20 research outputs found

    Distributed Environment for Efficient Virtual Machine Image Management in Federated Cloud Architectures

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    The use of Virtual Machines (VM) in Cloud computing provides various benefits in the overall software engineering lifecycle. These include efficient elasticity mechanisms resulting in higher resource utilization and lower operational costs. VM as software artifacts are created using provider-specific templates, called VM images (VMI), and are stored in proprietary or public repositories for further use. However, some technology specific choices can limit the interoperability among various Cloud providers and bundle the VMIs with nonessential or redundant software packages, leading to increased storage size, prolonged VMI delivery, stagnant VMI instantiation and ultimately vendor lock-in. To address these challenges, we present a set of novel functionalities and design approaches for efficient operation of distributed VMI repositories, specifically tailored for enabling: (i) simplified creation of lightweight and size optimized VMIs tuned for specific application requirements; (ii) multi-objective VMI repository optimization; and (iii) efficient reasoning mechanism to help optimizing complex VMI operations. The evaluation results confirm that the presented approaches can enable VMI size reduction by up to 55%, while trimming the image creation time by 66%. Furthermore, the repository optimization algorithms, can reduce the VMI delivery time by up to 51% and cut down the storage expenses by 3%. Moreover, by implementing replication strategies, the optimization algorithms can increase the system reliability by 74%

    Towards an Environment for Efficient and Transparent Virtual Machine Operations: The ENTICE Approach

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    Cloud computing is based on Virtual Machines (VM) or containers, which provide their own software execution environment that can be deployed by facilitating technologies on top of various physical hardware. The use of VMs or containers represents an efficient way to automatize the overall software engineering and operation life-cycle. Some of the benefits include elasticity and high scalability, which increases the utilization efficiency and decreases the operational costs. VMs or containers as software artifacts are created using provider-specific templates and are stored in proprietary or public repositories for further use. However, technology specific choices may reduce their portability, lead to a vendor lock-in, particularly when applications need to run in federated Clouds. In this paper we present the current state of development of the novel concept of a VM repository and operational environment for federated Clouds named ENTICE. The ENTICE environment has been designed to receive unmodified and functionally complete VM images from its users, and transparently tailor and optimise them for specific Cloud infrastructures with respect to their size, configuration, and geographical distribution, such that they are loaded, delivered, and executed faster and with improved QoS compared to their current behaviour. Furthermore, in this work a specific use case scenario for the ENTICE environment has been provided and the underlying novel technologies have been presented

    Dynamic management of virtual infrastructures

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s10723-014-9296-5Cloud infrastructures are becoming an appropriate solution to address the computational needs of scientific applications. However, the use of public or on-premises Infrastructure as a Service (IaaS) clouds requires users to have non-trivial system administration skills. Resource provisioning systems provide facilities to choose the most suitable Virtual Machine Images (VMI) and basic configuration of multiple instances and subnetworks. Other tasks such as the configuration of cluster services, computational frameworks or specific applications are not trivial on the cloud, and normally users have to manually select the VMI that best fits, including undesired additional services and software packages. This paper presents a set of components that ease the access and the usability of IaaS clouds by automating the VMI selection, deployment, configuration, software installation, monitoring and update of Virtual Appliances. It supports APIs from a large number of virtual platforms, making user applications cloud-agnostic. In addition it integrates a contextualization system to enable the installation and configuration of all the user required applications providing the user with a fully functional infrastructure. Therefore, golden VMIs and configuration recipes can be easily reused across different deployments. Moreover, the contextualization agent included in the framework supports horizontal (increase/decrease the number of resources) and vertical (increase/decrease resources within a running Virtual Machine) by properly reconfiguring the software installed, considering the configuration of the multiple resources running. This paves the way for automatic virtual infrastructure deployment, customization and elastic modification at runtime for IaaS clouds.The authors would like to thank to thank the financial support received from the Ministerio de Economia y Competitividad for the project CodeCloud (TIN2010-17804).Caballer Fernández, M.; Blanquer Espert, I.; Moltó, G.; Alfonso Laguna, CD. (2015). Dynamic management of virtual infrastructures. Journal of Grid Computing. 13(1):53-70. https://doi.org/10.1007/s10723-014-9296-5S5370131de Alfonso, C., Caballer, M., Alvarruiz, F., Molto, G., Hernández, V.: Infrastructure deployment over the cloud. In: 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, pp. 517–521. IEEE. (2011). doi: 10.1109/CloudCom.2011.77Alvarruiz, F., De Alfonso, C., Caballer, M., Hernández, V.: An energy manager for high performance computer clusters. In: 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications, pp. 231–238. (2012). doi: 10.1109/ISPA.2012.38Amazon Web Services: AWS CloudFormation. (2013). http://aws.amazon.com/es/cloudformation/Apache: Whirr (2013). http://whirr.apache.org/Blanquer, I., Brasche, G., Lezzi, D.: Requirements of scientific applications in cloud offerings. In: Proceedings of the 2012 6th Iberian Grid Infrastructure Conference, IBERGRID ’12, pp. 173–182 (2012)Bresnahan, J., Freeman, T., LaBissoniere, D., Keahey, K.: Managing appliance launches in infrastructure clouds. In: Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, TG ’11, pp. 12:1–12:7. ACM, New York (2011). doi: 10.1145/2016741.2016755Buyya, R., Ranjan, R., Calheiros, R.N.: InterCloud: utility-oriented federation of cloud computing environments for scaling of application services. Algoritm. Archit. Parallel Process. 6081, 20 (2010)Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Futur. Gener. Comput. Syst. 25(6), 599–616 (2009). doi: 10.1016/j.future.2008.12.001Caballer, M., De Alfonso, C., Alvarruiz, F., Moltó, G.: EC3: elastic cloud computing cluster. J. Comput. Syst. Sci. (2013). doi: 10.1016/j.jcss.2013.06.005Caballer, M., García, A., Moltó, G., de Alfonso, C.: Towards SLA-driven management of cloud infrastructures to elastically execute scientific applications. In: 6th Iberian Grid Infrastructure Conference (IberGrid), pp. 207–218 (2012)Carrión, J.V., Moltó, G., De Alfonso, C., Caballer, M., Hernández, V.: A generic catalog and repository service for virtual machine images. In: 2nd International ICST Conference on Cloud Computing CloudComp 2010 (2010)Cuomo, A., Modica, G., Distefano, S., Puliafito, A., Rak, M., Tomarchio, O., Venticinque, S., Villano, U.: An SLA-based broker for cloud infrastructures. J. Grid Comput 11(1), 1–25 (2012). doi: 10.1007/s10723-012-9241-4DeHaan, M.: Ansible. http://ansible.cc/ (2013)Distributed Management Task Force, Inc: Open Virtualization Format (OVF) (2010). http://dmtf.org/sites/default/files/standards/documents/DSP0243_1.1.0.pdfDistributed Management Task Force, Inc: Cloud Infrastructure Management Interface (CIMI) Model and REST Interface over HTTP Specification (2012). http://dmtf.org/sites/default/files/standards/documents/DSP0263_1.0.1.pdfEGI.eu: Seeking new horizons: EGI’s role for 2020. Tech. rep. (2012). https://documents.egi.eu/public/RetrieveFile?docid=1098&version=4&filename=EGI-1098-D230-final.pdfElmroth, E., Tordsson, J., Hernández, F.: Self-management challenges for multi-cloud architectures. Towards a service-based internet. Lect. Notes Comput. Sci. 6994, 38–49 (2011)HashiCorp: Vagrant (2013). http://www.vagrantup.com/Jacob, A.: Infrastructure in the cloud era. In: Proceedings of the 2009 International OReilly Conference Velocity (2009)Juve, G., Deelman, E.: Automating application deployment in infrastructure clouds. In: Proceedings of the 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, CLOUDCOM ’11, pp. 658–665. IEEE Computer Society, Washington DC (2011). doi: 10.1109/CloudCom.2011.102Keahey, K., Freeman, T.: Contextualization: providing one-click virtual clusters. In: 4th IEEE International Conference on eScience, pp. 301–308 (2008)Keahey, K., Freeman, T.: Architecting a large-scale elastic environment: recontextualization and adaptive cloud services for scientific computing (2012)Kecskemeti, G., Kertesz, A., Marosi, A., Kacsuk, P.: Interoperable resource management for establishing federated clouds. In: Achieving Federated and SelfManageable Cloud Infrastructures Theory and Practice, pp. 18–35 (2012). doi: 10.4018/978-1-4666-1631-8.ch002Kertesz, A., Kecskemeti, G., Oriol, M., Kotcauer, P., Acs, S., Rodríguez, M., Mercè, O., Marosi, A.C., Marco, J., Franch, X.: Enhancing federated cloud management with an integrated service monitoring approach. J. Grid Comput. 11(4), 699–720 (2013). doi: 10.1007/s10723-013-9269-0Loutas, N., Kamateri, E., Bosi, F., Tarabanis, K.: Cloud computing interoperability: the state of play. 2011 IEEE 3rd International Conference on Cloud Computing Technology and Science, pp. 752–757 (2011). doi: 10.1109/CloudCom.2011.116Marshall, P., Keahey, K., Freeman, T.: Elastic site: using clouds to elastically extend site resources. In: Proceedings of the 2010 IEEE/ACM 10th International Conference on Cluster, Cloud and Grid Computing, CCGRID ’10, pp. 43–52. IEEE Computer Society, Washington DC (2010). doi: 10.1109/CCGRID.2010.80Massie, M.L., Chun, B.N., Culler, D.E.: The ganglia distributed monitoring system: design, implementation, and experience. Parallel Comput. 30(5-6), 817–840 (2004)Mell, P., Grance, T.: The NIST definition of cloud computing. NIST Special Publication 800-145 (Final). Tech. rep. (2011). http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdfMoltó, G., Caballer, M., Romero, E., Alfonso, C.D.: Elastic memory management of virtualized infrastructures for applications with dynamic memory requirements. In: Proceedings of the International Conference on Computational Science ICCS 2013, pp. 159–168. Elsevier (2013). doi: 10.1016/j.procs.2013.05.179Morfeo: Claudia (2013). http://claudia.morfeo-project.org/wiki/index.php/Main_PageOASIS: Topology and Orchestration Specification for Cloud Applications Version 1.0 (2013). http://docs.oasis-open.org/tosca/TOSCA/v1.0/TOSCA-v1.0.htmlOCCI working group within the Open Grid Forum: Open Cloud Computing Interface Infrastructure (2011). http://ogf.org/documents/GFD.184.pdfOpscode: Chef (2013). http://www.opscode.com/chef/Pawluk, P., Simmons, B., Smit, M., Litoiu, M., Mankovski, S.: Introducing STRATOS: a cloud broker service. In: 2012 IEEE 5th International Conference on Cloud Computing, pp. 891–898 (2012). doi: 10.1109/CLOUD.2012.24Puppet Labs: IT Automation Software for System Administrators (2013). http://www.puppetlabs.com/Redl, C., Breskovic, I., Brandic, I., Dustdar, S.: Automatic SLA matching and provider selection in grid and cloud computing markets. In: Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing, GRID ’12, pp. 85–94. IEEE Computer Society, Washington (2012). doi: 10.1109/Grid.2012.18Rodero-Merino, L., Vaquero, L.M., Gil, V., Galán, F., Fontán, J., Montero, R.S., Llorente, I.M.: From infrastructure delivery to service management in clouds. Futur. Gener. Comput. Syst. 26(8), 1226–1240 (2010). doi: 10.1016/j.future.2010.02.013StratusLab: Claudia Platform (2013). http://stratuslab.eu/doku.php/claudiaSundareswaran, S., Squicciarini, A., Lin, D.: A brokerage-based approach for cloud service selection. In: Proceedings of the 2012 IEEE 5th International Conference on Cloud Computing, CLOUD ’12, pp. 558–565 (2012). doi: 10.1109/CLOUD.2012.119Telefónica Investigación y Desarrollo S.A. Unipersonal.: Telefónicas TCloud API Specification. (2010). http://www.tid.es/files/doc/apis/TCloud_API_Spec_v0.9.pdfYangui, S., Marshall, I.J., Laisne, J.P., Tata, S.: CompatibleOne: The open source cloud broker. J. Grid Comput. (2013). doi: 10.1007/s10723-013-9285-

    A service broker for Intercloud computing

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    This thesis aims at assisting users in finding the most suitable Cloud resources taking into account their functional and non-functional SLA requirements. A key feature of the work is a Cloud service broker acting as mediator between consumers and Clouds. The research involves the implementation and evaluation of two SLA-aware match-making algorithms by use of a simulation environment. The work investigates also the optimal deployment of Multi-Cloud workflows on Intercloud environments

    Efficient and elastic management of computing infrastructures

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    Tesis por compendio[EN] Modern data centers integrate a lot of computer and electronic devices. However, some reports state that the mean usage of a typical data center is around 50% of its peak capacity, and the mean usage of each server is between 10% and 50%. A lot of energy is destined to power on computer hardware that most of the time remains idle. Therefore, it would be possible to save energy simply by powering off those parts from the data center that are not actually used, and powering them on again as they are needed. Most data centers have computing clusters that are used for intensive computing, recently evolving towards an on-premises Cloud service model. Despite the use of low consuming components, higher energy savings can be achieved by dynamically adapting the system to the actual workload. The main approach in this case is the usage of energy saving criteria for scheduling the jobs or the virtual machines into the working nodes. The aim is to power off idle servers automatically. But it is necessary to schedule the power management of the servers in order to minimize the impact on the end users and their applications. The objective of this thesis is the elastic and efficient management of cluster infrastructures, with the aim of reducing the costs associated to idle components. This objective is addressed by automating the power management of the working nodes in a computing cluster, and also proactive stimulating the load distribution to achieve idle resources that could be powered off by means of memory overcommitment and live migration of virtual machines. Moreover, this automation is of interest for virtual clusters, as they also suffer from the same problems. While in physical clusters idle working nodes waste energy, in the case of virtual clusters that are built from virtual machines, the idle working nodes can waste money in commercial Clouds or computational resources in an on-premises Cloud.[ES] En los Centros de Procesos de Datos (CPD) existe una gran concentración de dispositivos informáticos y de equipamiento electrónico. Sin embargo, algunos estudios han mostrado que la utilización media de los CPD está en torno al 50%, y que la utilización media de los servidores se encuentra entre el 10% y el 50%. Estos datos evidencian que existe una gran cantidad de energía destinada a alimentar equipamiento ocioso, y que podríamos conseguir un ahorro energético simplemente apagando los componentes que no se estén utilizando. En muchos CPD suele haber clusters de computadores que se utilizan para computación de altas prestaciones y para la creación de Clouds privados. Si bien se ha tratado de ahorrar energía utilizando componentes de bajo consumo, también es posible conseguirlo adaptando los sistemas a la carga de trabajo en cada momento. En los últimos años han surgido trabajos que investigan la aplicación de criterios energéticos a la hora de seleccionar en qué servidor, de entre los que forman un cluster, se debe ejecutar un trabajo o alojar una máquina virtual. En muchos casos se trata de conseguir equipos ociosos que puedan ser apagados, pero habitualmente se asume que dicho apagado se hace de forma automática, y que los equipos se encienden de nuevo cuando son necesarios. Sin embargo, es necesario hacer una planificación de encendido y apagado de máquinas para minimizar el impacto en el usuario final. En esta tesis nos planteamos la gestión elástica y eficiente de infrastructuras de cálculo tipo cluster, con el objetivo de reducir los costes asociados a los componentes ociosos. Para abordar este problema nos planteamos la automatización del encendido y apagado de máquinas en los clusters, así como la aplicación de técnicas de migración en vivo y de sobreaprovisionamiento de memoria para estimular la obtención de equipos ociosos que puedan ser apagados. Además, esta automatización es de interés para los clusters virtuales, puesto que también sufren el problema de los componentes ociosos, sólo que en este caso están compuestos por, en lugar de equipos físicos que gastan energía, por máquinas virtuales que gastan dinero en un proveedor Cloud comercial o recursos en un Cloud privado.[CA] En els Centres de Processament de Dades (CPD) hi ha una gran concentració de dispositius informàtics i d'equipament electrònic. No obstant això, alguns estudis han mostrat que la utilització mitjana dels CPD està entorn del 50%, i que la utilització mitjana dels servidors es troba entre el 10% i el 50%. Estes dades evidencien que hi ha una gran quantitat d'energia destinada a alimentar equipament ociós, i que podríem aconseguir un estalvi energètic simplement apagant els components que no s'estiguen utilitzant. En molts CPD sol haver-hi clusters de computadors que s'utilitzen per a computació d'altes prestacions i per a la creació de Clouds privats. Si bé s'ha tractat d'estalviar energia utilitzant components de baix consum, també és possible aconseguir-ho adaptant els sistemes a la càrrega de treball en cada moment. En els últims anys han sorgit treballs que investiguen l'aplicació de criteris energètics a l'hora de seleccionar en quin servidor, d'entre els que formen un cluster, s'ha d'executar un treball o allotjar una màquina virtual. En molts casos es tracta d'aconseguir equips ociosos que puguen ser apagats, però habitualment s'assumix que l'apagat es fa de forma automàtica, i que els equips s'encenen novament quan són necessaris. No obstant això, és necessari fer una planificació d'encesa i apagat de màquines per a minimitzar l'impacte en l'usuari final. En esta tesi ens plantegem la gestió elàstica i eficient d'infrastructuras de càlcul tipus cluster, amb l'objectiu de reduir els costos associats als components ociosos. Per a abordar este problema ens plantegem l'automatització de l'encesa i apagat de màquines en els clusters, així com l'aplicació de tècniques de migració en viu i de sobreaprovisionament de memòria per a estimular l'obtenció d'equips ociosos que puguen ser apagats. A més, esta automatització és d'interés per als clusters virtuals, ja que també patixen el problema dels components ociosos, encara que en este cas estan compostos per, en compte d'equips físics que gasten energia, per màquines virtuals que gasten diners en un proveïdor Cloud comercial o recursos en un Cloud privat.Alfonso Laguna, CD. (2015). Efficient and elastic management of computing infrastructures [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/57187Compendi

    Earth Observation Open Science and Innovation

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    geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc

    An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management

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    (c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Smart urban transportation management can be considered as a multifaceted big data challenge. It strongly relies on the information collected into multiple, widespread, and heterogeneous data sources as well as on the ability to extract actionable insights from them. Besides data, full stack (from platform to services and applications) Information and Communications Technology (ICT) solutions need to be specifically adopted to address smart cities challenges. Smart urban transportation management is one of the key use cases addressed in the context of the EUBra-BIGSEA (Europe-Brazil Collaboration of Big Data Scientific Research through Cloud-Centric Applications) project. This paper specifically focuses on the City Administration Dashboard, a public transport analytics application that has been developed on top of the EUBra-BIGSEA platform and used by the Municipality stakeholders of Curitiba, Brazil, to tackle urban traffic data analysis and planning challenges. The solution proposed in this paper joins together a scalable big and fast data analytics platform, a flexible and dynamic cloud infrastructure, data quality and entity matching algorithms as well as security and privacy techniques. By exploiting an interoperable programming framework based on Python Application Programming Interface (API), it allows an easy, rapid and transparent development of smart cities applications.This work was supported by the European Commission through the Cooperation Programme under EUBra-BIGSEA Horizon 2020 Grant [Este projeto e resultante da 3a Chamada Coordenada BR-UE em Tecnologias da Informacao e Comunicacao (TIC), anunciada pelo Ministerio de Ciencia, Tecnologia e Inovacao (MCTI)] under Grant 690116.Fiore, S.; Elia, D.; Pires, CE.; Mestre, DG.; Cappiello, C.; Vitali, M.; Andrade, N.... (2019). An Integrated Big and Fast Data Analytics Platform for Smart Urban Transportation Management. IEEE Access. 7:117652-117677. https://doi.org/10.1109/ACCESS.2019.2936941S117652117677

    Cyber-storms come from clouds:Security of cloud computing in the IoT era

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    The Internet of Things (IoT) is rapidly changing our society to a world where every “thing” is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on the security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds

    Proyecto Docente e Investigador, Trabajo Original de Investigación y Presentación de la Defensa, preparado por Germán Moltó para concursar a la plaza de Catedrático de Universidad, concurso 082/22, plaza 6708, área de Ciencia de la Computación e Inteligencia Artificial

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    Este documento contiene el proyecto docente e investigador del candidato Germán Moltó Martínez presentado como requisito para el concurso de acceso a plazas de Cuerpos Docentes Universitarios. Concretamente, el documento se centra en el concurso para la plaza 6708 de Catedrático de Universidad en el área de Ciencia de la Computación en el Departamento de Sistemas Informáticos y Computación de la Universitat Politécnica de València. La plaza está adscrita a la Escola Técnica Superior d'Enginyeria Informàtica y tiene como perfil las asignaturas "Infraestructuras de Cloud Público" y "Estructuras de Datos y Algoritmos".También se incluye el Historial Académico, Docente e Investigador, así como la presentación usada durante la defensa.Germán Moltó Martínez (2022). Proyecto Docente e Investigador, Trabajo Original de Investigación y Presentación de la Defensa, preparado por Germán Moltó para concursar a la plaza de Catedrático de Universidad, concurso 082/22, plaza 6708, área de Ciencia de la Computación e Inteligencia Artificial. http://hdl.handle.net/10251/18903

    Secure Communication in Disaster Scenarios

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    Während Naturkatastrophen oder terroristischer Anschläge ist die bestehende Kommunikationsinfrastruktur häufig überlastet oder fällt komplett aus. In diesen Situationen können mobile Geräte mithilfe von drahtloser ad-hoc- und unterbrechungstoleranter Vernetzung miteinander verbunden werden, um ein Notfall-Kommunikationssystem für Zivilisten und Rettungsdienste einzurichten. Falls verfügbar, kann eine Verbindung zu Cloud-Diensten im Internet eine wertvolle Hilfe im Krisen- und Katastrophenmanagement sein. Solche Kommunikationssysteme bergen jedoch ernsthafte Sicherheitsrisiken, da Angreifer versuchen könnten, vertrauliche Daten zu stehlen, gefälschte Benachrichtigungen von Notfalldiensten einzuspeisen oder Denial-of-Service (DoS) Angriffe durchzuführen. Diese Dissertation schlägt neue Ansätze zur Kommunikation in Notfallnetzen von mobilen Geräten vor, die von der Kommunikation zwischen Mobilfunkgeräten bis zu Cloud-Diensten auf Servern im Internet reichen. Durch die Nutzung dieser Ansätze werden die Sicherheit der Geräte-zu-Geräte-Kommunikation, die Sicherheit von Notfall-Apps auf mobilen Geräten und die Sicherheit von Server-Systemen für Cloud-Dienste verbessert
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