Design and performance evaluation of advanced QoS-enabled service-oriented architectures for the Internet of Things

The Internet of Things (IoT) is rapidly becoming reality, the cut off prices as well as the advancement in the consumer electronic field are the two main training factor. For this reason, new application scenarios are designed every days and then new challenges that must be addressed. In the future we will be surrounded by many smart devices, which will sense and act on the physical environment. Such number of smart devices will be the building block for a plethora of new smart applications which will provide to end user new enhanced service. In this context, the Quality of Service (QoS) has been recognized as a non functional key requirement for the success of the IoT. In fact, in the future IoT, we will have different applications each one with different QoS requirements, which will need to interact with a finite set of smart device each one with its QoS capabilities. Such mapping between requested and offered QoS must be managed in order to satisfy the end users. The work of this thesis focus on how to provide QoS for IoT in a cross-layer manner. In other words, our main goal is to provide QoS support that, on one hand, helps the back-end architecture to manage a wide set of IoT applications, each one with its QoS requirements, while, on the other hand, enhances the access network by adding QoS capabilities on top of smart devices. We analyzed existing QoS framework and, based on the status of the art, we derive a novel model specifically tailored for IoT systems. Then we define the procedures needed to negotiate the desired QoS level and to enforce the negotiated QoS. In particular we take care of the Thing selection problem which is raised whenever more than one thing can be exploited to obtain a certain service. Finally we considered the access network by providing different solutions to handle QoS with different grain scale. We proposed a totally transparent solution which exploits virtualization and proxying techniques to differentiate between different class of client and provide a class based prioritization schema. Then we went further by designing a QoS framework directly on top of a standard IoT protocol called Constrained Application Protocol (CoAP). We designed the QoS support to enhance the Observing paradigm which is of paramount importance especially if we consider industrial applications which might benefit from a certain level of QoS assurances

A gateway-based scalable architecture for the Internet of Things

The Internet of Things is a wide research field, and a lot of problems still have to be solved. This work aims to solve some of them, with particular regard to identifications and end point communication using only standard protocols. It consists of a network of gateways connected to each other by an overlay network. Clients and servers, on the other hand, are connected only to their local gateway. In this way distributed resources are seen, by clients, as logically connected to their local gateway. The entire work has its focus on a SOA view, where clients ask for services and obtain responses without necessarily knowing anything about the overall system. Aiming to use standard protocols only, clients use CoAP for interacting with the overall system while a p2p network, called XMHT, forms the overlay network and is responsible for localizing resources. CoAP is also used for communications between gateways. Moreover the proposed architecture implements a new way for the observing feature that aims to solve performance issues when CoAp servers are hosted in constrained devices. For demonstration purposes a little prototype has been made. The prototype consists of two Alix, which operate as a gateway, and two different boards that are used to test a realistic scenario. The first board, in fact, can be used to remotely control a light bulb and also to detect the current consumption of the bulb itself. The second board, instead, has a light sensor and a water consumption sensor. In the testbed, clients send COAP requests only to their local gateway controlling, in this way, the whole environment

A Fog-based Distributed Look-up Service for Intelligent Transportation Systems

Future intelligent transportation systems and applications are expected to greatly benefit from the integration with a cloud computing infrastructure for service reliability and efficiency. More recently, fog computing has been proposed as a new computing paradigm to support low-latency and location-aware services by moving the execution of application logic on devices at the edge of the network in proximity of the physical systems, e.g. in the roadside infrastructure or directly in the connected vehicles. Such distributed runtime environment can support low-latency communication with sensors and actuators thus allowing functions such as real-time monitoring and remote control, e.g. for remote telemetry of public transport vehicles or remote control under emergency situations, respectively. These applications will require support for some basic functionalities from the runtime. Among them, discovery of sensors and actuators will be a significant challenge considering the large variety of sensors and actuators and their mobility. In this paper, a discovery service specifically tailored for fog computing platforms with mobile nodes is proposed. Instead of adopting a centralized approach, we pro-pose an approach based on a distributed hash table to be implemented by fog nodes, exploiting their storage and computation capabilities. The proposed approach supports by design multiple attributes and range queries. A prototype of the proposed service has been implemented and evaluated experimentally

the bartolomeo ammannati s fountain an artifact in progress

Abstract Artifacts are not only fundamental evidences of our history and culture, but they are even entities having a proper "life". The present research focuses on Bartolomeo Ammannati's Juno Fountain (1555) – a Late-Renaissance masterpiece whose eventful story made it moving around from its planned site, the "Sala Grande" in Florentine Palazzo Vecchio, to Pratolino Park, then to Boboli Garden. Finally, current fragments re-assembling and museography staging under the vaults of the National Museum of Bargello court in Florence has been set up a few years ago on the 5th centenary of Ammannati's birthdate – after careful historical research about the many vicissitudes of the Fountain. Although there isn't any location change expected for this Ammannati's artwork, investigations and researches are going on. Namely, the seismic performance of the reconstructed Fountain is to be checked with reference to the seismic hazard of the site, as provided by the Italian Code classification. To this objective, the previously done laser scanning which allowed a three-dimensional digital modeling to help re-assembling the Fountain, has been now adopted to perform the structural analysis. Consequently, a structural evaluation to check the setting's seismic behavior is currently under process. The research, developed by joining different knowledges and fields, is an example of the importance of a multidisciplinary approach for preserving artifacts and museums' collections

Semantic-based Context Modeling for Quality of Service Support in IoT Platforms

The 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.European Commission's FP

BETaaS: A Platform for Development and Execution of Machine-to-Machine Applications in the Internet of Things

The 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

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Energy-Efficient IoT Service Brokering with Quality of Service Support

The Internet of Things (IoT) is becoming real, and recent studies highlight that the number of IoT devices will significantly grow in the next decade. Such massive IoT deployments are typically made available to applications as a service by means of IoT platforms, which are aware of the characteristics of the connected IoT devices⁻usually constrained in terms of computation, storage and energy capabilities⁻and dispatch application’s service requests to appropriate devices based on their capabilities. In this work, we develop an energy-aware allocation policy that aims at maximizing the lifetime of all the connected IoT devices, whilst guaranteeing that applications’ Quality of Service (QoS) requirements are met. To this aim, we formally define an IoT service allocation problem as a non-linear Generalized Assignment Problem (GAP). We then develop a time-efficient heuristic algorithm to solve the problem, which is shown to find near-optimal solutions by exploiting the availability of equivalent IoT services provided by multiple IoT devices, as expected especially in the case of massive IoT deployments