Architecture Scenarios Research Articles

Evolutionary Algorithm to Support Field Architecture Scenario Screening Automation and Optimization Using Decentralized Subsea Processing Modules

Manual generation of test cases and scenario screening processes, during field architecture concept development, may produce a limited number of solutions that do not necessarily lead to an optimal concept selection. For more complex subsea field architectures, which might include processing modules for enhancing pressure and thermal management for the production network, the number of configuration cases and scenarios to evaluate can be extremely large and time and resource-consuming to handle through conventional manual design processes. This paper explores the use of evolutionary algorithms (EA) to automate case generation, scenario screening, and optimization of decentralized subsea processing modules during field development. An evaluation of various genetic operators and evolution strategies was performed to compare their performance and suitability to the application. Based on the evaluation results, an EA using structural uniform crossover and a gradient plus boundary mutation as the main variation operators was developed. The methodology combines EA and an integrated modeling approach to automate and optimize the concept selection and field architecture design when considering decentralized subsea processing modules.

Optimal path routing in WMNs: HGAB3C based approach

This paper proposes a new hybrid, optimal cost based routing approach namely HGAB3C implemented for routing in wireless mesh networks (WMNs). We used this proactive routing approach to find the optimal paths in dynamically created WMN of client nodes. The performance of proposed approach was evaluated with different architectural scenarios from 1000 nodes to 10,000 nodes WMNs with a step increase of 1000 nodes. The route costs were evaluated using integrated link cost (ILC) measure which is a function of jitter, network delay and throughput. Performance of this proposed approach was compared with seven other soft computing based approaches and two hard computing based algorithms. The proposed approach outperformed all the other 9 competing approaches. The proposed algorithm can also be used effectively in isolation wards of COVID-19 hospitals and quarantine centers where robots can be networked for communications between patients and doctors.

Retrieval of Vertical Foliage Profile and Leaf Area Index Using Transmitted Energy Information Derived from ICESat GLAS Data

The vertical foliage profile (VFP) and leaf area index (LAI) are critical descriptors in terrestrial ecosystem modeling. Although light detection and ranging (lidar) observations have been proven to have potential for deriving the VFP and LAI, existing methods depend only on the received waveform information and are sensitive to additional input parameters, such as the ratio of canopy to ground reflectance. In this study, we proposed a new method for retrieving forest VFP and LAI from Ice, Cloud and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) data over two sites similar in their biophysical parameters. Our method utilized the information from not only the interaction between the laser and the forest but also the sensor configuration, which brought the benefit that our method was free from an empirical input parameter. Specifically, we first derived the transmitted energy profile (TEP) through the lidar 1-D radiative transfer model. Then, the obtained TEP was utilized to calculate the vertical gap distribution. Finally, the vertical gap distribution was taken as input to derive the VFP based on the Beer–Lambert law, and the LAI was calculated by integrating the VFP. Extensive validations of our method were carried out based on the discrete anisotropic radiative transfer (DART) simulation data, ground-based measurements, and the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI product. The validation based on the DART simulation data showed that our method could effectively characterize the VFP and LAI under various canopy architecture scenarios, including homogeneous turbid and discrete individual-tree scenes. The ground-based validation also proved the feasibility of our method: the VFP retrieved from the GLAS data showed a similar trend with the foliage distribution density in the GLAS footprints; the GLAS LAI had a high correlation with the field measurements, with a determination coefficient (R2) of 0.79, root mean square error (RMSE) of 0.49, and bias of 0.17. Once the outliers caused by low data quality and large slope were identified and removed, the accuracy was further improved, with R2 = 0.85, RMSE = 0.35, and bias = 0.10. However, the MODIS LAI product did not present a good relationship with the GLAS LAI. Relative to the GLAS LAI, the MODIS LAI showed an overestimation in the low and middle ranges of the LAI and a saturation at high values of approximately LAI = 5.5. Overall, this method has the potential to produce continental- and global-scale VFP and LAI datasets from the spaceborne lidar system.

A Neural Networks Approach to Detecting Lost Heritage in Historical Video

Documenting Cultural Heritage through the extraction of 3D measures with photogrammetry is fundamental for the conservation of the memory of the past. However, when the heritage has been lost the only way to recover this information is the use of historical images from archives. The aim of this study is to experiment with new ways to search for architectural heritage in video material and to save the effort of the operator in the archive in terms of efficiency and time. A workflow is proposed to automatically detect lost heritage in film footage using Deep Learning to find suitable images to process with photogrammetry for its 3D virtual reconstruction. The performance of the network was tested on two case studies considering different architectural scenarios, the Tour Saint Jacques which still exists for the tuning of the networks, and Les Halles to test the algorithms on a real case of an architecture which has been destroyed. Despite the poor quantity and low quality of the historical images available for the training of the network, it has been demonstrated that, with few frames, it was possible to reach the same results in terms of performance of a network trained on a large dataset. Moreover, with the introduction of new metrics based on time intervals the measure of the real time saving in terms of human effort was achieved. These findings represent an important innovation in the documentation of destroyed monuments and open new ways to recover information about the past.

6G Architecture to Connect the Worlds

The post-pandemic future will offer tremendous opportunity and challenge from transformation of the human experience linking physical, digital and biological worlds: 6G should be based on a new architecture to fully realize the vision to connect the worlds. We explore several novel architecture concepts for the 6G era driven by a decomposition of the architecture into platform, functions, orchestration and specialization aspects. With 6G, we associate an open, scalable, elastic, and platform agnostic het-cloud, with converged applications and services decomposed into micro-services and serverless functions, specialized architecture for extreme attributes, as well as open service orchestration architecture. Key attributes and characteristics of the associated architectural scenarios are described. At the air-interface level, 6G is expected to encompass use of sub-Terahertz spectrum and new spectrum sharing technologies, air-interface design optimized by AI/ML techniques, integration of radio sensing with communication, and meeting extreme requirements on latency, reliability and synchronization. Fully realizing the benefits of these advances in radio technology will also call for innovations in 6G network architecture as described.

Evaluation of Markov Models for Architecture Conformance Checking

Conformance between architecture and implementation is a key aspect of architecture-centric development. However, the architecture “as documented” and the architecture “as implemented” tend to diverge from each other over time. Thus, conformance checks should be run periodically on the system in order to detect and correct differences. Despite having a structural conformance analysis, assessing whether the main scenarios describing the architectural behavior are faithfully implemented in the code is still challenging. Checking conformance to architectural scenarios is usually a time-consuming and error-prone activity. In this article, we describe ArchLearner, a tool to assist architects to bridge the gap between architecture and its implementation. The architecture is specified with Use-Case Maps (UCMs), a notation for modeling both high-level structure and behavior. ArchLearner uses Markov Models to detect code deviations with respect to predetermined UCMs, based on the analysis of system execution traces for those UCMs. The results from two case-studies have shown that ArchLearner is practical and reduces conformance checking efforts.

Optimization of the Size of Thread Pool in Runtime Systems to Enterprise Application Integration: a Mathematical Modelling Approach

Companies seek technological alternatives that provide competitiveness for their business processes. One of them is integration platforms, software tools that build integration solutions, which allow the different applications that make up the software ecosystem to work synchronously and that new applications or functionalities be incorporated with the least impact in the existing ones. The runtime system is the component of the integration platform responsible for managing the computational resources that run the integration solution. Among these The performance of the runtime systems is directly related to the number of threads available to run the integration solution, but scaling the number of threads that provide a shorter response time is a challenge for software engineers. If this quantity is undersized, it may cause a delay in the execution; if it is overestimated, it could cause a waste of computational resources. This article presents a mathematical model, defined by differential equations, that establishes the optimum number of threads, which maximizes the expected performance gain by minimizing the execution time of the integration solution. In addition, it presents the mathematical model application, which assists the analysis of the expected gain in different architecture scenarios and quantity of threads.

Optimised building energy and indoor microclimatic predictions using knowledge-based system identification in a historical art gallery

This paper presents a system identification (SID) model for an historical art gallery of great cultural significance. These buildings require tight indoor temperature and moisture controls that demand significant energy from air handling units. Complex dynamic building systems, stringent conservation restrictions, and lack of detailed monitoring make diagnosing and optimising their energy use difficult. Building simulation software programmes have proven to be effective, but have tended to rely on data generated by simulation models. This study shows how artificial neural network (ANN) models trained with historical real data can predict a building’s energy use and the optimal indoor microclimate necessary for conservation. Four ANN target-data scenarios were designed for optimised model predictions, and 12 ANN training algorithms were tested with six architectural scenarios collecting daily and hourly data. The ANN models used a randomised 80% sample of the database, with the remainder (20%) validating the models. The model displayed a high coefficient of correlation (0.99), with the mean square error and mean absolute error less than 0.1% and 2%, respectively. This ANN-based SID tool efficiently represents a complex building system and could be an ideal method for investigating optimisation strategies prior to their implementation.

Design and Evaluation of a 28-nm FD-SOI STT-MRAM for Ultra-Low Power Microcontrollers

The complexity of embedded devices increases as today's applications request always more services. However, the power consumption of systems-on-chip has significantly increased due to the high-density integration and the high leakage power of current CMOS transistors. To address these issues, emerging technologies are considered. Spin-transfer torque magnetic random access memory (STT-MRAM) is seen as a promising alternative solution to traditional memories, thanks to its negligible leakage current, high density, and non-volatility. In this paper, we present the design and evaluation of a 128-kB STT-RAM in a 28-nm FD-SOI technology with SRAM-like interface for ultra-low power microcontrollers. With 0.9-pJ/bit read in 5 ns and 3-pJ/bit write in 10 ns, this embedded non-volatile memory is suitable for the devices that run at frequencies under 100 MHz. Considering a low-power application with duty-cycled behavior, we evaluate the STT-MRAM as a replacement of embedded Flash and SRAM by comparing single- and multi-memory architecture scenarios.

Life Cycle Energy Assessment of a School Building under Envelope Retrofit: An Approach towards Environmental Impact Reduction

Energy efficiency of existing buildings is a concept to manage and restrain the growth in energy consumption and one of the crucial issues due to the magnitude of the sector. Educational buildings are in charge of about 15% of the total energy consumption of the non-residential building sector. However, not only operational but also embodied energy of a building should be reduced to get the overall benefits of energy efficiency, where, using energy efficient architectural measures and low emitting materials during every retrofit action can be a logical step. The majority of buildings in Turkey and EU was built earlier than the development of the energy efficiency in the construction sector, hence, without energy retrofit, consume an enormous amount of energy that can be averted significantly by the implementation of some even not advanced retrofit measures. Furthermore, demolishing of a building to construct a new one is not a rational approach concerning cost, time and environmental pollution. The study has been focused on the impact assessment of the various architectural scenarios of energy efficiency upgrading on the Life Cycle Energy Consumption (LCEC) and Life Cycle CO2 (LCCO2) emission. Within the scope of the study, a primary school building is selected to be analysed. Through analysis, the total embodied and operational energy use and CO2 emission regarding the life cycle phase of the building is quantitatively defined and investigated in the framework of life cycle inventory. The paper concentrates on the operation and embodied energy consumption arising from the application of a variety of measures on the building envelope. An educational building with low LCCO2 emissions and LCEC in Turkey is proposed. To exemplify the approach, contributions are applied to a case study in Istanbul as a representative school building. The primary energy consumption of the case study building is calculated with a dynamic simulation tool, EnergyPlus. Afterwards, a sort of architectural energy efficient measures is implemented in the envelope while the lighting and mechanical systems remain constant. The energy used in the production and transportation of materials, which are the significant parts of the embodied energy, are taken into account as well.

Vers un nouveau Surréalisme. Las fantasías arquitectónicas de Jim Kazanjian.

<p>Desde la aparición del movimiento en la primera mitad de los años 20, el maridaje de surrealismo y fotografía ha tenido a la arquitectura como uno de sus objetos privilegiados, produciendo imposibles fantasías arquitectónicas revestidas por el velo de lo real. Con la llegada de los métodos de foto-manipulación digital, esta experimentación se ha multiplicado, dando lugar a una enorme variedad de aproximaciones que juegan con la imagen fotográfica para producir escenarios arquitectónicos imposibles pero fascinantes. El artículo centra su mirada en la obra de Jim Kazanjian, un autor procedente del mundo de la construcción digital que, actuando desde los márgenes de la disciplina, ha producido a lo largo de la última década una obra que combina la pericia técnica con su interés por las atmósferas sombrías de los relatos de H.P. Lovecraft o Algernon Blackwood para producir improbables objetos arquitectónicos de oscura pero delicada belleza.</p>

Estimation of forest LAI by inverting canopy reflectance models and multi-angle imagery

Computer simulation models have seldom been applied for estimating the structural and biophysical variables of forest canopy. In this study, an approach for the estimation of leaf area index (LAI) using the information contained in hyperspectral, multi-angle images and the inversion of a computer simulation model are explored. For this purpose, L-systems combined with forest growth model ZELIG were applied to render 3-D forest architectural scenarios. The Radiosity-graphics combined model (RGM) was used to estimate forest LAI from the Compact High-Resolution Imaging Spectrometer/Project for On-Board Autonomy (CHRIS/PROBA) data. LAI inversion was performed using the look-up table (LUT) method. The estimated LAI was evaluated against in situ LAI measurement and compared against the LAI predictions from CHRIS data obtained using the Li-Strahler geometric-optical canopy reflectance model (GOMS). The results indicated that the method used in this study can be efficient strategy to estimate LAI by RGM model inversion.

Nómadas frente a parásitos: prácticas subversivas en la ciudad contemporánea

La manera en la que el arte y la arquitectura han reaccionado a la realidad social y construida a lo largo de la historia moderna reciente ha sido variada. Si ante el urbanismo expansivo característico de la Europa de posguerra se priorizaron prácticas desvinculadas del territorio bajo enfoques utópico idealistas, en el cambio de siglo, y especialmente tras 2008, las inquietudes son otras. El intento de reequilibrar los desajustes provocados por los procesos de crecimiento urbano desaforado de la primera década del siglo XX ha llevado cuanto menos a cuestionar la mercantilización de la ciudad existente, esta vez como acciones vinculadas al territorio bajo una actitud pragmática. Partiendo de la premisa de Fiuza Faustino "La ilegalidad como el único territorio liberado dentro de las metrópolis” (2008), en este artículo se identifican acciones cotidianas, actitudes de resistencia que expresan su rechazo a una organización jerárquica de los escenarios arquitectónicos precrisis y evidencian su urgencia de renovación. Estas acciones trabajan sobre las posibilidades de las prácticas subversivas como dispositivos que dan cabida a otras formas de distribución del poder. Dichas actitudes efímeras e itinerantes se ejemplifican en apropiaciones temporales que redescriben la ciudad existente y ya no escapan de ella, habida cuenta del momento que nos ha tocado vivir.

El lenguaje fotográfico de maquetas arquitectónicas como forma de expresión creativa

In this study we relate the architectural models designed by the architect as a tool to project the construction of a building in the urban space and the architectural scenarios created by the photographer for artistic purposes. The main aim is to know how the photographs of decontextualized scenarios isolate the buildings of their functionality in the public space, forming new perceptions of time, place and memory. Its purpose goes beyond the purely architectural, that is to say, it exceeds the level of mimesis or the duplicity of the gaze, previously to the materialization of any construction. To reach our aim, weanalyze the work of four contemporary artists, whose methodology is based onthe design and construction of architectural scenarios as a first step beforecapturing the photograph.

A Taxonomy-based Approach For Fault Localization In Service-Oriented Applications

Service Oriented Computing is a relevant paradigm that allows for building software solutions as it supports the creation of dynamic and agile applications. As a result of these benefits, applications based on the paradigm are commonly used in the industry. However, the more complex software solutions become, the higher the chance of having bugs is. Identifying them in the entire solution may also be one of the most tedious, expensive and time-consuming activity within the developing process. Therefore, fault localization aims at finding the location of faults, determining the root cause of the failure and identifying the causes of abnormal behavior of a faulty program. In particular, fault localization for service oriented applications is currently a research field that has received little attention. In this context, we present a taxonomy-based approach for fault localization in service oriented applications, using information of faults in the underlying architecture of these applications, namely SOA. The results on the location of faults are not only provided to the developer but also enhanced with architectural information, that is, showing the faults and their connection with exceptions, code and architectural scenarios. The experimental results carried out indicate that developers reduce their effort of localizing faults in terms of time and lines of code.

All-Optical Programmable Disaggregated Data Centre Network Realized by FPGA-Based Switch and Interface Card

This paper reports an FPGA-based switch and interface card (SIC) and its application scenario in an all-optical, programmable disaggregated data center network (DCN). Our novel SIC is designed and implemented to replace traditional optical network interface cards, plugged into the server directly, supporting optical packet switching (OPS)/optical circuit switching (OCS) or time division multiplexing (TDM)/wavelength division multiplexing (WDM) traffic on demand. Placing the SIC in each server/blade, we eliminate electronics from the top of rack (ToR) switch by pushing all the functionality on each blade while enabling direct intrarack blade-to-blade communication to deliver ultralow chip-to-chip latency. We demonstrate the disaggregated DCN architecture scenarios along with all-optical dimension-programmable N × M spectrum selective Switches (SSS) and an architecture-on-demand (AoD) optical backplane. OPS and OCS complement each other as do TDM and WDM, which can support variable traffic flows. A flat disaggregated DCN architecture is realized by connecting the optical ToR switches directly to either an optical top of cluster switch or the intracluster AoD optical backplane, while clusters are further interconnected to an intercluster AoD for scaling out.

An Energy-Efficient Strategy for VoD Content Replication in Integrated Metro/Access Networks

The Video-on-Demand (VoD) service is becoming one the most popular Internet services. Due to its bandwidth-consuming nature and thanks to the efforts made by telecom operators to provide the users with higher access rates, an huge amount of VoD traffic is expected to flood the core segment of the network, potentially leading to congestion and Quality of Experience degradation issues. A growing body of research is studying how to alleviate such traffic explosion. One of the most promising solutions consists in migrating the content in the metro and access segments of the network by deploying a system of Metro Servers (MSes) for VoD delivery. This way, the VoD traffic is kept as local as possible and the core network is traffic-offloaded. This paper investigates one of the most prominent risks by adopting this solution: in fact, if not carefully managed, a massive deployment of MSes in the network can lead to a significant increase of the overall energy consumption of the network. We first identify a consistent power model for the MSes and the network equipment in an integrated metro/access architecture scenario, then we define a strategy to switch on and off the network interfaces and the MSes depending on the VoD traffic load variation during the day. We show by means of simulations how our strategy always strikes the best trade-off between the energy consumption for content transport through the network and the energy consumption for processing and storage in the MSes.

공간정보 기반의 협업지원플랫폼 분석 및 구축

The fact that the limits of information recency, diversity, and usability are mainly caused by the supply oriented geospatial data and service development is commonly recognized. It is recently tried to overcome the limits by facilitating user experience and VGI(Volunteered Geographic Information) in several geospatial web services. This study suggests conceptual architecture and service scenario for geospatial collaborative platform prototype through review and examination of previous researches. The prototype, composed of 4 unit modules: 3D POI Creation Module, 3D POI Application Module, 3D POI/Event Management Module, 3D POI/Event Monitoring Module, provides the capability of collaboratively dealing with geospatial work. The suggested service scenario is demonstrated by developing prototype for the service modules.

A novel credibility-based group decision making method for Enterprise Architecture scenario analysis using Data Envelopment Analysis

Analysis and selection of Enterprise Architecture (EA) scenarios is a difficult and complex decision making process directly effecting the long-term business strategies realization. This complexity is associated with contradictory objectives and significant uncertainties involved in analysis process. Although a large body of intuitive and analytical models for EA analysis has evolved over the last few years, none of them leads to an efficient and optimized ranking in fuzzy environments. Moreover, it is necessary to simultaneously employ some complementary methods to reflect the ambiguity and vagueness as the main sources of uncertainty. This paper incorporates the concept of Data Envelopment Analysis (DEA) model into EA scenario analysis through a group analysis under uncertain conditions. To resolve the vagueness and ambiguity of the EA analysis, fuzzy credibility constrained programming and p-robustness technique are applied, respectively. Not only is the proposed DEA model linear, robust, and flexible in aggregating experts’ opinion in a group decision making process, but it also is successful in discrimination power improvement – a major shortcoming associated with classic DEA model. The proposed model provides useful solutions to support decision making process for large-scale Information Technology (IT) development planning.

Hacia un método de integración de procesos de negocio basado en escenarios, niveles arquitectónicos e información contextual

This paper presents a method of approaching business process integration, by taking into account contextual information related to architectural scenarios and levels of integration. The approach is validated through a case study related to the coffee industry. Based on this work, it can be concluded that the more information related to the context and its relationship to the domain and processes, it is possible to avoid unnecessary updates on processes and their variants are made.