LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft

Developing front-end Web 2.0 technologies to access services, content and things in the future Internet

The future Internet is expected to be composed of a mesh of interoperable web services accessible from all over the web. This approach has not yet caught on since global user?service interaction is still an open issue. This paper states one vision with regard to next-generation front-end Web 2.0 technology that will enable integrated access to services, contents and things in the future Internet. In this paper, we illustrate how front-ends that wrap traditional services and resources can be tailored to the needs of end users, converting end users into prosumers (creators and consumers of service-based applications). To do this, we propose an architecture that end users without programming skills can use to create front-ends, consult catalogues of resources tailored to their needs, easily integrate and coordinate front-ends and create composite applications to orchestrate services in their back-end. The paper includes a case study illustrating that current user-centred web development tools are at a very early stage of evolution. We provide statistical data on how the proposed architecture improves these tools. This paper is based on research conducted by the Service Front End (SFE) Open Alliance initiative

Developing IoT applications in the Fog:a distributed dataflow approach

In this paper we examine the development of IoT applications from the perspective of the Fog Computing paradigm, where computing infrastructure at the network edge in devices and gateways is leverage for efficiency and timeliness. Due to the intrinsic nature of the IoT: heterogeneous devices/resources, a tightly coupled perception-action cycle and widely distributed devices and processing, application development in the Fog can be challenging. To address these challenges, we propose a Distributed Dataflow (DDF) programming model for the IoT that utilises computing infrastructures across the Fog and the Cloud. We evaluate our proposal by implementing a DDF framework based on Node-RED (Distributed Node-RED or D-NR), a visual programming tool that uses a flow-based model for building IoT applications. Via demonstrations, we show that our approach eases the development process and can be used to build a variety of IoT applications that work efficiently in the Fog

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

A wot-based method for creating digital sentinel twins of iot devices

The data produced by sensors of IoT devices are becoming keystones for organizations to conduct critical decision-making processes. However, delivering information to these processes in real-time represents two challenges for the organizations: the first one is achieving a constant dataflow from IoT to the cloud and the second one is enabling decision-making processes to retrieve data from dataflows in real-time. This paper presents a cloud-based Web of Things method for creating digital twins of IoT devices (named sentinels).The novelty of the proposed approach is that sentinels create an abstract window for decision-making processes to: (a) find data (e.g., properties, events, and data from sensors of IoT devices) or (b) invoke functions (e.g., actions and tasks) from physical devices (PD), as well as from virtual devices (VD). In this approach, the applications and services of decision-making processes deal with sentinels instead of managing complex details associated with the PDs, VDs, and cloud computing infrastructures. A prototype based on the proposed method was implemented to conduct a case study based on a blockchain system for verifying contract violation in sensors used in product transportation logistics. The evaluation showed the effectiveness of sentinels enabling organizations to attain data from IoT sensors and the dataflows used by decision-making processes to convert these data into useful information