The Internet of Things (IoT) has transformed how everyone interacts with the environment. Over the past few years, this field has experienced exponential growth , which has led to difficulties in efficiently managing the data generated by these devices and has posed new challenges for cloud infrastructures. As the number of devices involved increases, latency and bandwidth issues become increasingly critical in these systems. To address these issues, architectures such as fog and edge computing emerged that proposed bringing information processing and storage closer to the data generators. This reduced the distance the data had to travel, thereby improving latency and bandwidth and reducing potential bottlenecks. These architectures have evolved into a new concept known as the computing continuum. This approach, based on dynamic collaboration between the cloud, fog, and edge, creates a continuous infrastructure of computational resources that optimizes data processing at each network level as needed. The computing continuum presents important challenges that need to be addressed at multiple levels: the application/algorithmic level (programming paradigms), middleware level (deployment, execution, scheduling, monitoring, data storage, transfer, processing, and analysis), and resource management level. The work introduced in this article addresses the challenges related to the efficient storage and transfer of data between the different levels across the computing continuum. We propose a distributed and parallel file system for this kind of infrastructure that can be used transparently at all levels. This file system can be deployed at different levels (fog, edge, and cloud) hierarchically, allowing the execution of applications at each level and efficient data transfer between these levels and the cloud. It also facilitates the development of IoT applications capable of efficiently transferring data by using typical file system calls. The work presents and validates this data storage system at different levels: two IoT devices (Raspberry Pi 1 & 4), an emulated environment, a controlled simulation, and a performance analysis with Amazon Cloud Services.

This article introduces CREATOR-Sail, a RISC-V web simulator that uses Sail as the instruction specification language. This enables binaries written in assembly language to be compiled, executed and debugged while simulating the complete RISC-V architecture and instruction set. The simulator can now simulate both 32-bit and 64-bit RISC-V variants and supports the simulation of the complete instruction set specified in the official standard, including vector and privileged instructions. Both variants include a cache memory module to increase the capacity for architecture simulation, mimicking a real processor. The aim of this work is to provide an industrial-level solution for companies and research groups, offering them a tool with which to customize the environment for their own purposes. The simulator includes an assembly compiler and a debugging module, making it more user-friendly and intuitive than other simulators. All simulator components have been integrated into the web environment using WebAssembly, which enables the execution of native code in a web environment and provides an execution performance similar to that of native applications compared to applications implemented only in JavaScript. The source code of web simulator is available at https://github.com/creatorsim/creator . The web simulator is available at https://creatorsim.github.io/creator/ .

This work introduces an exhaustive evaluation, including both benchmarks and real-world data-intensive applications, performed in MareNostrum 4 and HPC4AI Laboratory supercomputers using the Expand Ad-Hoc file system. Expand Ad-Hoc is an ad-hoc file system that dynamically virtualizes the local storage available on compute nodes (i.e., SSD, SHM, etc.) into a fast storage volume to reduce congestion on parallel file systems used as backends in High-Performance Computing (HPC) environments. The main contributions of this work include the design of a new ad-hoc parallel file system, called Expand Ad-Hoc , compatible with POSIX and MPI-IO, and an exhaustive and comprehensive evaluation of Expand. The evaluation compares the performance obtained using IOR and DLIO benchmarks and Nek5000 and Remote Sensing real-world applications on Expand Ad-Hoc , GekkoFS, GPFS, and BeeGFS, showing satisfactory results proving that Expand Ad-Hoc can be used in HPC environments to improve the I/O performance of data-intensive applications transparently.

Abstract In the last years, applications related to Artificial Intelligence and big data, among others, have been involved. There is a need to improve I/O operations to avoid bottlenecks in accessing a larger amount of data. For this purpose, the Expand Ad-Hoc parallel file system is being designed and developed. Since these applications have very long execution times, fault tolerance mechanisms in the file system are necessary to allow them to continue running in the presence of failures. This work introduces a fault-tolerant design based on data replication for the Expand Ad-Hoc parallel file system and an initial evaluation conducted on the HPC4AI Laboratory supercomputer in Torino. The evaluation of Expand Ad-Hoc with fault-tolerant found that, despite data replication, its performance and scalability are generally better than those of other parallel file systems without fault-tolerant.

An Ad-Hoc File System dynamically virtualizes storage on compute nodes into a fast storage volume to reduce congestion on parallel file systems used as backends in HPC environments and improve data locality. This paper presents Expand Ad-Hoc, a version of the Expand parallel file system, for use as an Ad-Hoc storage system for HPC environments. Such an update seeks to take better advantage of new storage technologies (on SSDs local to nodes, for example) and to adapt to new demands of current parallel applications (e.g., optimizing data access by analyzing data locality). The paper describes the new system’s features and presents a first evaluation comparing the performance of Expand with another Ad-Hoc File System (GekkoFS), and GPFS. The first results are quite satisfactory and demonstrate the good performance of Expand as an Ad-Hoc storage system.

In recent years, the devices that make up the Internet of Things (IoT) paradigm have been increasing in number and complexity as different layers of network computing, such as Cloud, Edge and Fog Computing, have emerged. Thanks to these latest paradigms and their different types of communications, it has been possible to reduce and distribute the computational load on the network. However, to build these infrastructures and reduce the cost, it is necessary to use a simulation platform to model these environments and analyze their behavior (power consumption, CPU usage, bandwidth, etc.) beforehand. An essential aspect of simulators is scalability, the ability to add new components and simulate large infrastructures without compromising the performance of the simulator. Many existing simulators, as will be discussed in this article, cannot scale adequately as new elements are added to the system. Furthermore, in these environments, it is useful to simulate mobile devices and to know the location of these devices for the development and analysis of new algorithms. To solve these problems, this article presents and describes the ENIGMA simulator. ENIGMA is a scalable simulator of Edge, Fog and Cloud computing infrastructures, which allows to efficiently simulate a large number of devices and elements and to analyze different characteristics (CPU usage, power consumption, network bandwidth, application execution time, etc.). Its objective is to analyze new infrastructures and algorithms. ENIGMA also includes support for including mobile devices and an API to integrate their visualization in graphical maps. The article presents an evaluation to compare the scalability of ENIGMA with other state-of-the-art simulators and different use cases that illustrate its operation.

This article introduces CREATOR, a new generic simulator for assembly programming, developed by the ARCOS group at the UC3M. CREATOR is a new, highly intuitive, and portable simulator that runs from a web browser (no installation needed). This simulator comes with the MIPS32 and RISC-V (32IMF) instruction set. Nevertheless, CREATOR allows, from the simulator itself, to edit and define other instruction sets (instructions, format, registers, etc.). Even more, CREATOR allows the definition of the parameter passing convention to be used in the instruction set. Once each particular instruction set (MIPS32, ARM, RISCV, etc.) has been defined, students can use CREATOR to edit, compile, execute and debug programs written in the associated assembler. The simulator also allows checking that the developed programs comply with the parameter passing convention defined for the instruction set. CREATOR lets us create subroutine libraries that can be loaded and linked to other assembly programs developed in the simulator. All CREATOR features allows teacher to design and deploy practical laboratories more adapted to the desired teaching goals. That improves the teaching experience of the assembly language frequently used in different subjects such as Computer Architecture or Computer Structure. The experience of its use has been very positive in the past courses for students and teachers in both the Universidad Carlos III de Madrid (UC3M) and the Universidad Castilla la Mancha (UCLM).