Industrial Edge Cloud for the Smart Factory

ABSTRACT

Industrial Edge Cloud in the Smart Factories

Cloud Computing has been used extensively for a number of purposes over the past few years. From everyday tasks like reading emails and watching videos to factory automation and device control, it has changed where data is processed and how it is accessed. However, the increasing number of connected devices brings problems such as low Quality of Service (QoS) due to infrastructure resources and high latency due to bandwidth constraints. The current trend to solve the problems posed by Cloud Computing is to perform computation as close to the field level as possible. This paradigm is called Edge Computing. There are several proposed architectures for Edge Computing, but so far there are no standards accepted by the community or industry. In addition, there is no common agreement on what the Edge Computing architecture physically looks like. In this paper, we describe the Industrial Edge Cloud, explain what Industrial Edge Cloud architecture looks like, what its requirements are, and what its capabilities are. We also define the key features that an Edge Node should support. Furthermore, we give a short insight into the challenges that come along with the networking of machines and plants and that it is not sufficient to just “secure” machines or plants, but that new interfaces of cybersecurity with operation, maintenance, safety etc. arise, which require corresponding security work.

Authors

• Volkan Gezer, Carsten Harms, Deutsches Forschungszentrum für Künstliche Intelligenz
• Carsten Brüggemann, Pfalzkom
• Michael Pfeifer, TÜV Süd
• Andreas Michael, TÜV Süd
• Simon Althoff, Weidmüller
• Torsten Runge, Deutsche Telekom/T-Systems
• Keran Sivalingam, Technologie-Initiative SmartFactory KL e.V.
• Martin Ruskowski, Deutsches Forschungszentrum für Künstliche Intelligenz

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Development and selection of suitable use cases and KPIs for the successful introduction of new high technology using the example of “Function-as-a-Service”

ABSTRACT

What distinguishes successful high-tech projects from failed ones? – Often not the quality of the technology itself, but rather misunderstood, unclear objectives, poor communication and often isolated project management.
As part of the EU research project “Physics” and the introduction of Function-as-a-Service at three pioneers from the fields of smart manufacturing, healthcare and agriculture, this paper aims to address an essential and often overlooked component of the successful introduction of high technology.
An interactive approach is introduced that explains how the success criterion of use case development can be positively designed, what important role stakeholder analysis plays and how direct and indirect business benefits can be identified and linked. Furthermore, the construction of suitable KPIs is discussed, which measure achievable goals and thus counteract wrong decisions. Finally, a list of individual problems with recommendations for practical implementation is given.

Authors

• Niklas, N.F., Franke
• Florian, F.M., Mohr
• André, A.H., Hennecke

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The post Entwicklung und Auswahl geeigneter Use Cases und KPIs zur erfolgreichen Einführung neuer Hochtechnologie am Beispiel von “Function-as-a-Service” appeared first on PHYSICS.

Conference: 2023 14TH IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

ABSTRACT

Serverless computing has reshaped the cloud com- puting landscape by offering benefits such as auto-scalability, streamlined operational management, and granular billing. As its adoption grows, challenges related to performance optimization in hybrid architectures combining private servers and public cloud clusters have emerged. Central to these challenges are achieving optimal response latency and balancing performance and cost. To address these challenges, this paper introduces an adaptive routing service specifically designed for hybrid environments, proficient in leveraging real-time function metrics. Our proposed service pivots on three integral components: a monitor that captures performance metrics and raises alarms for predefined anomalies; a forecaster that predicts function latency across clusters, which includes wait and execution times, and produces request distributions for each cluster to equalize the overall function latency; and a router then processes incoming requests, taking cues from the forecaster’s predictions. Notably, based on user-defined objectives, the forecaster can be directed to either minimize latency or optimize execution costs. Comprehen- sive evaluations on AWS and Azure using Apache OpenWhisk clusters showcase our approach’s effectiveness, yielding a 9% improvement in average latency, a 45% decrease in standard deviation latency and a 17% cost reduction compared to con- ventional 50-50 routing. The advantages of elevated monitoring frequency are also illuminated, emphasizing quicker convergence times.

Authors

• Georgios Fatouros
• George Kousiouris
• Georgios Makridis
• John Soldatos
• Michael Filippakis
• Dimosthenis Kyriazis

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The post Enhanced Routing for Serverless Functions: A Performance-based Approach with Runtime Adaptation appeared first on PHYSICS.

Conference: 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)

ABSTRACT

The integration of cloud computing and Internet of Things (IoT) technologies has brought significant advancements in the agriculture domain. However, the implementation of such systems often requires significant time and resources, making it challenging for smart agriculture providers to offer optimized yet affordable services for small and medium-sized farmers at scale. Low-code development platforms can be a viable solution to address these challenges, enabling non-experts to adapt or enhance existing applications with minimal coding. This paper presents a low-code approach to enhance smart agriculture scenarios with pattern-oriented functionality blocks for cloud/edge collaboration. It highlights the usage of a pattern collection for redesigning the implementation of smart agriculture applications that can enhance the data collection process as well as real-time decision-making and efficient resource management in the continuum. The effectiveness of the presented approach is demonstrated through the implementation of a case study in smart agriculture greenhouses. Evaluation results show that this approach can significantly reduce the time and effort required to deploy smart agriculture applications and provide data resilience.

Authors

• Georgios Fatouros
• George Kousiouris
• Theophile Lohier
• Georgios Makridis
• Ariana Polyviou
• John Soldatos
• Dimosthenis Kyriazis

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The post Enhancing Smart Agriculture Scenarios with Low-code, Pattern-oriented functionalities for Cloud/Edge collaboration appeared first on PHYSICS.

ABSTRACT

This paper presents a comprehensive collection of reusable artifacts for addressing security and privacy issues in the context of flow-based programming in Function-as-a-Service (FaaS) environments. With the rapid adoption of FaaS platforms, it becomes important to guarantee the security and privacy of applications. The presented artifacts incorporate a wide variety of nodes and techniques into the popular Node-RED architecture. They intend to improve the security and privacy of applications by addressing critical aspects such as secure data flow management, code authenticity and validation, access control mechanisms, and runtime monitoring and anomaly detection. Using these artifacts, developers can construct more robust and resilient applications in FaaS environments while mitigating potential security and privacy risks.

Authors

• Thodoridis Ioannidis
• Vaios Bolgouras
• Christos Xenakis
• Ilias Politis

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The post Securing the Flow: Security and Privacy Tools for Flow-based Programming appeared first on PHYSICS.

ABSTRACT

In this paper we report our experiences from the migration of an AI model inference process, used in the context of an E-health platform to the Function as a Service model. To that direction, a performance analysis is applied, across three available Cloud or Edge FaaS clusters based on the open source Apache Openwhisk FaaS platform. The aim is tExperimental data can aid in gaining insights about a system operation, as well as determining critical aspects of a modelling or simulation process. In this paper, we analyze the data acquired from an extensive experimentation process in a serverless Function as a Service system (based on the open source Apache Openwhisk) that has been deployed across 3 available cloud/edge locations with different system setups. Thus, they can be used to model distribution of functions through multi-location aware scheduling mechanisms. The experiments include different traffic arrival rates, different setups for the FaaS system, as well as different configurations for the hardware and platform used. We analyse the acquired data for the three FaaS system setups and discuss their differences presenting interesting conclusions with relation to transient effects of the system, such as the effect on wait and execution time. We also demonstrate interesting trade-offs with relation to system setup and indicate a number of factors that can affect system performance and should be taken under consideration in modelling attempts of such systems.

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The post Empirical Investigation of Factors influencing Function as a Service Performance in Different Cloud/Edge System Setups appeared first on PHYSICS.

Abstract

The ability to split applications across different locations in the continuum (edge/cloud) creates needs for In this paper we report our experiences from the migration of an AI model inference process, used in the context of an E-health platform to the Function as a Service model. To that direction, a performance analysis is applied, across three available Cloud or Edge FaaS clusters based on the open source Apache Openwhisk FaaS platform. The aim is to highlight differences in performance based on the characteristics of each cluster, the request rates and the parameters of Openwhisk. The conclusions can be applied for understanding the expected behavior of the inference function in each of these clusters as well as the effect of the Openwhisk execution model. Key observations and findings are reported on aspects such as function execution duration, function sizing, wait time in the system, network latency and concurrent container overheads for different load rates. These can be used to detect in a black box manner capabilities of unknown clusters, guide or fine-tune performance models as well as private cloud FaaS deployment setup.

Authors

• George Kousiouris
  
• Aristodemos Pnevmatikakis

The post Performance Experiences From Running An E-health Inference Process As FaaS Across Diverse Clusters appeared first on PHYSICS.

Abstract

The ability to split applications across different locations in the continuum (edge/cloud) creates needs for application break down into smaller and more distributed chunks. In this realm the Function as a Service approach appears as a significant enabler in this process. The paper presents a visual function and workflow development environment for complex FaaS (Apache OpenwhisK) applications. The environment offers a library of pattern based and reusable nodes and flows while mitigating function orchestration limitations in the domain. Generation of the deployable artefacts, i.e. the functions, is performed through embedded DevOps pipelines. A range of annotations are available for dictating diverse options including QoS needs, function or data locality requirements, function affinity considerations etc. These are propagated to the deployment and operation stacks for supporting the cloud/edge interplay. The mechanism is evaluated functionally through creating, registering and executing functions and orchestrating workflows, adapting typical parallelization patterns and an edge data collection process.

Authors

• George Kousiouris

• Szymon Ambroziak

• Blazej Zarzycki

• Domenico Costantino

• Stylianos Tsarsitalidis

• Vasileios Katevas

• Alessandro Mamelli

• Teta Stamati

The post A Pattern-based Function and Workflow Visual Environment for FaaS Development across the Continuum appeared first on PHYSICS.

Abstract

This paper focuses on Internet of Things (IoT) architectures and knowledge generation out of streams of events as the primary elements concerning the creation of user-centric IoT services. We provide a general, symmetrical IoT architecture, which enables two-way bidirectional communication between things and users within an application domain. We focus on two main components of the architecture (i.e., Event Engine and Process Engine) that handle event transformation by implementing parametric Complex Event Processing (CEP). More specifically, we describe and implement the transformation cycle of events starting from raw IoT data to their processing and transformation of events for calculating information that we need in an IoT-enabled application context. The implementation includes a library of composite transformations grouping the gradual and sequential steps for transforming basic IoT events into business events, which include ingestion, event splitting, and calculation of measurements’ average value. The appropriateness and possibility of inclusion and integration of the implementation in an IoT environment are demonstrated by providing our implementation for a smart farming application domain with four scenarios that each reflect a user’s requirements. Further, we discuss the quality properties of each scenario. Ultimately, we propose an IoT architecture and, specifically, a parametric CEP model and implementation for future researchers and practitioners who aspire to build IoT applications.

Authors

• Dimitris Gkoulis 
• Cleopatra Bardaki
• George Kousiouris
• Mara Nikolaidou

The post Transforming IoT Events to Meaningful Business Events on the Edge: Implementation for Smart Farming Application appeared first on PHYSICS.

Abstract

Towards enabling the automated and optimized FaaS deployment of applications in a hybrid-cloud setting, the application requirements should be met by comparing them to the capabilities of the available resources of available clusters. To this end, semantic matching between the application characteristics and the individual descriptions of available compute clusters (e.g. from public or private cloud or edge facilities available) is required. In this work, such a system is proposed, namely the Reasoning Framework, which performs semantic matching between application and resource (meta)data and facilitates information sharing among the FaaS platform components lever- aging Knowledge Graphs, ontology technologies, and semantic reasoning. The proposed system harvests information from the application function workflow, provided as a graph by the function editor specification (based on Node-RED), including developer-inserted annotations during the design process, and maps them to the dynamic information retrieved from the available clusters. The Reasoning Framework interprets these data as graphs and automatically applies several semantic rules that enable filtering of the available resources and efficient information retrieval through a RESTfull interface. The paper also discusses experimental results to further showcase the advantages of the proposed approach.

Authors

• Georgios Fatouros
• Yannis Poulakis
• Ariana Polyviou
• Stylianos Tsarsitalidis
• Georgios Makridis
• John Soldatos
• Georgios Kousiouris
• Michael Filippakis
• Dimosthenis Kyriazis

The post Knowledge Graphs and interoperability techniques for hybrid-cloud deployment of FaaS applications appeared first on PHYSICS.