Giacomo Tanganelli

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). 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 (according to a Things-as-a-Service model) regardless of the technology and the physical infrastructure they belong to.

CoAPthon: Easy development of CoAP-based IoT applications with Python

The Internet of Things (IoT) vision foresees billions of devices seamlessly integrated into information systems. In this context, the Constrained Application Protocol (CoAP) has been defined as a technology enabler to allow applications to interact with physical objects. In this work we present CoAPthon, an open-source Python-based CoAP library, which aims at simplifying the development of CoAP-enabled IoT applications. The library offers software developers a simple and easy-to-use programming interface to exploit CoAP as a communication protocol for rapid prototyping and deployment of IoT systems. The CoAPthon library is fully compliant with the CoAP RFC and implements in addition popular extensions such as the block-wise transfer and resource observing.

Energy-Efficient QoS-aware Service Allocation for the Cloud of Things

Cloud computing is a key enabler for the development and deployment of large-scale IoT service platforms. The integration into such platforms of different sensing and actuating systems will imply the availability of many similar IoT services with common functionalities though with different QoS and cost. A cloud-based IoT platform can then benefit from implementing QoS-aware service selection algorithms to match application demand to IoT services, whilst guaranteeing to meet the respective QoS requirements. Such algorithms must however take into account that IoT service providers are usually constrained devices with limited computation, storage and energy capabilities. In this work we formulate the QoS-aware service selection problem for IoT cloud platforms as an integer optimization problem, whose solution minimizes the energy consumption so as to maximize the lifetime of battery-powered devices, whilst guaranteeing the fulfillment of real-time QoS requirements. We then propose a computationally efficient heuristic algorithm to solve the problem, and show through extensive numerical analysis that it is able to find solutions very close to the optimal one in all considered scenarios.

A distributed architecture for discovery and access in the internet of things

A complete, though small-scale, end-to-end architecture for the Internet of Things (IoT) is demonstrated by means of a test-bed including: smart objects (both clients and servers) with limited capabilities and proxy devices which allow the latter to connect to a core network, where a peer-to-peer (P2P) overlay is set up and maintained for automatic discovery of resources and highly scalable access. The Constrained Application Protocol (CoAP) is used by smart objects to enable Machine-to-Machine (M2M) communications following a resource-oriented approach. Business logic and human interactions with the smart objects for aggregation and visualization, respectively, are also demonstrated, including Android mobile applications.

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.

A framework for QoS negotiation in things-as-a-service oriented architectures

The integration of existing heterogeneous vertical M2M systems into a new horizontal platform has been recognized as a key factor to boost the development of the Internet of Things vision. In this scenario, the European project BETaaS (Building the Environment for the Things as a Service) aims at developing a framework to enable integration of different M2M systems exposing physical objects to applications through a novel service-oriented interface, the Things as a Service model. Quality of Service support is a non-functional requirement of paramount importance for applications with stringent requirements which has been included by design in the BETaaS platform. In this paper the negotiation framework adopted in BETaaS to allow Machine-to-Machine (M2M) applications to negotiate the required Service Level Agreement is presented. The goal is to expose to applications a standard interface which can be exploited to negotiate the desired QoS selecting one of the service classes defined by the platform.

Edge-Centric Distributed Discovery and Access in the Internet of Things

Massive diffusion of constrained devices communicating through low-power wireless technologies in the future Internet of Things (IoT) will require in many scenarios the deployment of IoT gateways to allow applications to discover and access IoT resources. In this context, Fog/Edge computing will represent an opportunity to deploy IoT gateways in proximity of IoT domains, meeting the requirements of applications needing low-latency interactions with devices. In this paper, we present an edge-centric distributed architecture to provide resource discovery and access services to IoT applications. The proposed approach leverages the CoRE Resource Directory interface and the Constrained Application Protocol (CoAP) to expose a standard interface for global discovery and access. Multiple IoT gateways are federated through a peer-to-peer overlay implemented by a distributed hash table, which is exploited to share the information on IoT resources available across multiple domains. The proposed solution is validated by means of a small-scale prototype, and extensively evaluated through emulation in large scale deployment in comparison to a centralized Cloud-based approach. Experimental results demonstrated that the proposed approach guarantees lower latencies than a centralized solution and can ensure scalability for small to medium sized deployments.

CoAP Proxy Virtualization for the Web of Things

The future Web of Things (WoT) foresees a web in which applications can seamlessly access physical objects through the same REST interface used today to access web services. A key enabler of this shift is the Constrained Application Protocol (CoAP), a redesign of the popular HTTP protocol that aims at supporting resource-constrained devices for Machine-to-Machine applications. In this work we propose a proxy virtualization framework to support scalability and easy implementation of custom functionalities in large WoT deployments. The functionalities offered by a CoAP proxy are exploited to transparently decouple applications from servers and to guarantee the implementation of custom policies and functionalities through virtualization techniques. A solution based on Linux Containers is implemented in a real test bed made of off-the-shelf hardware and open-source software, demonstrating the feasibility of the proposed design. Experimental results have shown that the response time is highly improved by our solution thanks to central coordination of concurrent requests from different virtual proxy instances. Moreover, to highlight the potential of the proposed frame-work, a priority-based Quality of Service policy is also implemented and evaluated.

D2D Communications for Large-Scale Fog Platforms: Enabling Direct M2M Interactions

To many, fog computing is considered the next step beyond the current centralized cloud that will support the forthcoming Internet of Things (IoT) revolution. While IoT devices will still communicate with applications running in the cloud, localized fog clusters will appear with IoT devices communicating with application logic running on a proximate fog node. This will add proximity-based machine-to-machine (M2M) communications to standard cloud-computing traffic, and it calls for efficient mobility management for entire fog clusters and energy-efficient communication within them. In this context, long-term evolution-advanced (LTE-A) technology is expected to play a major role as a communication infrastructure that guarantees low deployment costs, native mobility support, and plug-andplay seamless configuration.

Highlighting Some Shortcomings of the CoCoA+ Congestion Control Algorithm

The Constrained Application Protocol (CoAP) is expected to be the de-facto standard application protocol for the future Internet of Things (IoT). Future IoT devices will be interconnected by networks characterized by high packet error rates and low throughput. For this reason, congestion control will be crucial to ensure proper and timed communication in these networks. In this context, CoCoA+, an advanced congestion control for CoAP, is currently under standardization. In this work, we present a critical analysis of CoCoA+ by means of simulation, and highlight some of its shortcomings and pitfalls. We considered a typical scenario with an increasing traffic load due to an increasing number of CoAP requests. We show how CoCoA+ may be characterized by many spurious retransmissions at some offered loads close to congestion.