Browsing by Author "Vallati, Carlo"
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item BETaaS platform - a Things as a Service environment for future M2M marketplaces(2015-02-23) Anggorojati, Bayu; Kyriazakos, Sofoklis; Prasad, Neeli; Vallati, Carlo; Mingozzi, Enzo; Tanganelli, Giacomo; Buonaccorsi, Novella; Valdambrini, Nicola; Martinez-Rodriguez, Belen; Nieto De-Santos, Francisco; Zonidis, Nikolaos; Labropoulous, George; Mamelli, Alessandro; Sommacampagna, Davide; Tecnalia Research & InnovationBuilding the Environment for Things as a Service (BETaaS) is a novel platform for the deployment and execution of contentcentric Machine-to-Machine (M2M) applications, which relies on a local cloud of gateways. BETaaS platform provides a uniform interface and services to map content with things in a context-aware manner. Deployment of services for the execution of applications is dynamic and takes into account the computational resources of the low-end physical devices used. To this aim, BETaaS platform is based on a suitable defined Internet of Things (IoT) model, allowing the integration of the BETaaS components within the future Internet environment. In this paper we present the BETaaS concept, the high level platform architecture and application scenarios that extend the state-of-the-art in M2M communications and open the horizon for future M2M marketplaces.Item BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things(2016-04-01) Vallati, Carlo; Mingozzi, Enzo; Tanganelli, Giacomo; Buonaccorsi, Novella; Valdambrini, Nicola; Zonidis, Nikolaos; Martinez-Rodriguez, Belen; Mamelli, Alessandro; Sommacampagna, Davide; Anggorojati, Bayu; Kyriazakos, Sofoklis; Prasad, Neeli; Nieto, Francisco Javier; Barreto, Oliver; Rodriguez, Oliver Barreto; Tecnalia Research & Innovation; BIGDATAThe integration of everyday objects into the Internet represents the foundation of the forthcoming Internet of Things (IoT). Such “smart” objects will be the building blocks of the next generation of applications that will exploit interaction between machines to implement enhanced services with minimum or no human intervention in the loop. A crucial factor to enable Machine-to-Machine (M2M) applications is a horizontal service infrastructure that seamlessly integrates existing IoT heterogeneous systems. The authors present BETaaS, a framework that enables horizontal M2M deployments. BETaaS is based on a distributed service infrastructure built on top of an overlay network of gateways that allows seamless integration of existing IoT systems. The platform enables easy deployment of applications by exposing to developers a service oriented interface to access things (the Things-as-a-Service model) regardless of the technology and the physical infrastructure they belong.Item Semantic-based Context Modeling for Quality of Service Support in IoT Platforms(IEEE, 2016-06-21) Mingozzi, Enzo; Tanganelli, Giacomo; Vallati, Carlo; Martinez-Rodriguez, Belen; Mendia, Izaskun; Gonzalez-Rodriguez, M.; Tecnalia Research & Innovation; BIGDATA; SGThe Internet of Things (IoT) envisions billions of devices seamlessly connected to information systems, thus providing a sensing platform for applications. The availability of such a huge number of smart things will entail a multiplicity of devices collecting overlapping data and/or providing similar functionalities. In this scenario, efficient discovery and appropriate selection of things through proper context acquisition and management will represent a critical requirement and a challenge for future IoT platforms. In this work we present a practical approach to model and manage context, and how this information can be exploited to implement QoS-aware thing service selection. In particular, it is shown how context can be used to infer knowledge on the equivalence of thing services through semantic reasoning, and how such information can be exploited to allocate thing services to applications while meeting QoS requirements even in case of failures. The proposed approach is demonstrated through a simple yet illustrative experiment in a smart home scenario.