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\"How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman's extremely popular Building Microservices, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture. With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You'll learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture.\"-- Provided by publisher

Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a collection of software systems that have been developed to coexist and evolve together. The stakeholders of such a system need a variety of models to give them a perspective of the possibilities of the system, to evaluate specific quality attributes, and to extend the system. A powerful representation when building or using software ecosystems is the use of architectural models, which describe the structural aspects of such a system. These models have value for security and compliance, are useful to build new systems, can be used to define service contracts, find where quality factors can be monitored, and to plan further expansion. We have described a cloud ecosystem in the form of a pattern diagram where its components are patterns and reference architectures. A pattern is an encapsulated solution to a recurrent problem. We have recently expanded these models to cover fog systems and containers. Fog Computing is a highly-virtualized platform that provides compute, storage, and networking services between end devices and Cloud Computing Data Centers; a Software Container provides an execution environment for applications sharing a host operating system, binaries, and libraries with other containers. We intend to use this architecture to answer a variety of questions about the security of this system as well as a reference to design interacting combinations of heterogeneous components. We defined a metamodel to relate security concepts which is being expanded.

This paper focuses on the development and deployment of a dApp (decentralized Application) for Smart Crop Production Data exchange (SCPDx) that runs on Antelope blockchain/IPFS infrastructure. The paper emphasizes practical approaches to dApp design and deployment, analyses architectural patterns of dApps, and underlines the role of smart contracts in implementing complex functionality. The paper’s contribution is the detailed description of the main smart contracts and the practical knowledge provided on the architecture and implementation of dApps, emphasizing the challenges and solutions in the development process, especially in the context of smart contract implementation. Future developments of the application towards additional data types processing, and design of an interface for leveraging, testing, and evaluating the performance of open source Large Language Models (LLMs) on specific datasets are commented on.

Carbonate sediments are susceptible to many factors, such as paleostructure, diagenesis, and strong microbial alteration; as such, their sedimentary architecture still calls for further research. In this study, the reef and shoal bodies in the XVm and XVp layers of the Middle–Upper Jurassic Karlov-Oxfordian in the S gas field were used as the object, and the architecture of the reef-shoal facies was studied. Based on the idea of “vertical grading and horizontal boundary”, the interface characteristics of the 6th to 4th levels of reef-shoal bodies in the study area were summarized, as were four ways to determine the boundaries of reef-shoal bodies. Based on the dense well network, we quantitatively described the scale of each small layer of single reef shoal body through the point-line-surface method and established a geological database of the reef shoal bodies in the study area. In addition, we established the width and thickness of the reef shoal body and the empirical formula for relationships. The study of morphological characteristics of reef-shoal bodies and the degree of overlap revealed six architecture models of reef-shoal bodies. The vertical and lateral superimposed reefs were obtained by evaluating the reservoir space, pore throat characteristics, and physical property characteristics corresponding to various architecture models. The vertical and lateral superimposed shoals corresponded to large reservoir thicknesses. The petrophysical properties were good, and we concluded that the reef-shoal superimposed area was a sweet spot for reservoir development. We applied the research results of reef-shoal architecture reservoir characteristics to gas field development, and therefore improved well pattern deployment in the reef-shoal superimposed area. By comparing the test results of newly deployed horizontal wells with adjacent vertical wells, we confirmed that the selection of horizontal wells was better for gas field development. This study on the architecture of reef-shoal facies could guide the study of carbonate rock architecture.

Security is one of the biggest concerns for cloud infrastructures. Cloud infrastructures are susceptible to a wide range of threats, including external and internal threats. Without proper security mechanisms, these threats may compromise the security properties of services hosted in the cloud. To secure cloud infrastructures against threats, it is crucial to perform a threat analysis in the early stages of the system development (i.e., during the design of the system architecture). Threat Analysis and Risk Assessment (TARA) is a well-known approach used by researchers and practitioners. TARA consists of several activities, including asset identification, threat scenarios, attack paths, and risk treatment decision. The risk treatment decision activity involves selecting appropriate security measures to mitigate the identified threat scenarios. In the current state of practice, TARA activities are performed manually by engineers, leading to time-consuming processes and potential errors. In our previous article, we proposed a logic programming tool to enable the automation of TARA activities, including the recommendation of cloud-based security measures. This article proposes Security Pattern Synthesis, a Model-Based Systems Engineering (MBSE) plugin for securing cloud architectures. Security Pattern Synthesis is implemented in Java while using the previously proposed logic-programming tool as a backend to reason about the security of the cloud architecture.

Based on current manual restoration methods, a better algorithm for restoring images based on sample blocks is proposed, along with a sustainable restoration technique for digital virtualization, with the aim of preserving and restoring the priceless art of ancient architectural motifs. The paper uses curve fitting to pre-process the restored photos by re-constructing their damaged borders and filling in the structural information that is absent with the aid of an enhancement of the Criminisi method. The repaired photos have improved edges that were previously blurry, fractured, and over-extended. In order to increase the dependability of the priority calculation when restoring photos and make it possible to acquire a more precise restoration order, we rewrote the priority calculation formula for restoration blocks in the Criminisi algorithm. The purpose was to enhance the aesthetics of the photographs and provide a viable and sustainable restoration technique for the restoration of ancient architectural motifs in Fujian. The Criminisi algorithm with deep learning is used in the thesis to fully restore the content, color, and texture of the architectural photographs, bringing the murals as close to their original state as is practical. In order to improve the blurry, broken, and over-extended edges of the restored images, the broken edges of the images are first repaired through image pre-processing. Then, adjustment factors are added to the priority calculation to increase the weight of the data items, resulting in a more accurate priority order while preventing the priority values from degrading quickly in the later stages of restoration. The PSNR values of the restored images were calculated and compared to those of the Criminisi method, demonstrating that the revised algorithm produces better restoration results and can effectively improve restoration efficiency while lowering restoration costs and ensuring pattern restoration sustainability. By retaining as much of the structural information of the original image as possible in the design of the network model and allocating larger weights to the structural part, this process also uses style migration in deep learning to restore the texture and color of the mural. As a result, the final image is as similar to the original image as possible in terms of content and as similar as possible to the style image in terms of color and texture. A better solution is proposed based on the Criminisi algorithm. By comparing the experimental results of the three sets of building images, the PSNR values of the priority improvement algorithm (30.26, 38.06, 39.56) were significantly better than those of the Criminisi algorithm (27.59, 37.06, 37.59), using the peak signal-to-noise ratio (PSNR) values as a reference standard. In order to determine the appropriate restoration sequence and enhance the quality of picture repair, the broken edges of the pattern are strengthened. The algorithm’s matching criteria can be applied in subsequent work to improve sample-matching accuracy and produce better sustainable restoration results for ancient architectural patterns in Fujian. It no longer requires specialized professional knowledge to reproduce the color of faded architectural photos; instead, a style migration approach is employed to recover the color and texture of architectural images. This study proposes the use of a texture synthesis method and a layered processing method through which the PSNR values of the resulting restored images calculated are superior and significantly higher than those of the sample-based method and the variational framework of synthetic images with regular texture components. We achieved the creation of an updated Criminisi algorithm-based solution that improves the quality of image restoration by fortifying the pattern’s frayed edges and determining the optimum repair order. These two techniques can be combined to improve the sustainability of restoration of faded architectural photographs for issues such as pattern breakage, color loss and fading. To achieve better restoration results for the historic architectural patterns in Fujian, the accuracy of sample matching can be increased, starting with the algorithm’s matching criterion.

As rail transit systems advance toward greater automation and intelligence, cloud computing technology, with its remarkable scalability and robust data processing capabilities, has been steadily expanding its footprint in this domain. However, the adoption of cloud computing also introduces new safety challenges for train control systems. Traditional safety computers in train control systems rely on heterogeneous redundancy with symmetry to enhance safety. Nevertheless, the software in cloud computing environments, even if heterogeneous, may share the same source code, thereby triggering the risk of common-cause failures in the software. To address these issues, this study proposes a multi-level monitoring architecture system tailored to the characteristics of cloud-based safety computing platforms. This architecture innovatively integrates the three-level monitoring architecture pattern from the automotive field, the secure channel pattern, and the distributed safety mechanism architecture. It monitors the levels of common-cause software failures that cannot be eliminated through heterogeneity. The introduction of multi-level active monitoring for risk control has reduced the impact of common-cause software failures on system security. By constructing a formal security model, quantitative evaluations are conducted separately on the single-channel L2 and L3, the dual-channel L4 without degradation or monitoring, and the dual-channel L4 monitoring architecture with complete functions. This verifies the effectiveness of the proposed monitoring architecture in reducing the risk of common-cause software failures in the virtualization layer. This study provides a robust theoretical foundation and technical support for the security-oriented design and development of the next-generation intelligent rail transit systems.

The architecture of a system is decided at the initial stage of the design. However, the robustness of the system is not usually assessed in detail during the initial stages, and the exploration of alternative system architectures is limited due to the influence of previous designs and opinions. This article presents a novel network generator that enables the analysis of the robustness of alternative system architectures in the initial stages of design. The generator is proposed as a network tool for system architectures dictated by their configuration of source and sink components structured in a way to deliver a particular functionality. Its parameters allow exploration with theoretical patterns to define the main structure and hub structure, vary the number, size, and connectivity of hub components, define source and sink components and directionality at the hub level and adapt a redundancy threshold criterion. The methodology in this article assesses the system architecture patterns through robustness and modularity network based metrics and methods. Two naval distributed engineering system architectures are examined as the basis of reference for the simulated networks. The generator provides the capacity to create alternative complex system architecture options with identifiable patterns and key features, aiding in a broader explorative and analytical, in-depth, time and cost-efficient initial design process.

Architectural facades now have the potential to be literally kinetic, through automated sunscreens and a range of animated surfaces. This book explores the aesthetic potential of these new types of moving facades. Critique of theory and practice in architecture is combined here with ideas from kinetic art of the 1960's. From this background the basic principles of kinetics are defined and are used to generate experimental computer animations. By classifying the animations, a theory of kinetic form called 'state change' is developed. This design research provides a unique and timely resource for those interested in the capacity of kinetics to enliven the public face of architecture. Extra material including animations can be seen at www.kineticarch.net/statechange