Generic Deployment Research Articles

Social Cyber-Physical Systems and Digital Twins Networks: A perspective about the future digital twin ecosystems

The Digital Twin, being a new transversal technology, has spread very quickly in several fields (industry, transportation, building, healthcare, etc.) and often in an anarchic way. As a result, several attempts to standardize and propose generic models for the Digital Twin (DT) have been made, in order to counterbalance the large heterogeneity that characterized the development of this technology as a consequence of a certain hype around this theme. This paper presents work that is part of our endeavors to develop a generic deployment methodology for DT, focusing on its interactional and systemic aspects. The deployment methodology is based on the 5C decomposition of Cyber-Physical Systems (CPS), where the first level "Configuration" implies the setting up of a generic architecture, hence the DT typology presented in this paper. Based on this, we presented a new vision of the 5D model of the DT, and then highlighted the interaction and evolution mechanisms that can characterize this latter during its life cycle. Finally, we discussed the concept of a hierarchical network of interconnected and evolving DTs. This will pave the way to further research that will address more specific architectures and technology dependent, dealing with the last level of the 5C pyramid.

Efficient Intelligent Generic Recommendation Knowledge Graph in Education Domain using Association Rule Mining and Machine Learning

Knowledge graph is used to extract and derive new facts from huge variety of data sources through relationship. An existing Natural language processing tool is specific and performs adaptive learning mechanism through instruction concepts. The specific knowledge graph suffers a problem of finding large collections of new facts with inter domain. This problem is addressed by implementing an efficient model for integrating various domain of interest as a generic knowledge graph. This proposed model has three major phases they are generic data collection, generic relationship establishment and generic deployment for education domain. The data are collected, preprocessed and categorized in to specific subject category by producing integrated data set. The relationship is established based on the pedagogical data with assessment data of leaners are classified in to course list. This generic knowledge graph is compared with the CNN based model and GCN based model. The validation of these models are assessed and deployed into application services for teachers and learners. The main objective of the proposed graph is to organize a generic knowledge graph for deriving huge amount of new facts to the education domain with maximum support and confidence level.

Evolution of the open-source data management system Ru-cio for LHC Run-3 and beyond ATLAS

Rucio, the distributed data management system of the ATLAS experiment already manages more than 400 Petabytes of physics data on the grid. Rucio was incrementally improved throughout LHC Run-2 and is currently being prepared for the HL-LHC era of the experiment. Next to these improvements the system is currently evolving into a full-scale generic data management system for application beyond ATLAS, or even beyond high-energy physics. This contribution focuses on the development roadmap of Rucio for LHC Run-3, such as event level data management, generic meta-data support and increased usage of networks and tapes. At the same time Rucio is evolving beyond the original ATLAS requirements. This includes additional authentication mechanisms, generic database compatibility, deployment and packaging of the software stack in containers, and a project paradigm shift to a full-scale open source project..

Structured decision-making for the management of a biological fieldable laboratory during outbreaks: a case for European Union Civil Protection Mechanism (EUCPM)

Fast on-scene deployment of an analytical laboratory capacity to help contain an outbreak of infectious disease requires setting up an appropriate policy framework and a range of operating procedures to ensure efficient support to decision-making, as well as the optimal engagement and use of dedicated resources. This work focuses on fully autonomous deployment when the mobile capacity operators themselves need to make decisions and implement all the operational functions (OFs), from basic needs like provision of equipment, power supply, food and accommodation for the staff, to complicated procedures like logistics of transportation and supply chain. A model of the identity and structure of specific decision-making requirements for a generic deployment of laboratory capacities was built from the real experience during specific deployments of the operators and managers of the Belgian capacity Biological Light Fieldable Laboratory for Emergencies (B-LiFE). Self- and external assessments were conducted and lessons learned successively reviewed after each deployment by B-LiFE laboratory operators and managers and observers in the framework of European demonstration projects and joint exercises. The result was consolidated by integrating the assessment of European Commission-appointed certifiers during the certification procedure of B-LIFE as a self-sufficient module of the European Medical Corps, namely the European modules exercise “Modex” in April 2017 (Revinge, Sweden) followed by the “ModTTX 4” Table-top in May 2017 (Bruges, Belgium). A complete and updated set of Fieldable Laboratory operational functions is presented, including their contents, cross-links, inter-dependencies, information needs for implementation, and related decisions.

MORTICIA, a statistical analysis software package for determining optical surveillance system effectiveness.

Surveillance modelling in terms of the standard Detect, Recognise and Identify (DRI) thresholds remains a key requirement for determining the effectiveness of surveillance sensors. With readily available computational resources it has become feasible to perform statistically representative evaluations of the effectiveness of these sensors. A new capability for performing this Monte-Carlo type analysis is demonstrated in the MORTICIA (Monte- Carlo Optical Rendering for Theatre Investigations of Capability under the Influence of the Atmosphere) software package developed at the Council for Scientific and Industrial Research (CSIR). This first generation, python-based open-source integrated software package, currently in the alpha stage of development aims to provide all the functionality required to perform statistical investigations of the effectiveness of optical surveillance systems in specific or generic deployment theatres. This includes modelling of the mathematical and physical processes that govern amongst other components of a surveillance system; a sensor's detector and optical components, a target and its background as well as the intervening atmospheric influences. In this paper we discuss integral aspects of the bespoke framework that are critical to the longevity of all subsequent modelling efforts. Additionally, some preliminary results are presented.

Drone Path Planning for Secure Positioning and Secure Position Verification

Many dependable systems rely on the integrity of the position of their components. In such systems, two key problems are secure localization and secure location verification of the components. Researchers proposed several solutions, which generally require expensive infrastructures of several fixed stations ( anchors ) with trusted positions. In this paper, we explore the approach of replacing all the fixed anchors with a single drone that flies through a sequence of waypoints. At each waypoint, the drone acts as an anchor and securely determines the positions. This approach completely eliminates the need for many expensive anchors. The main challenge becomes how to find a convenient path for the drone to do this for all the devices. The problem presents novel aspects, which make existing path planning algorithms unsuitable. We propose LocalizerBee , VerifierBee , and PreciseVerifierBee : three path planning algorithms that allow a drone to respectively measure, verify, and verify with a guaranteed precision a set of positions in a secure manner. They are able to securely localize all the positions in a generic deployment area, even in the presence of drone control errors. Moreover, they produce short path lengths and they run in a reasonable processing time.

Optimal WSN Deployment Models for Air Pollution Monitoring

Air pollution has become a major issue in the modern megalopolis because of industrial emissions and increasing urbanization along with traffic jams and the heating/cooling of buildings. Monitoring urban air quality is therefore required by municipalities and the civil society. Current monitoring systems rely on reference sensing stations that are precise but massive, costly, and, therefore, seldom. In this paper, we focus on an alternative or complementary approach, with a network of low cost and autonomic wireless sensors, aiming at a finer spatiotemporal granularity of sensing. Generic deployment models in the literature are not adapted to the stochastic nature of pollution sensing. Our main contribution is to design integer linear programming models that compute sensor deployments capturing both the coverage of pollution under time-varying weather conditions and the connectivity of the infrastructure. We evaluate our deployment models on a real data set of Greater London. We analyze the performance of the proposed models and show that our joint coverage and connectivity formulation is tight and compact, with a reasonable enough execution time. We also conduct extensive simulations to derive engineering insights for effective deployments of air pollution sensors in an urban environment.

Implementing generic PaaS deployment API: repackaging and deploying applications on heterogeneous PaaS platforms

The cloud platform-as-a-service (PaaS) model provides developers with the ability to deploy and manage their applications remotely in the cloud and pay only for actual usage hours. Currently, there is no standard API for PaaS deployment and management; each PaaS provider [e.g., Google AppEngine (GAE), OpenShift (OS), Cloud Foundry (CF), and Windows Azure] has its own proprietary APIs. This lack of standardisation adds a layer of complexity to application deployment and migration between heterogeneous PaaS platforms because of API incompatibility. A standard (generic) PaaS deployment API overcomes the previously mentioned PaaS API heterogeneity. A generic open-source API, namely the COAPS API, has been proposed to support deployment and management of applications on CF and OS PaaS platforms. This work implements COAPS deployment API to include the GAE PaaS. Whereas both CF and OS PaaS platforms use the same application packaging, deploying the same application on GAE requires application repackaging. We evaluated our work using a case study in which the same application is automatically deployed on CF and GAE.

Implementing generic PaaS deployment API: repackaging and deploying applications on heterogeneous PaaS platforms

Implementing generic PaaS deployment API: repackaging and deploying applications on heterogeneous PaaS platforms

Fusion: Expensive and Taking Forever?

The road map of fusion power is compared to the development and deployment of other energy technologies. A generic deployment model is presented, which describes the fastest deployment (of any new technology) achievable with the constraint that the industrial capacity that needs to be built up must be continuous and should not overshoot the replacement market in the final, saturated state. It is shown that the development needs an ‘investment’ phase to build up industrial capacity which takes several decades, during which growth is typically exponential, but net energy production is negligible. During the exponential growth the cost is dominated by the capital investment, which allows for a simple comparison of different energy technologies. Fusion is at the start of the exponential growth phase, while still having significant uncertainties concerning its technical feasibility. In comparison to e.g. solar PV and wind, fusion is ‘late’, lagging by some 50 years. To follow the same rate of development that fission, wind and PV have shown, fusion will need to have 3 DEMO reactors operational in the early 2050s, followed by 10 generation one (GEN1) plants in the early 2060s and 100 GEN2 plants in the early 2070s. For the cost development to be comparable, an estimated allowable cost for one DEMO reactor is ~20 G$. While these indicative numbers for the pace and cost of development are very challenging but perhaps not unthinkable for fusion, this analysis does point towards an emphasis on ‘simpler and cheaper’ reactor designs.

Tutorial on Applying the VM Technology for TFT-LCD Manufacturing

In the high-tech industries, on-line quality monitoring on each workpiece under processing is required to ensure process stability and improve yield rate. However, conducting workpiece-by-workpiece actual metrology is very expensive and time-consuming. In this case, a novel idea is to use “virtual metrology” (VM) that conjectures workpiece quality based on process data collected from production equipment with a slight supplement of actual metrology data. The purpose of this tutorial paper is to select the thin film transistor-liquid crystal display (TFT-LCD) manufacturing processes as the illustrative examples for demonstrating the methodology of fab-wide implementation of the VM technology systematically. To begin with, a survey of VM-related literature is performed. Then, the features of an effective and refined VM system are presented with the automatic VM (AVM) system developed by the authors as a case study, followed by introduction of the TFT-LCD production tools and manufacturing processes. After that, the generic deployment schemes of the VM technology for the TFT-LCD tools are proposed. Finally, illustrative examples with the AVM system as a case study are presented to show how the VM technology applies to TFT-LCD manufacturing.

Distributed Text Classification With an Ensemble Kernel-Based Learning Approach

Constructing a single text classifier that excels in any given application is a rather inviable goal. As a result, ensemble systems are becoming an important resource, since they permit the use of simpler classifiers and the integration of different knowledge in the learning process. However, many text-classification ensemble approaches have an extremely high computational burden, which poses limitations in applications in real environments. Moreover, state-of-the-art kernel-based classifiers, such as support vector machines and relevance vector machines, demand large resources when applied to large databases. Therefore, we propose the use of a new systematic distributed ensemble framework to tackle these challenges, based on a generic deployment strategy in a cluster distributed environment. We employ a combination of both task and data decomposition of the text-classification system, based on partitioning, communication, agglomeration, and mapping to define and optimize a graph of dependent tasks. Additionally, the framework includes an ensemble system where we exploit diverse patterns of errors and gain from the synergies between the ensemble classifiers. The ensemble data partitioning strategy used is shown to improve the performance of baseline state-of-the-art kernel-based machines. The experimental results show that the performance of the proposed framework outperforms standard methods both in speed and classification.

A Proposition of Generic Deployment Platform for Component Based Applications*

A Proposition of Generic Deployment Platform for Component Based Applications*

A Proposition of Generic Deployment Platform for Component Based Applications

A Proposition of Generic Deployment Platform for Component Based Applications

Tunneling techniques for end-to-end VPNs: generic deployment in an optical testbed environment

Service providers today are constantly seeking to offer multiple services on a single common infrastructure. For instance, it is desirable sometimes to provide transport services transparently to data traffic encapsulated over different network layers. Tunneling is a technique for encapsulating a packet or frame within another packet of the same or a different network layer. One of the motivations for tunneling is bridging various heterogeneous networks that use different protocols for communication. Tunneling is also used for providing private and secure communications over a publicly shared network. This article investigates the interactions between different tunneling technologies in order to provide end-to-end virtual connectivity to end clients. Particularly, the article describes the technical details of the implementation of various layer 2 tunneling techniques - such as L2TP, GRE, and MPLS-based tunnels - in order to establish an end-to-end virtual connection service as a concatenation of services offered by the different network domains along the path between end users

The infrastructure for E-business

Electronic commerce has obtained its means of spreading out to every corner of the world via the Internet. The article gives an overview of the implementation of Internet-based virtual private networks (VPN), the generic deployment framework and main enabling techniques.