scale smart computing system, it can easily recognize that various kind of services is served for different purposes. Significantly, every service corresponds with the various tasks, which have different resource requirements. So, knowing the characteristics of participating devices and system offered services is giving advantages to build effective and resource management mechanism in F2C-enabled system. Considering these facts, initially, we have given our intense focus for identifying and defining the taxonomic model for all the participating devices and system involved services-tasks. In any F2C-enabled system consists of a large number of small Internet-of-Things (IoTs) and generating a continuous and colossal amount of sensing-data by capturing various environmental events. Notably, this sensing-data is one of the key ingredients for various smart services which have been offered by the F2C-enabled system. Besides that, resource statistical information is also playing a crucial role, for efficiently providing the services among the system consumers. Continuous monitoring of participating devices generates a massive amount of resource statistical information in the F2C-enabled system. Notably, having this information, it becomes much easier to know the device's availability and suitability for executing some tasks to offer some services. Therefore, ensuring better service facilities for any latency-sensitive services, it is essential to securely distribute the sensing-data and resource statistical information over the network. Considering these matters, we also proposed and designed a secure and distributed database framework for effectively and securely distribute the data over the network. To build an advanced and smarter system is necessarily required an effective mechanism for the utilization of system resources. Typically, the utilization and resource handling process mainly depend on the resource selection and allocation mechanism. The prediction of resources (e.g., RAM, CPU, Disk, etc.) usage and performance (i.e., in terms of task execution time) helps the selection and allocation process. Thus, adopting the machine learning (ML) techniques is much more useful for designing an advanced and sophisticated resource allocation mechanism in the F2C-enabled system. Adopting and performing the ML techniques in F2C-enabled system is a challenging task. Especially, the overall diversification and many other issues pose a massive challenge for successfully performing the ML techniques in any F2C-enabled system. Therefore, we have proposed and designed two different possible architectural schemas for performing the ML techniques in the F2C-enabled system to achieve an adaptive, advance and sophisticated resource management mechanism in the F2C-enabled system. Our proposals are the initial footmarks for designing the overall architectural framework for resource management mechanism in F2C-enabled system.La tecnologia del segle XXI avança ràpidament i ens condueix cap a un nou món intel·ligent, creant nous models d'arquitectures informàtiques. Fog-to-Cloud (F2C) és un d’ells, i sorgeix per garantir el compromís d’acostar les instal·lacions informàtiques a prop de la xarxa i també ajudar el sistema informàtic a gran escala a ser més intel·ligent. Com que el F2C es troba en un estat preliminar, un dels majors reptes d’aquest paradigma tecnològic és gestionar eficientment els recursos informàtics. Per fer front a aquest repte, en aquest treball hem centrat el nostre interès en dissenyar un marc arquitectònic per construir un mecanisme de gestió de recursos adequat, adaptatiu i eficient a F2C.F2C ha estat concebut com una plataforma informàtica combinada, coordinada i jeràrquica, on participen un gran nombre de dispositius heterogenis. La seva versatilitat planteja un gran repte per gestionar-los de manera eficaç. Els serveis que s'hi executen consten de diverses tasques, que tenen requisits de recursos diferents. Per tant, conèixer les característiques dels dispositius participants i dels serveis que ofereix el sistema és un requisit per dissenyar mecanismes eficaços i de gestió de recursos en un sistema habilitat per F2C. Tenint en compte aquests fets, inicialment ens hem centrat en identificar i definir el model taxonòmic per a tots els dispositius i sistemes implicats en l'execució de tasques de serveis. Qualsevol sistema habilitat per F2C inclou en un gran nombre de dispositius petits i connectats (conegut com a Internet of Things, o IoT) que generen una quantitat contínua i colossal de dades de detecció capturant diversos events ambientals. Aquestes dades són un dels ingredients clau per a diversos serveis intel·ligents que ofereix F2C. A més, el seguiment continu dels dispositius participants genera igualment una gran quantitat d'informació estadística. En particular, en tenir aquesta informació, es fa molt més fàcil conèixer la disponibilitat i la idoneïtat dels dispositius per executar algunes tasques i oferir alguns serveis. Per tant, per garantir millors serveis sensibles a la latència, és essencial distribuir de manera equilibrada i segura la informació estadística per la xarxa. Tenint en compte aquests assumptes, també hem proposat i dissenyat un entorn de base de dades segura i distribuïda per gestionar de manera eficaç i segura les dades a la xarxa. Per construir un sistema avançat i intel·ligent es necessita un mecanisme eficaç per a la gestió de l'ús dels recursos del sistema. Normalment, el procés d’utilització i manipulació de recursos depèn principalment del mecanisme de selecció i assignació de recursos. La predicció de l’ús i el rendiment de recursos (per exemple, RAM, CPU, disc, etc.) en termes de temps d’execució de tasques ajuda al procés de selecció i assignació. Adoptar les tècniques d’aprenentatge automàtic (conegut com a Machine Learning, o ML) és molt útil per dissenyar un mecanisme d’assignació de recursos avançat i sofisticat en el sistema habilitat per F2C. L’adopció i la realització de tècniques de ML en un sistema F2C és una tasca complexa. Especialment, la diversificació general i molts altres problemes plantegen un gran repte per realitzar amb èxit les tècniques de ML. Per tant, en aquesta recerca hem proposat i dissenyat dos possibles esquemes arquitectònics diferents per realitzar tècniques de ML en el sistema habilitat per F2C per aconseguir un mecanisme de gestió de recursos adaptatiu, avançat i sofisticat en un sistema F2C. Les nostres propostes són els primers passos per dissenyar un marc arquitectònic general per al mecanisme de gestió de recursos en un sistema habilitat per F2C.Postprint (published version

Publicacions científiques de l'Escola Politècnica Superior d'Enginyeria de Vilanova i la Geltrú (EPSEVG) 2017-2021

La motivació que origina l’elaboració d’aquest informe va néixer l’any 2021 quan l’equip directiu de l’EPSEVG va sol·licitar conèixer el posicionament científic de la comunitat investigadora del Campus UPC Vilanova per tal d’identificar la seva recerca més rellevant. Aleshores es va realitzar l’informe Publicacions científiques de l'Escola Politècnica Superior d'Enginyeria de Vilanova i la Geltrú (EPSEVG) en el període 2015-2020 que s’actualitza en el present informe dins el període 2017-2021, ja que interessa mantenir una visió per blocs de 5 anys. La informació de base s’ha extret del portal de la producció científica FUTUR que fa visibles les publicacions introduïdes al sistema d’informació DRAC (Descriptor de la Recerca i l’Activitat Acadèmica) de la Universitat Politècnica de Catalunya. També s’ha utilitzat la base de dades Scopus d’Elsevier i Web of Science per identificar els quartils de les revistes recuperades (JCR) i per elaborar el mapa de matèries. La consulta d’aquestes fonts i recollida d’indicadors s’ha realitzat durant els mesos gener a abril 2023 en base a la producció científica del personal amb activitat de recerca de l’EPSEVG, signada amb l’afiliació UPC. El llistat de personal objecte d’aquest estudi s’ha elaborat a partir dels resultats que genera FUTUR en la cerca de ”EPSEVG” al botó d’Organitzacions. Així doncs, és de vital importància mantenir actualitzats els perfils a FUTUR, base d’informació d’aquest treball. Les publicacions científiques que s’han considerat per presentar en aquest informe són els articles de revista, les tesis doctorals, projectes competitius i no competitius i les patents. S’han exclòs els treballs presentats a congressos perquè no tenen un pes important en els processos d’avaluació i acreditació. La metodologia es basa en la recollida de diversos indicadors bibliomètrics de la producció científica del personal docent i investigador (PDI) adscrit als grups de recerca de l'Escola Politècnica Superior d'Enginyeria de Vilanova i la Geltrú (EPSEVG) durant els anys 2017-2021 per tal d’oferir una visió qualitativa global. Els indicadors que s’han tingut en compte són: nombre d’articles, indexats a Scopus; nombre de revistes amb indicació de quartil, segons WOS; nombre de cites (exclusió d’autocites), segons Scopus; nombre de projectes R+D+I competitius i no competitius; nombre de tesis dirigides i nombre patents, segons Futur. L’estructura d’aquest informe es desplega des d’una visió general a una més específica. En el primer apartat s’analitzen les dades generals i globals, seguidament aquests dades es mostren en relació als grups de recerca. Existeix PDI vinculat a l’EPSEVG, sense assignació a cap grup de recerca o amb assignació a grups amb seu a altres campus o universitats, que no formen part d’aquest estudi.Postprint (author's final draft

An exploration of cloud-based technology for enhancing emergency management: Cases from New Zealand

Despite widespread acknowledgement of the disruptive effect cloud-based technologies have in business, little is known about the role they might play in emergency management, in particular in natural emergencies. This research addresses this gap by exploring emergency management professionals’ perceptions of cloud usage in key emergency management lifecycle stages of preparedness and response. The Diffusion of Innovation theory is used as a theoretical lens to understand the factors that might influence emergency management professionals to utilise cloud-based technologies. It was employed as it focuses on understanding the adoption rate of an innovative technology. A multiple case study approach was employed involving six key New Zealand emergency services organisations. Twenty-nine semi-structured interviews were conducted with emergency professionals at both managerial and operational levels combined with three focus groups and five exercise observations. Data were analysed through grounded theory analysis. A comprehensive framework of multi-dimensional elements that influence the emergency professionals’ perceptions of cloud-based technology deployment was derived from the data. Six key elements were found to have significant influences on the emergency professionals’ perceptions against actual cloud-based technology usage in natural emergencies: organisational readiness, coordination, cloud-based technology characteristics, individual perceptions, individual readiness and non- cloud-based technology redundancy. Organisational readiness is shaped by four critical aspects: usage frequency, usage preparedness, organisational capacity, and training, which is a prerequisite for realising the success of cloud-based technology deployment when managing emergencies. Better inter-agency coordination enhances the emergency professionals’ confidence in using cloud-based technologies during the response stage. The cloud-based technology characteristics also significantly influence cloud-based technology deployment, including perceived advantages, perceived disadvantages, usefulness, and the deployment model type. The individual perception of enhancement expectation reflects the emergency professionals’ real needs in using cloud-based technologies when dealing with emergencies. The individual readiness includes human factors and knowledge, showing that personal attitudes towards cloud-based technology usage and cloud-based technology knowledge sufficiency influence cloud-based technology deployment for managing emergencies. Non- cloud-based technology redundancy eases the emergency professionals’ concerns of using cloud-based technologies when unexpected situations occur during natural emergencies. The framework highlights the need for examining diverse elements in an integrated manner to understand the emergency professionals’ utilisation patterns of cloud-based technologies for managing natural emergencies. The thesis concludes that awareness of the emergency professionals’ cloud-based technology utilisation patterns can help inform the use of cloud-based technologies to improve and integrate emergency preparations and responses. The research contributes to the body of knowledge in the field of both cloud computing and emergency management by providing a comprehensive framework to reveal an in-depth understanding of multi-dimensional elements that influence the emergency professionals’ perceptions of cloud-based technology deployment in natural emergencies. The framework can be used as practical guidelines for similar emergency services organisations to enhance organisational and individual readiness in cloud-based technology utilisation to carry out more effective emergency management performance

Emerging Technologies

This monograph investigates a multitude of emerging technologies including 3D printing, 5G, blockchain, and many more to assess their potential for use to further humanity’s shared goal of sustainable development. Through case studies detailing how these technologies are already being used at companies worldwide, author Sinan Küfeoğlu explores how emerging technologies can be used to enhance progress toward each of the seventeen United Nations Sustainable Development Goals and to guarantee economic growth even in the face of challenges such as climate change. To assemble this book, the author explored the business models of 650 companies in order to demonstrate how innovations can be converted into value to support sustainable development. To ensure practical application, only technologies currently on the market and in use actual companies were investigated. This volume will be of great use to academics, policymakers, innovators at the forefront of green business, and anyone else who is interested in novel and innovative business models and how they could help to achieve the Sustainable Development Goals. This is an open access book

Sustainable Development of the Biosphere

The future management of the world's resources depends upon reconciling the needs of socio-economic development with the conservation of the world's environment. This book provides a strategic framework for understanding and managing the long-term and large-scale interactions between these two requirements, based upon the sustainable development of the natural resources of the biosphere. It represents the first results of an on-going collaborative study organized by the International Institute for Applied Systems Analysis (IIASA) and involving some of the world's leading historians, natural scientists, development specialists and policy advisors. It provides an authoritative introduction to some of the most complex contemporary environmental issues, and is written in an easily comprehensible style to make the information accessible to a wide range of professional disciplines, to policy makers and analysts, and to the concerned layman