1,720,961 research outputs found
Differentiated service/data migration for edge services leveraging container characteristics
Full text linkThe Multi-access Edge Computing (MEC) and Fog Computing paradigms are enabling the opportunity to have middleboxes either statically or dynamically deployed at network edges acting as local proxies with virtualized resources for supporting and enhancing service provisioning in edge localities. However, migration of edge-enabled services poses significant challenges in the edge computing environment. In this paper, we propose an edge computing platform architecture that supports service migration with different options of granularity (either entire service/data migration, or proactive application-aware data migration) across heterogeneous edge devices (either MEC-based servers or resource-poor Fog devices) that host virtualized resources (Docker Containers). The most innovative elements of the technical contribution of our work include i) the possibility to select either an application-agnostic or an application-aware approach, ii) the possibility to choose the appropriate application-aware approach (e.g., based on data access frequencies), iii) an automatic edge services placement support with the aim of finding a more effective placement with low energy consumption, and iv) the in-lab experimentation of the performance achieved over rapidly deployable environments with resource-limited edges such as Raspberry Pi devices
Machine Learning for Predictive Diagnostics at the Edge: An IIoT Practical Example
Full text linkEdge Computing is becoming more and more essential for the Industrial Internet of Things (IIoT) for data acquisition from shop floors. The shifting from central (cloud) to distributed (edge nodes) approaches will enhance the capabilities of handling real-time big data from IoT. Furthermore, these paradigms allow moving storage and network resources at the edge of the network closer to IoT devices, thus ensuring low latency, high bandwidth, and location-based awareness. This research aims at developing a reference architecture for data collecting, smart processing, and manufacturing control system in an IIoT environment. In particular, our architecture supports data analytics and Artificial Intelligence (AI) techniques, in particular decentralized and distributed hybrid twins, at the edge of the network. In addition, we claim the possibility to have distributed Machine Learning (ML) by enabling edge devices to learn local ML models and to store them at the edge. Furthermore, edges have the possibility of improving the global model (stored at the cloud) by sending the reinforced local models (stored in different shop floors) towards the cloud. In this paper, we describe our architectural proposal and show a predictive diagnostics case study deployed in an edge-enabled IIoT infrastructure. Reported experimental results show the potential advantages of using the proposed approach for dynamic model reinforcement by using real-time data from IoT instead of using an offline approach at the cloud infrastructure
A layered middleware for ot/it convergence to empower industry 5.0 applications
Full text linkWe are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0 (I5.0) era goes a step beyond, aiming to build cross-border, sustainable, and circular value chains benefiting society as a whole. An enabler of this vision is the integration of data and AI in the industrial decision-making process, which does not exhibit yet a coordination between the Operation and Information Technology domains (OT/IT). This work proposes an architectural approach and an accompanying software prototype addressing the OT/IT convergence problem. The approach is based on a two-layered middleware solution, where each layer aims to better serve the specific differentiated requirements of the OT and IT layers. The proposal is validated in a real testbed, employing actual machine data, showing the capacity of the components to gracefully scale and serve increasing data volumes
An sdn‐enabled architecture for it/ot converged networks: A proposal and qualitative analysis under ddos attacks
Full text linkReal‐time business practices require huge amounts of data directly from the production assets. This new thirst for accurate and timely data has forced the convergence of the traditionally business‐focused information technology (IT) environment with the production‐focused operational technology (OT). Recently, software‐defined network (SDN) methodologies have benefitted OT networks with enhanced situational awareness, centralized configuration, deny‐by-default forwarding rules, and increased performance. What makes SDNs so innovative is the separation between the control plane and the data plane, centralizing the command in the controllers. However, due to their young age, the use of SDNs in the industry context has not yet matured comprehensive SDN‐based architectures for IT/OT networks, which are also resistant to security attacks such as denial‐of‐service ones, which may occur in SDN‐based industrial IoT (IIoT) networks. One main motivation is that the lack of comprehensive SDN‐based architectures for IT/OT networks making it difficult to effectively simulate, analyze, and identify proper detection and mitigation strategies for DoS attacks in IT/OT networks. No consolidated security solutions are available that provide DoS detection and mitigation strategies in IT/OT networks. Along this direction, this paper’s contributions are twofold. On the one hand, this paper proposes a convergent IT/OT SDN‐based architecture applied in a real implementation of an IT/OT support infrastructure called SIRDAM4.0 within the context of the SBDIOI40 project. On the other hand, this paper proposes a qualitative analysis on how this architecture works under DoS attacks, focusing on what the specific problems and vulnerabilities are. In particular, we simulated several distributed denial-of‐service (DDoS) attack scenarios within the context of the proposed architecture to show the minimum effort needed by the attacker to hack the network, and our obtained experimental results show how it is possible to compromise the network, thus considerably worsening the performance and, in general, the functioning of the network. Finally, we conclude our analysis with a brief description on the importance of employing machine learning approaches for attack detection and for mitigation techniques
Optimal Placement of Micro-services Chains in a Fog Infrastructure
Full text linkFog computing emerged as a novel approach to deliver micro-services that support innovative applications. This paradigm is consistent with the modern approach to application development, that leverages the composition of small micro-services that can be combined to create value-added applications. These applications typically require the access from distributed data sources, such as sensors located in multiple geographic locations or mobile users. In such scenarios, the traditional cloud approach is not suitable because latency constraints may not be compatible with having time-critical computations occurring on a far away data-center; furthermore, the amount of data to exchange may cause high costs imposed by the cloud pricing model. A layer of fog nodes close to application consumers can host pre-processing and data aggregation tasks that can reduce the response time of latency-sensitive elaboration as well as the traffic to the cloud data-centers. However, the problem of smartly placing micro-services over fog nodes that can fulfill Service Level Agreements is far more complex than in the more controlled scenario of cloud computing, due to the heterogeneity of fog infrastructures in terms of performance of both the computing nodes and inter-node connectivity. In this paper, we tackle such problem proposing a mathematical model for the performance of complex applications deployed on a fog infrastructure. We adapt the proposed model to be used in a genetic algorithm to achieve optimized deployment decisions about the placement of micro-services chains. Our experiments prove the viability of our proposal with respect to meeting the SLA requirements in a wide set of operating conditions
MEFS: Mobile edge file system for edge-assisted mobile apps
No full textComputation offloading is employed by mobile apps running over resource-constrained devices to leverage the cloud in overcoming their resource limits. The advent of the Multi-access Edge Computing (MEC) paradigm further extends the potential opportunities of mobile-cloud offloading, allowing new service provisioning scenarios, such as mobile gaming and multimedia, where responsiveness of mobile devices at the network edge significantly benefits from low latency interactions. However, state-of-the-art offloading platforms for MEC architectures have not addressed the technical challenge of supporting specific file systems for this MEC-enabled class of applications, with components running at three hosting environments, i.e., mobile, edge, and cloud. This paper proposes the Mobile Edge File System (MEFS), an application-level distributed file system designed to be highly resilient and able to efficiently maintain consistency among the mobile, edge, and cloud entities. MEFS supports application handoff through live migration as end devices move between edges. The cloud transparently helps with recovery from faulty edge nodes or in the case of unavailability of edges in the user's proximity. We implemented a MEFS prototype in Android along with MEFS-based MEC-enabled mobile apps. The experimental results show how MEFS can achieve low latency and low overhead
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
MSN: A Playground Framework for Design and Evaluation of MicroServices-Based sdN Controller
Full text linkSoftware-defined networking decouples control and data plane in softwarized networks. This allows for centralized management of the network, but complete centralization of the controller functions raises potential issues related to failure, latency, and scalability. Distributed controller deployment is adopted to optimize scalability and latency problems. However, existing controllers are monolithic, resulting in code inefficiency for distributed deployment. Some seminal ongoing efforts have been proposed with the idea of disaggregating the SDN controller architecture into an assembly of various subsystems, each of which can be responsible for a certain controller task. These subsystems are typically implemented as microservices and deployed as virtual network functions, in particular as Docker Containers. This enables flexible deployment of controller functions. However, these proposals (e.g., μONOS) are still in their early stage of design and development, so that a full decomposition of the SDN controller is not been available yet. To fill that gap, this article derives some important design guidelines to decompose an SDN controller into a set of microservices. Next, it also proposes a microservices-based decomposed controller architecture, foreseeing communications issues between the controller sub-functions. These design and performance considerations are also proven via the implementation of the proposed architecture as a solution, called Micro-Services based SDN controller (MSN), based on the Ryu SDN controller. Moreover, MSN includes different network communication protocols, such as gRPC, WebSocket, and REST-API. Finally, we show experimental results that highlight the robustness and latency of the system on a networking testbed. Collected results prove the main pros and cons of each network communication protocol and an evaluation of our proposal in terms of system resilience, scalability and latency
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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