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Mauro Femminella and Gianluca Reali. "An edge abstraction layer enabling federated and hierarchical orchestration of CCAM services in 5G and beyond networks." ITU Journal on Future and Evolving Technologies 3, no. 2 (2022): 59–81. http://dx.doi.org/10.52953/lnav1342.
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This paper shows a flexible orchestration solution for deploying Cooperative, Connected, and Automated Mobility (CCAM) services in 5G and beyond networks. This solution is based on the concepts of federation and hierarchy of orchestration functions. The federated approach is leveraged to cope with the differentiated complexity operation when multiple network operators are considered, whereas the hierarchical approach addresses the issue of jointly orchestrating multiple edge platforms in the network of a single operator. In this complex orchestration architecture, the main contribution of this paper consists of the design and implementation of an Abstraction and Adaptation Layer (AAL) for edge clouds, a new component enabling a truly cooperative and coordinated orchestration between different edge systems, characterized by appreciable experimental performance in terms of latency.
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Amarjeet Singh, Et al. "Microservices Container Security Orchestration Framework within Kubernetes and Docker for Business-Critical Applications within Digital Transformation." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 3 (2023): 332–36. http://dx.doi.org/10.17762/ijritcc.v11i3.9863.
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Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality-of-Service metrics. The CI in CI/CD stands for continuous integration. Continuous integration drives the automation in the development and delivery of the code and developers frequently apply code changes. It’s an automated process that allows multiple developers to contribute software components to the same project without integration conflicts. CI also triggers the process of testing the applications automatically upon code commit into the repository. Container virtualization technology facilitates the creation of microservices-based systems through continuous integration. Container-based apps can be deployed more easily when they use orchestration systems like Kubernetes, which has become the de facto standard. It can be difficult to create effective and precise orchestration systems, nevertheless. The scheduler, a crucial orchestrator task that allocates physical resources to containers, is the subject of this article. Scheduling strategies are developed using several Quality of Service metrics.
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Nina Slamnik-Krijestorac, Mauro Femminella, Girma M. Yilma, Marco Liebsch, Gianluca Reali, and Johann M. Marquez-Barja. "Orchestrating distributed 5G edges for automotive cross-border trials: Validation of an experimental prototype." ITU Journal on Future and Evolving Technologies 4, no. 2 (2023): 306–24. http://dx.doi.org/10.52953/jttu5989.
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The automotive industry requires ultra-reliable low-latency connectivity for its vehicles, and as such, it is one of the promising customers of 5G ecosystems and their orchestrated network infrastructure. In particular, Multi-Access Edge Computing (MEC) provides moving vehicles with localized low-latency access to service instances. However, given the mobility of vehicles, and various resource demand patterns at the distributed MEC nodes, challenges such as fast reconfiguration of the distributed deployment according to mobility pattern and associated service and resource demand need to be mitigated. In this paper, we present the orchestrated edges platform, which is a solution for orchestrating distributed edges in complex cross-border network environments, tailored to Connected, Cooperative, and Automated Mobility (CCAM) use cases within a 5G ecosystem. The proposed solution enables collaboration between orchestrators that belong to different tiers, and various federated edge domains, with the goal to enable service continuity for vehicles traversing cross-border corridors. The paper presents the prototype that we built for the H2020 5G-CARMEN trials, including the validation of the orchestration design choices, followed by the promising results that span both orchestration (orchestration latency) and application performance-related metrics (client-to-edge and edge-to-edge service data plane latencies).
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Bayani, Samir Vinayak, Ravish Tillu, and Jawaharbabu Jeyaraman. "Streamlining Compliance: Orchestrating Automated Checks for Cloud-based AI/ML Workflows." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 2, no. 3 (2023): 413–35. http://dx.doi.org/10.60087/jklst.vol2.n3.p435.
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Ensuring security and safeguarding data privacy within cloud workflows has garnered considerable attention in research circles. For instance, protecting the confidentiality of patients' private data managed within a cloud-deployed workflow is crucial, as is ensuring secure communication of such sensitive information among various stakeholders. In light of this, our paper proposes an architecture and a formal model for enforcing security within cloud workflow orchestration. The proposed architecture underscores the importance of monitoring cloud resources, workflow tasks, and data to identify and anticipate anomalies in cloud workflow orchestration. To achieve this, we advocate a multi-modal approach combining deep learning, one-class classification, and clustering techniques. In summary, our proposed architecture offers a comprehensive solution to security enforcement within cloud workflow orchestration, leveraging advanced techniques like deep learning for anomaly detection and prediction, particularly pertinent in critical domains such as healthcare during unprecedented times like the COVID-19 pandemic.
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Akter, Sohana. "Harmonizing Compliance: Coordinating Automated Verification Processes within Cloud-based AI/ML Workflows." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 3, no. 1 (2024): 143–60. http://dx.doi.org/10.60087/jaigs.vol03.issue01.p160.
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The significance of ensuring security and upholding data privacy within cloud-based workflows is widely recognized in research domains. This importance is particularly evident in contexts such as safeguarding patients' private data managed within cloud-deployed workflows, where maintaining confidentiality is paramount, alongside ensuring secure communication among involved stakeholders. In response to these imperatives, our paper presents an architecture and formal model designed to enforce security measures within cloud workflow orchestration. Central to our proposed architecture is the emphasis on continuous monitoring of cloud resources, workflow tasks, and data streams to detect and preempt anomalies in workflow orchestration processes. To accomplish this, we advocate for a multi-modal approach that integrates deep learning, one-class classification, and clustering techniques. In essence, our proposed architecture offers a comprehensive solution for enforcing security within cloud workflow orchestration, harnessing advanced methodologies like deep learning for anomaly detection and prediction. This approach is particularly pertinent in critical sectors such as healthcare, especially during unprecedented events like the COVID-19 pandemic.
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Akter, Sohana. "Harmonizing Compliance: Coordinating Automated Verification Processes within Cloud-based AI/ML Workflows." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 3, no. 1 (2024): 292–302. http://dx.doi.org/10.60087/jaigs.v3i1.121.
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The significance of ensuring security and upholding data privacy within cloud-based workflows is widely recognized in research domains. This importance is particularly evident in contexts such as safeguarding patients' private data managed within cloud-deployed workflows, where maintaining confidentiality is paramount, alongside ensuring secure communication among involved stakeholders. In response to these imperatives, our paper presents an architecture and formal model designed to enforce security measures within cloud workflow orchestration. Central to our proposed architecture is the emphasis on continuous monitoring of cloud resources, workflow tasks, and data streams to detect and preempt anomalies in workflow orchestration processes. To accomplish this, we advocate for a multi-modal approach that integrates deep learning, one-class classification, and clustering techniques. In essence, our proposed architecture offers a comprehensive solution for enforcing security within cloud workflow orchestration, harnessing advanced methodologies like deep learning for anomaly detection and prediction. This approach is particularly pertinent in critical sectors such as healthcare, especially during unprecedented events like the COVID-19 pandemic.
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Zou, Guobing, Yixin Chen, You Xu, Ruoyun Huang, and Yang Xiang. "Towards Automated Choreographing of Web Services Using Planning." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 178–84. http://dx.doi.org/10.1609/aaai.v26i1.8101.
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For Web service composition, choreography has recently received great attention and demonstrated a few key advantages over orchestration such as distributed control, fairness, data efficiency, and scalability. Automated design of choreography plans, especially distributed plans for multiple roles, is more complex and has not been studied before. Existing work requires manual generation assisted by model checking. In this paper, we propose a novel planning-based approach that can automatically convert a given composition task to a distributed choreography specification. Although planning has been used for orchestration, it is difficult to use planning for choreography, as it involves decentralized control, concurrent workflows, and contingency. We propose a few novel techniques, including compilation of contingencies, dependency graph analysis, and communication control, to handle these characteristics using planning. We theoretically show the correctness of this approach and empirically evaluate its practicability.
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Sciancalepore, Vincenzo, Faqir Zarrar Yousaf, and Xavier Costa-Perez. "z-TORCH: An Automated NFV Orchestration and Monitoring Solution." IEEE Transactions on Network and Service Management 15, no. 4 (2018): 1292–306. http://dx.doi.org/10.1109/tnsm.2018.2867827.
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Singh, Shikha, Ajay Kumar Bharti, Himanshu Pandey, Rakesh Kumar Yadav, Durgansh Sharma, and N. R. Shanker. "Towards Automated and Optimized Security Orchestration in Cloud SLA." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 3 (2023): 215–22. http://dx.doi.org/10.17762/ijritcc.v11i3.6339.
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In cloud computing, providers pool their resources and make them available to customers. Next-generation computer scientists are flocking to the cutting-edge field of cloud computing for their research and exploration of uncharted territory. There are still several barriers that cloud service providers must overcome in order to provide cloud services in accordance with service level agreements. Each cloud service provider aspires to achieve maximum performance as per Service Level Agreements (SLAs), and this is especially true when it comes to the delivery of services. A cloud service level agreement (SLA) guarantees that cloud service providers will satisfy the needs of large businesses and offer their clients with a specified list of services. The authors offer a web service level agreement–inspired approach for cloud service agreements. We adopt patterns and antipatterns to symbolize the best and worst practices of OCCI (Open Cloud Computing Interface Standard), REST (Representational State Transfer), and TOSCA (Topology and Orchestration Specification for Cloud Applications) with DevOps solutions, all of which API developers should bear in mind when designing APIs. When using this method, everything pertaining to the cloud service, from creation to deployment to measurement to evaluation to management to termination, may be handled mechanically. When distributing resources to cloud apps, our system takes into account the likelihood of SLA breaches and responds by providing more resources if necessary. We say that for optimal performance, our suggested solution should be used in a private cloud computing setting. As more and more people rely on cloud computing for their day-to-day workloads, there has been a corresponding rise in the need for efficient orchestration and management strategies that foster interoperability.
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Rusek, Marian, and Joanna Landmesser. "Time Complexity of an Distributed Algorithm for Load Balancing of Microservice-oriented Applications in the Cloud." ITM Web of Conferences 21 (2018): 00018. http://dx.doi.org/10.1051/itmconf/20182100018.
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Microservice architecture is a relatively new cloud application design pattern. Each microservice has a single responsibility in terms of functional requirement, and that can be managed independently from other microservices. This is done using automated cloud orchestration systems. In this paper we analyze the time complexity of an simple swarm-like decentralized load balancing algorithm for microservices running inside OpenVZ virtualization containers. We show that it can offer performance improvements with respect to the existing centralized container orchestration systems.
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Shamsuddeen Rabiu, Abubakar Abba, and Mustapha Ahmed Abubakar. "Autonomous workload distribution for container-based micro services environments." World Journal of Advanced Engineering Technology and Sciences 9, no. 2 (2023): 242–50. http://dx.doi.org/10.30574/wjaets.2023.9.2.0226.
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Microservice architecture represents a cloud application design approach that transfers the intricacies from the conventional monolithic applications to the infrastructure. It involves breaking down the application into small, containerized microservices, each responsible for a specific functional requirement. These microservices can be independently deployed, scaled, and tested through automated orchestration systems. Our paper introduces an autonomous system for distributing workloads among containerized microservices within the cloud like a swarm, designed specifically for microservices operating within OpenVZ containers. This system has the potential to enhance performance compared to existing centralized container orchestration systems.
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Czekierda, Łukasz, Krzysztof Zieliński, and Sławomir Zieliński. "Automated Orchestration of Online Educational Collaboration in Cloud-based Environments." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 1 (2021): 1–26. http://dx.doi.org/10.1145/3412381.
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Integrated collaboration environments (ICEs) are widely used by corporations to increase productivity by fostering groupwide and interpersonal collaboration. In this article, we discuss the enhancements of such environment needed to build an educational ICE (E-ICE) that addresses the specific needs of educational users. The motivation for the research was the Małopolska Educational Cloud (MEC) project conducted by AGH University and its partners. The E-ICE developed by MEC project fosters collaboration between universities and high schools by creating an immersive virtual collaboration space. MEC is a unique project due to its scale and usage domain. Multiple online collaboration events are organized weekly between over 150 geographically scattered institutions. Such events, aside from videoconferencing, require various services. The MEC E-ICE is a complex composition of a significant number of services and various terminals that require very specific configuration and management. In this article, we focus on a model-driven approach to automating the organization of online meetings in their preparation, execution, and conclusion phases. We present a conceptual model of E-ICE-supported educational courses, introduce a taxonomy of online educational services, identify planes and modes of their operation, as well as discuss the most common collaboration patterns. The MEC E-ICE, which we present as a case study, is built in accordance with the presented, model-driven approach. MEC educational services are described in a way that allows for converting the declarative specification of E-ICE application models into platform-independent models, platform-specific models, and, finally, working sets of orchestrated service instances. Such approach both reduces the level of technical knowledge required from the end-users and considerably speeds up the construction of online educational collaboration environments.
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Frommel, C., F. Krebs, T. Haase, et al. "Automated manufacturing of large composites utilizing a process orchestration system." Procedia Manufacturing 51 (2020): 470–77. http://dx.doi.org/10.1016/j.promfg.2020.10.066.
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Purahong, B., J. Sithiyopasakul, P. Sithiyopasakul, A. Lasakul, and C. Benjangkaprasert. "Automated Resource Management System Based upon Container Orchestration Tools Comparison." Journal of Advances in Information Technology 14, no. 3 (2023): 501–9. http://dx.doi.org/10.12720/jait.14.3.501-509.
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Bouami, Hind, and Patrick Millot. "Healthcare Delivery System Security: the orchestration of automated and organizational solutions." IFAC-PapersOnLine 52, no. 19 (2019): 127–32. http://dx.doi.org/10.1016/j.ifacol.2019.12.123.
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Mthembu, Sabelo Justice, Ijeoma Noella Ezeji, and Matthew Adigun. "Orchestration Tools For Efficient Deployment of IoT Applications In Fog Computing: A Systematic Review." International Conference on Artificial Intelligence and its Applications 2023 (November 9, 2023): 146–51. http://dx.doi.org/10.59200/icarti.2023.021.
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Internet of Things (IoT) is the developing technology that enables devices to communicate without human interaction. IoT utilizes cloud computing services to collect and process data for IoT devices and to manage the device remotely. Cloud computing is not efficient enough to handle the fast stream of data produced by the IoT, therefore scaling up IoT applications to meet demands of high peak becomes easier and highly automated in fog computing. Containers are mostly used as virtualization solutions for IoT in fog computing. It enables the execution of small microservices to large applications. However, the rise of many lightweight containers has resulted in new application architectures and fundamentally changing how applications are deployed and visualized. Due to this change, container orchestration tools were proposed. These tools allow users to coordinate and manage containers. However, container orchestration tools need to meet the requirements of IoT applications and constraints imposed on the nodes in fog. This paper presents a systematic literature review on the selection of orchestration tools for the efficient deployment of IoT applications in fog computing. Moreover, the performance of IoT applications must be considered by applying different metrics. This paper aims to propose potential research directions to address identified gaps in the selection of orchestration tools.
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Fernandez, Vidal, and Valera. "Enabling the Orchestration of IoT Slices through Edge and Cloud Microservice Platforms." Sensors 19, no. 13 (2019): 2980. http://dx.doi.org/10.3390/s19132980.
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This article addresses one of the main challenges related to the practical deployment of Internet of Things (IoT) solutions: the coordinated operation of entities at different infrastructures to support the automated orchestration of end-to-end Internet of Things services. This idea is referred to as “Internet of Things slicing” and is based on the network slicing concept already defined for the Fifth Generation (5G) of mobile networks. In this context, we present the architectural design of a slice orchestrator addressing the aforementioned challenge, based on well-known standard technologies and protocols. The proposed solution is able to integrate existing technologies, like cloud computing, with other more recent technologies like edge computing and network slicing. In addition, a functional prototype of the proposed orchestrator has been implemented, using open-source software and microservice platforms. As a first step to prove the practical feasibility of our solution, the implementation of the orchestrator considers cloud and edge domains. The validation results obtained from the prototype prove the feasibility of the solution from a functional perspective, verifying its capacity to deploy Internet of Things related functions even on resource constrained platforms. This approach enables new application models where these Internet of Things related functions can be onboarded on small unmanned aerial vehicles, offering a flexible and cost-effective solution to deploy these functions at the network edge. In addition, this proposal can also be used on commercial cloud platforms, like the Google Compute Engine, showing that it can take advantage of the benefits of edge and cloud computing respectively.
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Lee, Seunghwan, Linh-An Phan, Dae-Heon Park, Sehan Kim, and Taehong Kim. "EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX." Applied Sciences 12, no. 1 (2021): 140. http://dx.doi.org/10.3390/app12010140.
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With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling.
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Prieto, L. P., K. Sharma, Ł. Kidzinski, M. J. Rodríguez-Triana, and P. Dillenbourg. "Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data." Journal of Computer Assisted Learning 34, no. 2 (2018): 193–203. http://dx.doi.org/10.1111/jcal.12232.
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Nowsath, N. Mohammed. "IoT BIOMETRIC ATTENDANCE SYSTEM NEXUS WITH AUTOMATED DATA STREAMLINING AND SOFTWARE ORCHESTRATION." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29389.
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Biometric technology involves the recognition and authentication of individuals by examining unique characteristics of the human body. In modern times, attendance is taken traditionally in educational institutions using paper and pen, it increases the workload for teachers and also takes time. The purpose of this design is to make a biometric system for students. As the world becomes modern and digitalized, so we need to make a portable system for attendance with an embedded software application. By this proposal, authorized access will be given to the teacher to activate the biometric for each period. After student attendance is recognized by a fingerprint sensor the required messages will be sent to their parents for every period and the data will be stored in the application. In addition, the proposed system could increase productivity and reduce the manual process, truancy, and lateness in educational institutions. Keywords-- IoT, Attendance, Fingerprint, Biometrics, Firebase, Android Application
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Slamnik-Kriještorac, Nina, Erik de Britto e Silva, Esteban Municio, Henrique C. Carvalho de Resende, Seilendria A. Hadiwardoyo, and Johann M. Marquez-Barja. "Network Service and Resource Orchestration: A Feature and Performance Analysis within the MEC-Enhanced Vehicular Network Context." Sensors 20, no. 14 (2020): 3852. http://dx.doi.org/10.3390/s20143852.
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By providing storage and computational resources at the network edge, which enables hosting applications closer to the mobile users, Multi-Access Edge Computing (MEC) uses the mobile backhaul, and the network core more efficiently, thereby reducing the overall latency. Fostering the synergy between 5G and MEC brings ultra-reliable low-latency in data transmission, and paves the way towards numerous latency-sensitive automotive use cases, with the ultimate goal of enabling autonomous driving. Despite the benefits of significant latency reduction, bringing MEC platforms into 5G-based vehicular networks imposes severe challenges towards poorly scalable network management, as MEC platforms usually represent a highly heterogeneous environment. Therefore, there is a strong need to perform network management and orchestration in an automated way, which, being supported by Software Defined Networking (SDN) and Network Function Virtualization (NFV), will further decrease the latency. With recent advances in SDN, along with NFV, which aim to facilitate management automation for tackling delay issues in vehicular communications, we study the closed-loop life-cycle management of network services, and map such cycle to the Management and Orchestration (MANO) systems, such as ETSI NFV MANO. In this paper, we provide a comprehensive overview of existing MANO solutions, studying their most important features to enable network service and resource orchestration in MEC-enhanced vehicular networks. Finally, using a real testbed setup, we conduct and present an extensive performance analysis of Open Baton and Open Source MANO that are, due to their lightweight resource footprint, and compliance to ETSI standards, suitable solutions for resource and service management and orchestration within the network edge.
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Baranda Hortiguela, Jorge, Josep Mangues-Bafalluy, Ricardo Martinez, et al. "Realizing the Network Service Federation Vision: Enabling Automated Multidomain Orchestration of Network Services." IEEE Vehicular Technology Magazine 15, no. 2 (2020): 48–57. http://dx.doi.org/10.1109/mvt.2020.2979558.
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Moubayed, Abdallah, Abdallah Shami, and Anwer Al-Dulaimi. "On End-to-End Intelligent Automation of 6G Networks." Future Internet 14, no. 6 (2022): 165. http://dx.doi.org/10.3390/fi14060165.
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The digital transformation of businesses and services is currently in full force, opening the world to a new set of unique challenges and opportunities. In this context, 6G promises to be the set of technologies, architectures, and paradigms that will promote the digital transformation and enable growth and sustainability by offering the means to interact and control the digital and virtual worlds that are decoupled from their physical location. One of the main challenges facing 6G networks is “end-to-end network automation”. This is because such networks have to deal with more complex infrastructure and a diverse set of heterogeneous services and fragmented use cases. Accordingly, this paper aims at envisioning the role of different enabling technologies towards end-to-end intelligent automated 6G networks. To this end, this paper first reviews the literature focusing on the orchestration and automation of next-generation networks by discussing in detail the challenges facing efficient and fully automated 6G networks. This includes automating both the operational and functional elements for 6G networks. Additionally, this paper defines some of the key technologies that will play a vital role in addressing the research gaps and tackling the aforementioned challenges. More specifically, it outlines how advanced data-driven paradigms such as reinforcement learning and federated learning can be incorporated into 6G networks for more dynamic, efficient, effective, and intelligent network automation and orchestration.
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Baranski, M., G. Bode, F. Nienaber, B. Bruhn, P. Grant, and H. Ziegeldorf. "Scalable decarbonisation using automated operation optimisation." Journal of Physics: Conference Series 2600, no. 13 (2023): 132011. http://dx.doi.org/10.1088/1742-6596/2600/13/132011.
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Abstract One of the biggest challenges in facing the climate crisis is the decarbonization of the large and diverse building stock. A reduction of carbon dioxide emissions can be achieved by technical measures and engaging the building occupants to adapt their behaviour. Among the technical measures, implementing predictive control as an upgrade of the existing heating, ventilation, air conditioning and cooling system is especially promising as it allows reductions at potentially low running cost. However, the effort for adapting, implementing and deploying these methods to fit specific buildings and scenarios is high and requires special domain knowledge, hindering the wide-spread application. In this paper, we present a highly automated and data-driven implementation process utilizing an open-source container orchestration system, and the results from real-life case studies in existing buildings in which predictive control was retrofitted. Additionally, occupant information systems were installed in the buildings for increasing transparency about the building performance and the effect of the occupants’ behaviour. The shown method is useful for reducing the time required and manual effort for implementing new control strategies, and thus reducing carbon dioxide emissions while simultaneously increasing thermal comfort and air quality.
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Pelle, István, Márk Szalay, János Czentye, Balázs Sonkoly, and László Toka. "Cost and Latency Optimized Edge Computing Platform." Electronics 11, no. 4 (2022): 561. http://dx.doi.org/10.3390/electronics11040561.
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Latency-critical applications, e.g., automated and assisted driving services, can now be deployed in fog or edge computing environments, offloading energy-consuming tasks from end devices. Besides the proximity, though, the edge computing platform must provide the necessary operation techniques in order to avoid added delays by all means. In this paper, we propose an integrated edge platform that comprises orchestration methods with such objectives, in terms of handling the deployment of both functions and data. We show how the integration of the function orchestration solution with the adaptive data placement of a distributed key–value store can lead to decreased end-to-end latency even when the mobility of end devices creates a dynamic set of requirements. Along with the necessary monitoring features, the proposed edge platform is capable of serving the nomad users of novel applications with low latency requirements. We showcase this capability in several scenarios, in which we articulate the end-to-end latency performance of our platform by comparing delay measurements with the benchmark of a Redis-based setup lacking the adaptive nature of data orchestration. Our results prove that the stringent delay requisites necessitate the close integration that we present in this paper: functions and data must be orchestrated in sync in order to fully exploit the potential that the proximity of edge resources enables.
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Xiong, Zhitao, and Johan Olstam. "Orchestration of driving simulator scenarios based on dynamic actor preparation and automated action planning." Transportation Research Part C: Emerging Technologies 56 (July 2015): 120–31. http://dx.doi.org/10.1016/j.trc.2015.02.008.
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Dietze, Stefan, Alessio Gugliotta, John Domingue, and Michael Mrissa. "Mediation Spaces for Similarity-Based Semantic Web Services Selection." International Journal of Web Services Research 8, no. 1 (2011): 1–20. http://dx.doi.org/10.4018/jwsr.2011010101.
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Semantic Web Services (SWS) aim at the automated discovery, selection and orchestration of Web services based on comprehensive, machine-interpretable semantic descriptions. The latter are, in principle, deployed by multiple possible actors (i.e., service providers and service consumers); thus, a high level of heterogeneity between distinct SWS annotations is expected. Therefore, mediation between concurrent semantic representations of services is a key requirement to fully implement the SWS vision. In this paper, the authors argue that “semantic-level mediation” is necessary to identify semantic similarities across distinct SWS representations. The authors formalize and implement a mediation approach based on “Mediation Spaces” (MS), which enables the implicit representation of semantic similarities among distinct SWS descriptions. As a result, given a specific SWS approach and the proposed MS, a general purpose algorithm is implemented to empower SWS selection with the automatic computation of semantic similarities between a given SWS request and a set of SWS offers. A prototypical application illustrates the approach and highlights the benefits w.r.t. current mediation approaches.
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Llorens-Carrodeguas, Alejandro, Stefanos G. Sagkriotis, Cristina Cervelló-Pastor, and Dimitrios P. Pezaros. "An Energy-Friendly Scheduler for Edge Computing Systems." Sensors 21, no. 21 (2021): 7151. http://dx.doi.org/10.3390/s21217151.
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The deployment of modern applications, like massive Internet of Things (IoT), poses a combination of challenges that service providers need to overcome: high availability of the offered services, low latency, and low energy consumption. To overcome these challenges, service providers have been placing computing infrastructure close to the end users, at the edge of the network. In this vein, single board computer (SBC) clusters have gained attention due to their low cost, low energy consumption, and easy programmability. A subset of IoT applications requires the deployment of battery-powered SBCs, or clusters thereof. More recently, the deployment of services on SBC clusters has been automated through the use of containers. The management of these containers is performed by orchestration platforms, like Kubernetes. However, orchestration platforms do not consider remaining energy levels for their placement decisions and therefore are not optimized for energy-constrained environments. In this study, we propose a scheduler that is optimised for energy-constrained SBC clusters and operates within Kubernetes. Through comparison with the available schedulers we achieved 23% fewer event rejections, 83% less deadline violations, and approximately a 59% reduction of the consumed energy throughout the cluster.
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Kelly, Nick, Kate Thompson, and Pippa Yeoman. "Theory-led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning." Journal of Learning Analytics 2, no. 2 (2015): 14–43. http://dx.doi.org/10.18608/jla.2015.22.3.
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This paper describes theory-led design as a way of developing novel tools for learning analytics. It focuses upon the domain of real-time automated discourse analysis (ADA) of group learning activities to facilitate instructor orchestration of online groups. The paper outlines the literature on the development of LA especially within the domain of ADA, and proposes that there is reason to conduct more tool development based upon first-principles. It describes first principles as being drawn from theory and subsequently informing the structure and behaviour of tools and presents a framework for this process. The framework is substantiated through the example of developing a new tool for assisting instructors with the orchestration of online groups. A description of the tool is given and examples of results from use with real-world data are presented. The paper concludes that whilst design purely from first principles may be elusive, the call is for more intent to explicitly connect the design process to theory on the basis that this has the potential to yield innovation when developing tools as well as the prospect of a the outcomes from tools connecting back to theory.
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Balcas, Justas, Harvey Newman, Preeti P. Bhat, et al. "Automated Network Services for Exascale Data Movement." EPJ Web of Conferences 295 (2024): 01009. http://dx.doi.org/10.1051/epjconf/202429501009.
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The Large Hadron Collider (LHC) experiments distribute data by leveraging a diverse array of National Research and Education Networks (NRENs), where experiment data management systems treat networks as a “blackbox” resource. After the High Luminosity upgrade, the Compact Muon Solenoid (CMS) experiment alone will produce roughly 0.5 exabytes of data per year. NREN Networks are a critical part of the success of CMS and other LHC experiments. However, during data movement, NRENs are unaware of data priorities, importance, or need for quality of service, and this poses a challenge for operators to coordinate the movement of data and have predictable data flows across multi-domain networks. The overarching goal of SENSE (The Software-defined network for End-to-end Networked Science at Exascale) is to enable National Labs and universities to request and provision end-to-end intelligent network services for their application workflows leveraging SDN (Software-Defined Networking) capabilities. This work aims to allow LHC Experiments and Rucio, the data management software used by CMS Experiment, to allocate and prioritize certain data transfers over the wide area network. In this paper, we will present the current progress of the integration of SENSE, Multi-domain end-to-end SDN Orchestration with QoS (Quality of Service) capabilities, with Rucio, the data management software used by CMS Experiment.
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Mudaranthakam, Dinesh Pal, Alexandra Brown, Elizabeth Kerling, Susan E. Carlson, Christina J. Valentine, and Byron Gajewski. "The Successful Synchronized Orchestration of an Investigator-Initiated Multicenter Trial Using a Clinical Trial Management System and Team Approach: Design and Utility Study." JMIR Formative Research 5, no. 12 (2021): e30368. http://dx.doi.org/10.2196/30368.
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Background As the cost of clinical trials continues to rise, novel approaches are required to ensure ethical allocation of resources. Multisite trials have been increasingly utilized in phase 1 trials for rare diseases and in phase 2 and 3 trials to meet accrual needs. The benefits of multisite trials include easier patient recruitment, expanded generalizability, and more robust statistical analyses. However, there are several problems more likely to arise in multisite trials, including accrual inequality, protocol nonadherence, data entry mistakes, and data integration difficulties. Objective The Biostatistics & Data Science department at the University of Kansas Medical Center developed a clinical trial management system (comprehensive research information system [CRIS]) specifically designed to streamline multisite clinical trial management. Methods A National Institute of Child Health and Human Development–funded phase 3 trial, the ADORE (assessment of docosahexaenoic acid [DHA] on reducing early preterm birth) trial fully utilized CRIS to provide automated accrual reports, centralize data capture, automate trial completion reports, and streamline data harmonization. Results Using the ADORE trial as an example, we describe the utility of CRIS in database design, regulatory compliance, training standardization, study management, and automated reporting. Our goal is to continue to build a CRIS through use in subsequent multisite trials. Reports generated to suit the needs of future studies will be available as templates. Conclusions The implementation of similar tools and systems could provide significant cost-saving and operational benefit to multisite trials. Trial Registration ClinicalTrials.gov NCT02626299; https://tinyurl.com/j6erphcj
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Gatzianas, Marios, Agapi Mesodiakaki, George Kalfas, et al. "Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks." Applied Sciences 11, no. 22 (2021): 10547. http://dx.doi.org/10.3390/app112210547.
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In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.
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Liu, Chang, and Chen Meng. "Information Integration in ATS Based on ATML." Advanced Materials Research 962-965 (June 2014): 2699–702. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2699.
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We describe the conclusions of a technology and communities survey supported by concurrent and follow-on proof-of-concept prototyping to evaluate feasibility of defining a durable, versatile, reliable, visible software interface to support strategic modularization of test software development. The objective is that test sets and support software with diverse origins, ages, and abilities can be reliably integrated into test configurations that assemble and tear down and reassemble with scalable complexity in order to conduct both parametric tests and monitored trial runs. The resulting approach is based on integration of three recognized technologies that are currently gaining acceptance within the test industry and when combined provide a simple, open and scalable test orchestration architecture that addresses the objectives of the Automation Hooks task. The technologies are automated discovery using multicast DNS Zero Configuration Networking (zeroconf), commanding and data retrieval using resource-oriented Restful Web Services, and XML data transfer formats based on Automatic Test Markup Language (ATML). This open-source standards-based approach provides direct integration with existing commercial off-the-shelf (COTS) analysis software tools.
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Xiao, F., G. Y. K. Shea, M. S. Wong, and J. Campbell. "An automated and integrated framework for dust storm detection based on ogc web processing services." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-2 (November 11, 2014): 151–56. http://dx.doi.org/10.5194/isprsarchives-xl-2-151-2014.
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Dust storms are known to have adverse effects on public health. Atmospheric dust loading is also one of the major uncertainties in global climatic modelling as it is known to have a significant impact on the radiation budget and atmospheric stability. The complexity of building scientific dust storm models is coupled with the scientific computation advancement, ongoing computing platform development, and the development of heterogeneous Earth Observation (EO) networks. It is a challenging task to develop an integrated and automated scheme for dust storm detection that combines Geo-Processing frameworks, scientific models and EO data together to enable the dust storm detection and tracking processes in a dynamic and timely manner. This study develops an automated and integrated framework for dust storm detection and tracking based on the Web Processing Services (WPS) initiated by Open Geospatial Consortium (OGC). The presented WPS framework consists of EO data retrieval components, dust storm detecting and tracking component, and service chain orchestration engine. The EO data processing component is implemented based on OPeNDAP standard. The dust storm detecting and tracking component combines three earth scientific models, which are SBDART model (for computing aerosol optical depth (AOT) of dust particles), WRF model (for simulating meteorological parameters) and HYSPLIT model (for simulating the dust storm transport processes). The service chain orchestration engine is implemented based on Business Process Execution Language for Web Service (BPEL4WS) using open-source software. The output results, including horizontal and vertical AOT distribution of dust particles as well as their transport paths, were represented using KML/XML and displayed in Google Earth. A serious dust storm, which occurred over East Asia from 26 to 28 Apr 2012, is used to test the applicability of the proposed WPS framework. Our aim here is to solve a specific instance of a complex EO data and scientific model integration problem by using a framework and scientific workflow approach together. The experimental result shows that this newly automated and integrated framework can be used to give advance near real-time warning of dust storms, for both environmental authorities and public. The methods presented in this paper might be also generalized to other types of Earth system models, leading to improved ease of use and flexibility.
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Musser, Jeremy, Ezra Kissel, Martin Swany, et al. "Applying OSiRIS NMAL to Network Slices on SLATE." EPJ Web of Conferences 245 (2020): 07055. http://dx.doi.org/10.1051/epjconf/202024507055.
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The Network Management Abstraction Layer (NMAL) extends perfSONAR capabilities to include automated network topology discovery and tracking in the Unified Network Information Service (UNIS), and incorporate Software Defined Networking (SDN) into overall operations of the OSiRIS distributed Ceph infrastructure. We deploy perfSONAR components both within OSiRIS and at our “client” locations to allow monitoring and measuring the networks interconnecting science domain users and OSiRIS components. Topology discovery (using an SDN controller application) and Flange Network Orchestration (NOS) rules are used to dynamically manage network pathing in our testbed environments. NMAL components have been containerized to operate within the Services Layer at the Edge (SLATE) infrastructure, and we describe our experiences in packaging and deploying our services.
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Kasturi, Santanam, Xiaolong Li, Peng Li, and John Pickard. "A Proposed Approach to Integrate Application Security Vulnerability Data with Incidence Response Systems." American Journal of Networks and Communications 13, no. 1 (2024): 19–29. http://dx.doi.org/10.11648/j.ajnc.20241301.12.
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This paper has proposed a method to develop an attack tree, from application vulnerability data discovered through tests and scans and correlation analysis using incoming transaction requests monitored by a Web Application Firewall (WAF) tool. The attack tree shows multiple pathways for an attack to shape through vulnerability linkages and a deeper analysis of the Common Weakness Enumeration (CWE) and Common Vulnerability Exposure (CVE) mapping to individual vulnerabilities. By further relating to a parent, peer, or child CWE (including CWEs that follow another CWE and in some cases precede other CWEs) will provide more insight into the attack patterns. These patterns will reveal a multi-vulnerability, multi-application attack pattern which will be hard to visualize without data consolidation and correlation analysis. The correlation analysis tied to the test and scan data supports a vulnerability lineage starting from incoming requests to individual vulnerabilities found in the code that traces a possible attack path. This solution, if automated, can provide threat alerts and immediate focus on vulnerabilities that need to be remedied as a priority. SOAR (Security Orchestration, Automation, and Response), XSOAR (Extended Security Orchestration, Automation, and Response), SIEM (Security Information and Event Management), and XDR (Extended Detection and Response) are more constructed to suit networks, infrastructure and devices, and sensors; not meant for application security vulnerability information as collected. So, this paper makes a special case that must be made for integration of application security information as part of threat intelligence, and threat and incident response systems.
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Wettinger, Johannes, Tobias Binz, Uwe Breitenbücher, Oliver Kopp, and Frank Leymann. "Streamlining Cloud Management Automation by Unifying the Invocation of Scripts and Services Based on TOSCA." International Journal of Organizational and Collective Intelligence 4, no. 2 (2014): 45–63. http://dx.doi.org/10.4018/ijoci.2014040103.
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Today, there is a huge variety of script-centric approaches, APIs, and tools available to implement automated provisioning, deployment, and management of applications in the Cloud. The automation of all these aspects is key for reducing costs. However, most of these approaches are script-centric and provide proprietary solutions employing different invocation mechanisms, interfaces, and state models. Moreover, most Cloud providers offer proprietary APIs to be used for provisioning and management purposes. Consequently, it is hard to create deployment and management plans that integrate multiple of these approaches. The goal of our work is to come up with an approach for unifying the invocation of scripts and services without handling each proprietary interface separately. A prototype realizes the presented approach in a standards-based manner using the Topology and Orchestration Specification for Cloud Applications (TOSCA).
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Teplovs, Chris. "Commentary On “Theory-led design of instruments and representations in learning analytics: Developing a novel tool for orchestration of online collaborative learning”." Journal of Learning Analytics 2, no. 2 (2015): 44–46. http://dx.doi.org/10.18608/jla.2015.22.4.
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This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on issues of sustainability and scalability of learning analytics innovations.
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Chirivella-Perez, Enrique, Jose M. Alcaraz Calero, Qi Wang, and Juan Gutiérrez-Aguado. "Orchestration Architecture for Automatic Deployment of 5G Services from Bare Metal in Mobile Edge Computing Infrastructure." Wireless Communications and Mobile Computing 2018 (November 22, 2018): 1–18. http://dx.doi.org/10.1155/2018/5786936.
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The progress in realizing the Fifth Generation (5G) mobile networks has been accelerated recently towards deploying 5G prototypes with increasing scale. One of the Key Performance Indicators (KPIs) in 5G deployments is the service deployment time, which should be substantially reduced from the current 90 hours to the target 90 minutes on average as defined by the 5G Public-Private Partnership (5G-PPP). To achieve this challenging KPI, highly automated and coordinated operations are required for the 5G network management. This paper addresses this challenge by designing and prototyping a novel 5G service deployment orchestration architecture that is capable of automating and coordinating a series of complicated operations across physical infrastructure, virtual infrastructure, and service layers over a distributed mobile edge computing paradigm, in an integrated manner. Empirical results demonstrate the superior performance achieved, which meets the 5G-PPP KPI even in the most challenging scenario where 5G services are installed from bare metal.
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Cheng, M. C., S. C. Chou, Y. C. Chen, B. Chen, C. Liu, and S. J. Yu. "AUTOMATED FORMOSAT IMAGE PROCESSING SYSTEM FOR RAPID RESPONSE TO INTERNATIONAL DISASTERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 755–62. http://dx.doi.org/10.5194/isprs-archives-xli-b4-755-2016.
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FORMOSAT-2, Taiwan’s first remote sensing satellite, was successfully launched in May of 2004 into the Sun-synchronous orbit at 891 kilometers of altitude. With the daily revisit feature, the 2-m panchromatic, 8-m multi-spectral resolution images captured have been used for researches and operations in various societal benefit areas. This paper details the orchestration of various tasks conducted in different institutions in Taiwan in the efforts responding to international disasters. The institutes involved including its space agency-National Space Organization (NSPO), Center for Satellite Remote Sensing Research of National Central University, GIS Center of Feng-Chia University, and the National Center for High-performance Computing. Since each institution has its own mandate, the coordinated tasks ranged from receiving emergency observation requests, scheduling and tasking of satellite operation, downlink to ground stations, images processing including data injection, ortho-rectification, to delivery of image products. With the lessons learned from working with international partners, the FORMOSAT Image Processing System has been extensively automated and streamlined with a goal to shorten the time between request and delivery in an efficient manner. The integrated team has developed an Application Interface to its system platform that provides functions of search in archive catalogue, request of data services, mission planning, inquiry of services status, and image download. This automated system enables timely image acquisition and substantially increases the value of data product. Example outcome of these efforts in recent response to support Sentinel Asia in Nepal Earthquake is demonstrated herein.
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Cheng, M. C., S. C. Chou, Y. C. Chen, B. Chen, C. Liu, and S. J. Yu. "AUTOMATED FORMOSAT IMAGE PROCESSING SYSTEM FOR RAPID RESPONSE TO INTERNATIONAL DISASTERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 755–62. http://dx.doi.org/10.5194/isprsarchives-xli-b4-755-2016.
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FORMOSAT-2, Taiwan’s first remote sensing satellite, was successfully launched in May of 2004 into the Sun-synchronous orbit at 891 kilometers of altitude. With the daily revisit feature, the 2-m panchromatic, 8-m multi-spectral resolution images captured have been used for researches and operations in various societal benefit areas. This paper details the orchestration of various tasks conducted in different institutions in Taiwan in the efforts responding to international disasters. The institutes involved including its space agency-National Space Organization (NSPO), Center for Satellite Remote Sensing Research of National Central University, GIS Center of Feng-Chia University, and the National Center for High-performance Computing. Since each institution has its own mandate, the coordinated tasks ranged from receiving emergency observation requests, scheduling and tasking of satellite operation, downlink to ground stations, images processing including data injection, ortho-rectification, to delivery of image products. With the lessons learned from working with international partners, the FORMOSAT Image Processing System has been extensively automated and streamlined with a goal to shorten the time between request and delivery in an efficient manner. The integrated team has developed an Application Interface to its system platform that provides functions of search in archive catalogue, request of data services, mission planning, inquiry of services status, and image download. This automated system enables timely image acquisition and substantially increases the value of data product. Example outcome of these efforts in recent response to support Sentinel Asia in Nepal Earthquake is demonstrated herein.
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Barthe-Delanoë, Anne-Marie, Sabine Carbonnel, Frédérick Bénaben, and Hervé Pingaud. "An Event-Driven Platform for Agility Management of Crisis Response." International Journal of Information Systems for Crisis Response and Management 6, no. 2 (2014): 54–70. http://dx.doi.org/10.4018/ijiscram.2014040104.
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This article aims at presenting a whole approach of Information System Interoperability management in a crisis management cell: a Mediation Information System (MIS) may be used to help the crisis cell partners to design, run and manage the workflows of the response to a crisis situation. The architecture of the MIS meets the needs of low coupling between the partners' Information System components and the need of agility for such a platform. It is based on Service Oriented Architecture (SOA) and Event-Driven Architecture (EDA) principles that are combined to the Complex Event Processing (CEP) principles. This should leads on the one hand to an easier orchestration, choreography and real-time monitoring of the workflows' activities, on the other hand to assume on-the-fly automated agility of the crisis response (considering agility as the ability of the processes to remain consistent with the response to the crisis).
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Ali, Syed Saqib, and Bong Jun Choi. "State-of-the-Art Artificial Intelligence Techniques for Distributed Smart Grids: A Review." Electronics 9, no. 6 (2020): 1030. http://dx.doi.org/10.3390/electronics9061030.
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The power system worldwide is going through a revolutionary transformation due to the integration with various distributed components, including advanced metering infrastructure, communication infrastructure, distributed energy resources, and electric vehicles, to improve the reliability, energy efficiency, management, and security of the future power system. These components are becoming more tightly integrated with IoT. They are expected to generate a vast amount of data to support various applications in the smart grid, such as distributed energy management, generation forecasting, grid health monitoring, fault detection, home energy management, etc. With these new components and information, artificial intelligence techniques can be applied to automate and further improve the performance of the smart grid. In this paper, we provide a comprehensive review of the state-of-the-art artificial intelligence techniques to support various applications in a distributed smart grid. In particular, we discuss how artificial techniques are applied to support the integration of renewable energy resources, the integration of energy storage systems, demand response, management of the grid and home energy, and security. As the smart grid involves various actors, such as energy produces, markets, and consumers, we also discuss how artificial intelligence and market liberalization can potentially help to increase the overall social welfare of the grid. Finally, we provide further research challenges for large-scale integration and orchestration of automated distributed devices to realize a truly smart grid.
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Faas, Frank G. A., M. Cristina Avramut, Bernard M. van den Berg, A. Mieke Mommaas, Abraham J. Koster, and Raimond B. G. Ravelli. "Virtual nanoscopy: Generation of ultra-large high resolution electron microscopy maps." Journal of Cell Biology 198, no. 3 (2012): 457–69. http://dx.doi.org/10.1083/jcb.201201140.
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A key obstacle in uncovering the orchestration between molecular and cellular events is the vastly different length scales on which they occur. We describe here a methodology for ultrastructurally mapping regions of cells and tissue as large as 1 mm2 at nanometer resolution. Our approach employs standard transmission electron microscopy, rapid automated data collection, and stitching to create large virtual slides. It greatly facilitates correlative light-electron microscopy studies to relate structure and function and provides a genuine representation of ultrastructural events. The method is scalable as illustrated by slides up to 281 gigapixels in size. Here, we applied virtual nanoscopy in a correlative light-electron microscopy study to address the role of the endothelial glycocalyx in protein leakage over the glomerular filtration barrier, in an immunogold labeling study of internalization of oncolytic reovirus in human dendritic cells, in a cryo-electron microscopy study of intact vitrified mouse embryonic cells, and in an ultrastructural mapping of a complete zebrafish embryo slice.
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Serôdio, Carlos, Pedro Mestre, Jorge Cabral, Monica Gomes, and Frederico Branco. "Software and Architecture Orchestration for Process Control in Industry 4.0 Enabled by Cyber-Physical Systems Technologies." Applied Sciences 14, no. 5 (2024): 2160. http://dx.doi.org/10.3390/app14052160.
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In the context of Industry 4.0, this paper explores the vital role of advanced technologies, including Cyber–Physical Systems (CPS), Big Data, Internet of Things (IoT), digital twins, and Artificial Intelligence (AI), in enhancing data valorization and management within industries. These technologies are integral to addressing the challenges of producing highly customized products in mass, necessitating the complete digitization and integration of information technology (IT) and operational technology (OT) for flexible and automated manufacturing processes. The paper emphasizes the importance of interoperability through Service-Oriented Architectures (SOA), Manufacturing-as-a-Service (MaaS), and Resource-as-a-Service (RaaS) to achieve seamless integration across systems, which is critical for the Industry 4.0 vision of a fully interconnected, autonomous industry. Furthermore, it discusses the evolution towards Supply Chain 4.0, highlighting the need for Transportation Management Systems (TMS) enhanced by GPS and real-time data for efficient logistics. A guideline for implementing CPS within Industry 4.0 environments is provided, focusing on a case study of real-time data acquisition from logistics vehicles using CPS devices. The study proposes a CPS architecture and a generic platform for asset tracking to address integration challenges efficiently and facilitate the easy incorporation of new components and applications. Preliminary tests indicate the platform’s real-time performance is satisfactory, with negligible delay under test conditions, showcasing its potential for logistics applications and beyond.
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Bady, Elena, Katharina Möller, Tim Mandelkow, et al. "Abstract 597: BLEACH&STAIN 15 marker multiplexed imaging in 3098 human carcinomas revealed six major PD-L1 driven immune phenotypes with distinct spatial orchestration." Cancer Research 82, no. 12_Supplement (2022): 597. http://dx.doi.org/10.1158/1538-7445.am2022-597.
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Abstract Multiplex fluorescence immunohistochemistry (mfIHC) approaches were yet either limited to 6 markers or limited to a small (1.5cmx1.5cm) tissue size that hampers translational studies on large tissue microarray (TMA) cohorts. To be able to assess more marker in a large patient cohort, we have developed a BLEACH&STAIN multiplex fluorescence immunohistochemistry approach that enabled the simultaneous analysis of 15 biomarkers. To study the relationship of PD-L1 expression on multiple different cell types and the relationship with various lymphocyte subtypes, PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, and CD31 were analyzed in 3098 tumor samples from 44 different tumor types. An artificial intelligence-based framework - incorporating three different deep learning systems - for automated marker quantification on tumor as well as immune cells was further established to study the spatial interplay between PD-L1 expression and the composition of tumor infiltrating leucocytes (TILs). Comparing the automated deep learning-based PD-L1 quantification with conventional brightfield PD-L1 data revealed a high concordance in tumor cells (p<0.0001) as well as immune cells (p<0.0001) and an accuracy of the automated PD-L1 quantification ranging from 90% to 95.2%. Unsupervised clustering showed that a major proportion of the three PD-L1 phenotypes (i.e., PD-L1+ tumor and immune cells [G1], PD-L1+ immune cells [G2], PD-L1 negative [G3]) were either inflamed (G1.1, G2.1, G3.1) or non-inflamed (G1.2, G2.2, G3.2). In the inflamed PD-L1+ patients (G.1.1), spatial analysis revealed that an elevated intratumoral CD68+CD163+ M2 macrophages as well as CD11c+ dendritic cell infiltration (p<0.001 each) was associated with a high (CD3+CD4±CD8±FOXP3±) T-cell exclusion and a high PD-1 expression on T-cells (p<0.001 each). In breast cancer, a particular poor prognosis for the non-inflamed PD-L1+ breast cancer patients (G1.2, G2.2) was found and the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival with an area under receiver operating curves (AUC) of 0.72 (p<0.001) than the percentage of PD-L1+ tumor cells (AUC: 0.54). In conclusion, BLEACH&STAIN mfIHC in combination with a deep learning-based framework for automated PD-L1 assessment on tumor and immune cells enabled a rapid and comprehensive assessment of PD-L1 expression in different cell types and their interrelation with inflammatory cells. Our approach enabled the identification of six major PD-L1 phenotypes ranging from an PD-L1+ tumor cell inflamed phenotype (G1.1) with a spatial T-cell exclusion to a non-inflamed PD-L1+ immune cell phenotype showing a particular poor prognosis (G2.2) to a non-inflamed PD-L1 negative phenotype (G3.2). Citation Format: Elena Bady, Katharina Möller, Tim Mandelkow, Ronald Simon, Maximilian Lennartz, Claudia Hube-Magg, Guido Sauter, Niclas C. Blessin. BLEACH&STAIN 15 marker multiplexed imaging in 3098 human carcinomas revealed six major PD-L1 driven immune phenotypes with distinct spatial orchestration [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 597.
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Kevin B. Costa, Felipe S. Dantas Silva, Douglas B. Maciel, Charles H. F. Santos, Augusto J. V. Neto, and Fabio L. Verdi. "Self-organized and fully service-automated monitoring approach at the cloud-network slice granularity." ITU Journal on Future and Evolving Technologies 4, no. 2 (2023): 325–49. http://dx.doi.org/10.52953/wmnr9875.
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The cloud-network slicing concept has been established to deal with the advent of the Fifth Generation (5G) of mobile networks and its enabling technologies, thus promoting softwarization and cloudification. The Novel Enablers for Cloud Slicing (NECOS) ecosystem distinguishes itself over state of the art through the definition of slicing at both cloud and network levels and by promoting a Management and Orchestration (MANO) platform that provisions features with a self-organized and full-service automation approach across multiple federated domains. In the NECOS architecture, the Infrastructure and Monitoring Abstraction (IMA) component fetches Key Performance Indicators (KPIs) associated with the constituent parts of the active cloud-network slice instances managed by the NECOS platform. However, the design of the IMA monitoring component follows a centralized approach running at the core-cloud domain. Thus, the IMA concentrates on the monitoring data fetching function, done through interaction with measurement applications. It books all of them into a database and then forwards the incoming data for targeting management applications. Our findings in the slice monitoring state of the art study and assessments in IMA central cloud monitoring suggest that the centralized cloud approach cannot make distinct monitoring technologies compatible, besides not presenting a monitoring-as-a-service perspective that allows a self-organized and fully-service automated monitoring management scheme. In this regard, this work proposes the Distributed Infrastructure and Monitoring Abstraction (DIMA) multilevel monitoring plan. DIMA can promote monitoring as a service across an edge-cloud continuum inside the NECOS domain, enabling cloud/edge-centric and distributed monitoring schemes at the granularity of cloud-network slices' constituent parts.
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Pisarić, Milan, Vladimir Dimitrieski, Marko Vještica, Goran Krajoski, and Mirna Kapetina. "Towards a Flexible Smart Factory with a Dynamic Resource Orchestration." Applied Sciences 11, no. 17 (2021): 7956. http://dx.doi.org/10.3390/app11177956.
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Amid the current industrial revolution, a total disruption of the existing production lines may seem to be the easiest approach, as the potential possibilities seem limitless when starting from the ground up. On the business side, an adaptation of existing production lines is always a preferred option. In support of adaptation as opposed to disruption, this paper presents a new approach of using production process orchestration in a smart factory, discussed in an industrial case-study example. A proposed smart factory has the Orchestrator component in its core, responsible for complete semantical orchestration of production processes on one hand, and various factory resources on the other hand, in order to produce the desired product. The Orchestrator is a complex, modular, highly scalable, and pluggable software product responsible for automatised planning, scheduling, and execution of the complete production process. According to their offered capabilities, non-smart and smart resources—machines, robots, humans—are simultaneously and dynamically assigned to execute their dedicated production steps.
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Tembhurne, Omprakash, Sonali Milmile, Ganesh R. Pathak, Atul O. Thakare, and Abhijeet Thakare. "An Orchestrator." International Journal of Open Source Software and Processes 13, no. 1 (2022): 1–17. http://dx.doi.org/10.4018/ijossp.308792.
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A development of an orchestrator that manages multiusers and shared resources is extremely useful for automaton of jobs on the multiple machines. Many companies such as UiPath, Blue Prism, Automation Anywhere, etc. have their own orchestrator, but their orchestration services have some drawbacks (i.e., huge cost of yearly subscription, lack of user defined flexibility in architecture, and third-party security issues). The manuscript contains the design and analysis of orchestrator using open-source programming language and cloud platform (i.e., Python and OpenStack). The main focus of this paper is design and development of the orchestrator with shared resources and distribute environment management system that help to manage the multiuser, multi-machine environment in an efficient way. The overall examination delights that design and development of inhouse orchestrator application using open-source assets is not only useful in terms of colossal expense slicing, but also the development of free and flexible robotic process automation applications.
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Fank, Jana, Christian Knies, and Frank Diermeyer. "Analysis of a Human-Machine Interface for Cooperative Truck Overtaking Maneuvers on Freeways: Increase Success Rate and Assess Driving Behavior during System Failures." Multimodal Technologies and Interaction 5, no. 11 (2021): 69. http://dx.doi.org/10.3390/mti5110069.
Texto completoResumen
Cooperation between road users based on V2X communication has the potential to make road traffic safer and more efficient. The exchange of information enables the cooperative orchestration of critical traffic situations, such as truck overtaking maneuvers on freeways. With the benefit of such a system, questions arise concerning system failure or the abrupt and unexpected behavior of road users. A human-machine interface (HMI) organizes and negotiates the cooperation between drivers and maintains smooth interaction, trust, and system acceptance, even in the case of a possible system failure. A study was conducted with 30 truck drivers on a dynamic truck driving simulator to analyze the negotiation of cooperation requests and the reaction of truck drivers to potential system failures. The results show that an automated cooperation request does not translate into a significantly higher cooperation success rate. System failures in cooperative truck passing maneuvers are not considered critical by truck drivers in this simulated environment. The next step in the development process is to investigate how the success rate of truck overtaking maneuvers on freeways can be further increased as well as the implementation of the system in a real vehicle to investigate the reaction behavior of truck drivers in case of system failures in a real environment.