Distributed Software Platform Research Articles

A resources ecosystem for digital and heritage-led holistic knowledge in rural regeneration

This paper presents a digital resources ecosystem prototype of integrated tools and resources to support heritage-led regeneration of rural regions, thanks to a deeper understanding of the complexity of cultural natural landscapes throughout their historical and current development. The ecosystem is conceived as a distributed software platform establishing data ecosystem and open standards for the management of information, aimed at providing different services and applications to address the needs of the various end-users identified. The platform has been conceived and realised in the framework of a Horizon 2020 research project, with a view to building a set of holistic knowledge about rural regions and their cultural and natural heritage and making it available for long-lasting heritage-led territorial processes of change. It is the product of a multidisciplinary collaboration amongst heritage, digital humanities and ICTs experts, and combines data and methodologies from a range of approaches to humanities together with the customisation of effective digital tools. It has been designed for deployment also in cloud systems compliant with the Infrastructure-as-a-Service paradigm. All data is Findable, Accessible, Interoperable, Reusable (FAIR data). It hosts and integrates different tools, making the data gathered with/for local stakeholders usable and making the same data re-usable within the tools’ functions, generating integrated heritage knowledge. It comprises data on 19 rural pilot territories, where the tools and their integration have been developed and tested, while 62 more are partially included as additional territories which participate in certain activities within the project. The main testers for this platform and its functions are the local stakeholders of these territories. The paper describes and analyses the platform and its impact, discussing the integration of tools as an innovative approach that goes beyond the use of individual tools in shaping a multidimensional vision. It also offers an analysis of the potential of an integrated digital ecosystem in evidence-based and place-based regeneration strategies. Some reflections for developments and cooperation during the pandemic are also presented.

Distributed AI embedded cluster for real-time video analysis systems with edge computing

Herein, on the basis of a distributed AI cluster, a real-time video analysis system is proposed for edge computing. With ARM cluster server as the hardware platform, a distributed software platform is constructed. The system is characterized by flexible expansion, flexible deployment, data security, and network bandwidth efficiency, which makes it suited to edge computing scenarios. According to the measurement data, the system is effective in increasing the speed of AI calculation by over 20 times in comparison with the embedded single board and achieving the calculation effect that matches GPU. Therefore, it is considered suited to the application in heavy computing power such as real-time AI computing.

The Research on Hadoop and Cloud Computing-Based Mass Data Storage Model of Computation

Cloud computing as a new business model that allows the user according to their needs using the resource pool which formed by data on a large number of computers. Hadoop, as the distributed software platform is the most widely use of cloud computing. It can run applications on the computer cluster which formed by a large number of low-cost hardware devices, and turn the calculation into data completely then deal with massive data. This article describes the basic framework of Hadoop and the advantages of dealing with massive data, the concept of cloud computing, and research of computing and storage model which base on Hadoop and cloud computing.

High Performance Internet Traffic Generators

In the networking field, traffic generator platforms are of a paramount importance. This paper deals with the description of a distributed software platform for synthetic traffic generation over IPv4/v6 networks, called D-ITG (Distributed Internet Traffic Generator). We point our attention on the original architectural choices and evaluate the performance achieved by the platform. D-ITG supports several protocols and many traffic patterns. We tested our generation platform over different scenarios and compared it to many of the currently available, and most widely adopted, traffic generators. We found that D-ITG offers enhanced functionalities and improved performance.

Real-time performance monitoring and anomaly detection in the Internet: An adaptive, objective-driven, mix-and-match approach

Algorithms for real-time performance management and adaptive fault/anomaly detection in Internet protocol (IP) networks and services have been developed, and a corresponding real-time distributed software platform has been implemented. These algorithms automatically and adaptively detect “soft” faults or anomalies (performance degradations) in IP networks and services, enabling timely correction of network exceptions before failures occur and services are compromised and thereby achieving proactive network and service management. Further, these algorithms are implemented as a reliable, fully distributed real-time software platform — the network/service anomaly detector (NSAD) — with the following features. First, it provides a flexible platform on which preconstructed monitoring and detection components can be mixed, matched, and distributed to form a wide range of application-specific NSADs and performance monitors. Second, NSAD and its components can auto-recover in real time, making it a reliable system for persistent monitoring of networks and their services. Third, anomaly detection is performed on raw network observables — for example, performance data such as management information base-2 (MIB2) and remote monitor-1/2 (RMON1/2) variables — and algebraic functions of these observables (objective functions), thereby enabling objective-driven anomaly detection of wide range and high sensitivity. Fourth, controlled testing (with anomalies injected a priori into a test network) demonstrates that NSAD can detect anomalies reliably in IP networks. Thus, NSAD provides a powerful framework/platform for automatic, proactive fault/anomaly detection and performance management in IP networks and services.

Scene Reconstruction and Robot Navigation Using Dynamic Fields

In this paper, we present an approach to autonomous robot navigation in an unknown environment. We design and integrate algorithms to reconstruct the scene, locate obstacles and do short-term field-based path planning. The scene reconstruction is done using a region matching flow algorithm to recover image deformation and structure from motion to recover depth. Obstacles are located by comparing the surface normal of the known floor with the surface normal of the scene. Our path planning method is based on electric-like fields and uses current densities that can guarantee fields without local minima and maxima which can provide solutions without the need of heuristics that plague the more traditional potential fields approaches. We implemented a modular distributed software platform (FBN) to test this approach and we ran several experiments to verify the performance with very encouraging results.

Designing a system infrastructure for distributed programs

A distributed program is one that consists of several components distributed over a network of computers. The reliability of a distributed program is strongly affected by the behaviour of the underlying distributed system software platform. One of the most fundamental issues in improving the reliability of distributed programs is to provide a better environment within which these programs operate. This paper investigates the functional requirement of the infrastructure of a distributed operating system in anticipation of the goal of improving the reliability of distributed programs. It identifies the major problems that make the task of achieving high software quality hard to accomplish, then suggests possible functionality that is advisable for the system infrastructure to provide. The design and implementation of the new distributed system service are then described.

PVM-based parallel computing: a case study on power plant simulation

Parallel computing architectures are a promising answer to the growing needs of computing power in many application fields. This model can be easily fitted to applications that are structured as a collection of weakly coupled processes. Every process evolves independently and synchronises periodically with the others by exchanging relatively small messages. The power plant simulators developed at our Research Center are an example of this kind of application. Due to the absence of standards in this field, our activity was focused upon the implementation of a distributed software platform, open to heterogeneous systems, and to be used as a reference for our future developments. In this paper, after a brief description of the simulation environment, we describe a first parallel version based on a Transputer network and then the current evolution based on a network of heterogeneous workstations.