NFV Based Gateways for Virtualized Wireless Sensors Networks: A Case Study

Virtualization enables the sharing of a same wireless sensor network (WSN) by multiple applications. However, in heterogeneous environments, virtualized wireless sensor networks (VWSN) raises new challenges such as the need for on-the-fly, dynamic, elastic and scalable provisioning of gateways. Network Functions Virtualization (NFV) is an emerging paradigm that can certainly aid in tackling these new challenges. It leverages standard virtualization technology to consolidate special-purpose network elements on top of commodity hardware. This article presents a case study on NFV based gateways for VWSNs. In the study, a VWSN gateway provider, operates and manages an NFV based infrastructure. We use two different brands of wireless sensors. The NFV infrastructure makes possible the dynamic, elastic and scalable deployment of gateway modules in this heterogeneous VWSN environment. The prototype built with Openstack as platform is described

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

An Experimental Case Study on Edge Computing based Cyber-Physical Digital Service Provisioning with Mobile Robotics

Digitalization of physical interaction and infrastructure intensive industries provides an opportunity for new kind of value co-creation via cyber-physical digital service provisioning. The rapid technological progress is enabling re-distribution of both physical and cognitive tasks and work between people and machines. The paper explores concept of cyber-physical digital service and presents an experimental case study on cyber-physical digital service provisioning for building diagnostics, utilizing a mobile robot as service actor and resource. The case study applies Design Science Research Methodology (DSRM) with an objective to identify insights on design challenges and digital technology infrastructure requirements of cyber-physical digital service provisioning. Based on evaluation of designed, developed and demonstrated trial system, insights on identified design challenges and related requirements for evolution of digital technology infrastructure are provided as result

Comparison on OpenStack and OpenNebula performance to improve multi-Cloud architecture on cosmological simulation use case

With the increasing numbers of Cloud Service Providers and the migration of the Grids to the Cloud paradigm, it is necessary to be able to leverage these new resources. Moreover, a large class of High Performance Computing (HPC) applications can run these resources without (or with minor) modifications. But using these resources come with the cost of being able to interact with these new resource providers. In this paper we introduce the design of a HPC middleware that is able to use resources coming from an environment that compose of multiple Clouds as well as classical \hpc resources. Using the \diet middleware, we are able to deploy a large-scale, distributed HPC platform that spans across a large pool of resources aggregated from different providers. Furthermore, we hide to the end users the difficulty and complexity of selecting and using these new resources even when new Cloud Service Providers are added to the pool. Finally, we validate the architecture concept through cosmological simulation RAMSES. Thus we give a comparison of 2 well-known Cloud Computing Software: OpenStack and OpenNebula.Avec l'augmentation du nombre de fournisseurs de service Cloud et la migration des applications depuis les grilles de calcul vers le Cloud, il est nécessaire de pouvoir tirer parti de ces nouvelles ressources. De plus, une large classe des applications de calcul haute performance peuvent s'exécuter sur ces ressources sans modifications (ou avec des modifications mineures). Mais utiliser ces ressources vient avec le coût d'être capable d'intéragir avec des nouveaux fournisseurs de ressources. Dans ce papier, nous introduisons la conception d'un nouveau intergiciel HPC qui permet d'utiliser les ressources qui proviennent d'un environement composé de plusieurs Clouds comme des ressources classiques. En utilisant l'intergiciel \diet, nous sommes capable de déployer une plateforme HPC distribuée et large échelle qui s'étend sur un large ensemble de ressources aggrégées entre plusieurs fournisseurs Cloud. De plus, nous cachons à l'utilisateur final la difficulté et la complexité de sélectionner et d'utiliser ces nouvelles ressources quand un nouveau fournisseur de service Cloud est ajouté dans l'ensemble. Finalement, nous validons notre concept d'architecture via une application de simulation cosmologique RAMSES. Et nous fournissons une comparaison entre 2 intergiciels de Cloud: OpenStack et OpenNebula