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RLaaS-Frame
Published in J. P. Mohsen, Mohamed Y. Ismail, Hamid R. Parsaei, Waldemar Karwowski, Global Advances in Engineering Education, 2019
Xuemin Chen, Qianlong Lan, Ning Wang, Gangbing Song, Hamid R. Parsaei
In order to combine the advantages of VM and Docker, an optimized solution to support the RLaaS-Frame is proposed. OpenStack, as a very popular software platform, is used in our optimized solution. OpenStack is a free cloud platform for private and public clouds. It supports an IaaS cloud and provides allocation for computational resources in support of both interactive and computationally intensive applications [43]. The software platform consists of interrelated components that control diverse, multi-vendor hardware polls of processing, storage, and networking resources throughout a data center. The key components of OpenStack include Nova Computing module, Glance Image Service, Swift Object Storage, Heat Orchestration, and Neutron Networking, etc. [44]. Docker provides deterministic software packaging and fits nicely with the immutable infrastructure model such as the optimized mobile application architecture and Wiki-based remote laboratory platform. OpenStack offers a complete data center management solution in which containers or hypervisors are only part of an RLaaS-Frame. OpenStack also includes multi-tenant security and isolation, management and monitoring, storage and networking and more. All of these services are needed for RLaaS-Frame to manage the cloud or data center. So Docker on top of OpenStack serves is an excellent containerization of micro-services pods for the RLaaS-Frame.
A Data Aware Scheme for Scheduling Big Data Applications with SAVANNA Hadoop
Published in Mahmoud Elkhodr, Qusay F. Hassan, Seyed Shahrestani, Networks of the Future, 2017
K. Hemant Kumar Reddy, Himansu Das, Diptendu Sinha Roy
In order to assess the efficacy of the proposed DACS, we deploy a virtualized environment using OpenStack [5]. Savanna-Hadoop on OpenStack offers a unified milieu for performing jobs capable of map-reduce capabilities. OpenStack offers a wide range of APIs to support deployment of applications, including services for computing, networking, storing, and other basic services. A multi-node Savanna-Hadoop cluster provides distributed access to all data stored uniformly. Figure 18.3 shows a high level abstraction of the proposed DACS with Savanna Hadoop on OpenStack. The layered framework presents an abstract view of DACS, where analytics API employed on top up SAVANA Hadoop Cluster (SHC). For any user analytic operations, the API interacts with SHC and after processing the query at this level it passes it to the next layer called OpenStack Cloud. The job of the OpenStack Cloud layer includes a check for authorization, VM allocation, migration, QoS measures, and tuning parameters to improve the efficiency of the model.
Cloud Computing: The Flexible Future
Published in Hrishikesh Venkatarman, Ramona Trestian, 5G Radio Access Networks: Centralized RAN, Cloud-RAN, and Virtualization of Small Cells, 2017
Joanna Kusznier, Xuan Thuy Dang, Manzoor Ahmed Khan
OpenStack has a modular architecture and it is decomposed into various components: compute (Nova), networking (Neutron/Quantum), identity management (Keystone), object storage (Swift), block storage (Cinder), image service (Glance), and user interface dashboard (Horizon). These components are designed to work together in order to provide a complete IaaS. APIs integrate these OpenStack components, which enable the component-specific services to be used by other components. The modular structure makes OpenStack extendable/customizable to the application areas of the consumer. Figure 5.10 illustrates a simplified view of the conceptual architecture. It is assumed that all of the services are used in the most standard configuration. To illustrate different components of the OpenStack, Figure 5.11 is a regenerated form of Figure 5.10, which more concretely highlights the component names and their integration.
Application of the Internet of Things in the textile industry
Published in Textile Progress, 2019
Hitesh Manglani, George L. Hodge, William Oxenham
The scope of this section includes IoT based spinning industry solutions for staple products only (as of 2019). Oerlikon Manmade Fibers Segment showcased IoT-based solutions at ITMA ASIA + CITME 2018, which are discussed but not compared and analyzed with others since the review deals with staple spinning solutions only. Oerlikon Barmag and Neumag provide AIM4DTY solutions [138] utilizing machine learning to identify possible causes of errors in machine texturing to help reduce quality risks. In the texturing machine, the UNITENS monitoring sensor continually measures the yarn tension at all positions. An error is generated if a measurement value does not lie within the prescribed tolerances. The form of graph and trend lines can provide error information to AIM4DTY, which it collects over the period to train itself and become better at predicting errors. This data is collected centrally and provided to users using HMI based services such as process monitoring via a service online app on smartphones and tablets. This, along with assistance system based on mixed-reality glasses (Microsoft HoloLens), forms Plant Operation Control (see Figure 6). The system is claimed to support predictive maintenance concepts and enables virtual 360-degree tours through spinning systems. Oerlikon processes most of the data on the customer’s onsite data center, and only permitted data is sent to the central server with approval to take data security into account. This onsite data center works on an open operating system called OpenStack. OpenStack is a cloud operating system that controls large pools of computing, storage, and networking resources throughout a data center, all managed and provisioned through APIs (Application Programming Interfaces) with common authentication mechanisms. They also claim to process all data in accordance with the new European General Data Protection Regulation, taking all further international data protection standards into account.