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Internet of Things (IoT) devices facilitate intelligent service delivery in a broad range of settings, such as smart offices, homes and cities. However, the existing IoT access control solutions are mainly based on conventional identity management schemes and use centralized architectures. There are known security and privacy limitations with such schemes and architectures, such as the single-point failure or surveillance (e.g., device tracking). Hence, in this paper, we present an architecture for capability-based IoT access control utilizing the blockchain and decentralized identifiers to manage the identity and access control for IoT devices. Then, we propose a protocol to provide a systematic view of system interactions, to improve security. We also implement a proof-of-concept prototype of the proposed approach and evaluate the prototype using a real-world use case. Our evaluation results show that the proposed solution is feasible, secure, and scalable.

The development of next-generation electrodes is key for advancing performance parameters of lithium-ion batteries and achieving the target of net-zero emissions in the near future. Electrode architecture and design can greatly affect electrode properties and the effects are sometimes complicated. The architecture of current electrodes is designed mainly based on empirical studies by making trade-offs between battery performance parameters. Thus, a holistic understanding of the relationships between electrode architecture-property-performance is urgently needed. Additionally, the implementation of next-generation electrodes with optimised architectures also relies on manufacturing capability. Various manufacturing processes have been proposed to produce electrodes with characteristic architectures. Nevertheless, the merits and limitations of the manufacturing processes are not well understood and selecting appropriate manufacturing processes is challenging. Herein, ten manufacturing processes are illustrated, which have been classified into four categories of slurry casting, templating, additive manufacturing, laser ablation. The overall performance of all the manufacturing processes is first qualitatively compared from five different aspects of architectural controllability, scalability, sustainability, simplicity and cost, followed by a quantitative comparison using a Weighted Manufacturing Score method. This work provides a guideline for future electrode architectural design illustrating the limitations and potential advantages of different methodologies to stimulate the development of the next-generation LIB electrodes.

The various colors and color combinations in an urban environment are perceived and experienced individually. The article indicates the important role of color in shaping architecture and urban space. The paper discusses the theories of color harmony as an aesthetic principle in architectural design. The results of the research have proven the significant role of color as an element of the composition of urban space affecting the observer. This translates into the importance of color in architectural design, taking into account the difficulty and ambiguity in predicting color aesthetics; the impact of color on humans; and its cognitive, emotional and behavioral effects. The information and conclusions obtained as a result of the literature studies and the results of the survey gave the basis for determining various color strategies in shaping architecture and the effects that we can achieve in urban space thanks to a well-thought-out, conscious use of colors. The research findings also indicate that it is necessary to supplement architectural education programs with broadly understood knowledge about color and its impact on humans. The implemented activities are a response to current ideas and directions in designing and teaching architectural design outlined and suggested as part of the New European Bauhaus initiative.

Over the life cycle of a civil infrastructure (a bridge as an example), 0.4–2% of the construction cost is spent annually on its maintenance. Utilising new technologies including the internet of things (IoT) and digital twin (DT) can significantly reduce the infrastructure maintenance costs. An infrastructure DT involves its digital replica and must include data on geometric, geospatial reference, performance, attributes (material, environment etc.) and management. Then, the acquired data need to be analysed and visualised to inform maintenance decision making. To develop this DT, the first step is the study of the infrastructure life cycle to design DT architecture. Using data semantics, this paper presents a novel DT architecture design for an intelligent infrastructure maintenance system. Semantic modelling is used as a powerful tool to structure and organize data. This approach provides an industry context through capturing knowledge about infrastructures in the structure of semantic model graph. Using new technologies, DT approach derives and presents meaningful data on infrastructure real-time performance and maintenance requirements, and in a more expressible and interpretable manner. The data semantic model will guide when and what data to collect for feeding into the infrastructure DT. The proposed DT concept was applied on one of the conveyors of Dalrymple Bay Coal Terminal in Queensland Australia to monitor the structural performance in real-time, which enables predictive maintenance to avoid breakdowns and disruptions in operation and consequential financial impacts. [ABSTRACT FROM AUTHOR]

[Display omitted] Advances in miniaturized portable electronics and progress on novel enabling technologies, consequently accompanied by power consumption downgraded from the scale of milliwatts (mW) to microwatts (μW), have inevitably facilitate the development of an emerging discipline-wearable human energy conversion systems. Served as a passive human energy harvester which can directly convert heat into electricity in long-term operations without the user's intervention, wearable thermoelectric generators (WTEG) have sparked considerable research interest for next-generation power supply. In comparison to the longstanding research history of thermoelectrics, their wearables are still in infancy of extensive growth over the last decade. Although, historically, the main challenge behind the conventional thermoelectric generator (TEG) is the improvement of dimensionless figure-of-merit (zT), wearable applications usually impose additional restrictions that can be more pivotal than zT value. Diversified targeted strategies therefore have been proposed to push TEG toward wearable application. Here, we review the evolutionary roadmap of the wearable thermoelectric generators in the past decade, it could be concluded that the trend in WTEG is to move toward stretchable three-dimension (3D)-structure with rational thermal design at the moment. The basic concept targeting WTEG, which highly differs from that of the traditional TEG, is introduced at first. And then, aiming to provide detailed design guidelines for WTEG, we begin with carefully discussing the key issues for TEG toward wearable application. Finally, the specific strategies targeted WTEG that is classified into thermal design regarding extrinsic temperature difference (ΔT ext), parasitic and TEG thermal resistance, mechanical design with emphasis on optimizing deformability at materials/device level beyond flexibility toward stretchability, as well as architecture design from two-dimension (2D) to 3D feature are comprehensively summarized, respectively. With these understandings, perspectives for the future development of WTEG are outlined. This review emphasizes issues and provides additional insight in advanced strategies for pushing TEG toward wearable application. The key issues clarified and the design roadmap summarized here arise from the goal of providing ideas for the concurrent optimization of the future WTEG, as well as realistically promoting the TEG toward wearable application. [ABSTRACT FROM AUTHOR]

Continuous-flow microfluidic biochips have attracted high research interest over the past years. Inside such a chip, fluid samples of milliliter volumes are efficiently transported between devices (e.g., mixers, heaters, etc.) to automatically perform various laboratory procedures in biology and biochemistry. Each transportation task, however, requires an exclusive flow path composed of multiple contiguous microchannels during its execution period. Excess/waste fluids, in the meantime, should be discarded by independent flow paths connected to waste ports. All these paths are etched in a very tiny chip area using multilayer soft lithography and driven by flow ports connecting with external pressure sources, forming a highly integrated chip architecture that determines the final performance of biochips. In this article, we propose a new and practical design flow called PathDriver+ (PD+) for the architecture design of microfluidic biochips, integrating the actual fluid manipulations into both high-level synthesis and physical design, which has never been considered in prior work. With this design flow, highly efficient chip architectures with a flow-path network that enables the actual fluid transportation and removal can be constructed automatically. Meanwhile, fluid volume management between devices and flow-path minimization are realized for the first time, thus, ensuring the correctness of assay outcomes while reducing the complexity of chip architectures. Additionally, diagonal channel routing is implemented to fundamentally improve the chip performance. The tradeoff between the numbers of channel intersections and fluidic ports is evaluated to further reduce the fabrication cost of biochips. The experimental results on multiple benchmarks confirm that the proposed design flow leads to high assay execution efficiency and low overall chip cost. [ABSTRACT FROM AUTHOR]

Satellite Internet has the ability of global seamless coverage, which will be an important part of the future land-sea-air-space integrated network.Firstly, the architecture of satellite Internet was discussed, which included the general composition of the system, networking mode, working process, etc.Secondly, the methods of modeling broadband and narrowband traffic were proposed to extract the uneven space-time distribution characteristics of traffic for satellite Internet.Then, the co-frequency interference of spectrum-sharing was analyzed, showing that there would be more serious co-frequency interference among different non-geostationary satellite orbit (NGSO) constellations in the future.Next, the schemes of both beamforming design for low earth orbit satellite and beam-hopping design for high orbit satellite were explored, which could significantly improve the system capacity through efficient mining of space-domain resources.Finally, the development prospect of several technologies of satellite Internet were given.

The article examines methods for integrating 3D-stacked DRAM with AI logic chips, in order to overcome the memory bandwidth challenges faced in the AI inference of transformer models. The findings indicate that this approach can yield a 9x to 3x reduction in power consumption while maintaining similar performance levels, or alternatively, an 8x improvement in performance with comparable power consumption. • Proposes a novel 3D-stack DRAM architecture comparing with HBM and LPDDR. • Introduces a PNM-based architecture design for AI inference. • Yields a 9x to 3x reduction in power consumption while maintaining similar performance. [ABSTRACT FROM AUTHOR]

Abstract Due to the complexity of business ecosystems, the architecture of business ecosystems has not been well discussed in the literature, and modeling or simulation of business ecosystems has been rarely focused. Therefore, this paper proposes a business ecosystem ontology and introduces a methodology for business ecosystem architecture design. The proposed methodology includes five stages: 1) Boundary identification of a business ecosystem; 2) Identification of actors and their roles in the business ecosystem; 3) Identification of actors’ value propositions; 4) Identification of interaction between actors; 5) Verification of business ecosystem architecture design. This paper uses the Danish electricity system as an example to introduce the methodology, and use Electric Vehicle home charging as a case study to demonstrate the application of the developed methodology. The case study demonstrates that the proposed methodology is a systematic approach and can be easily applied to any ecosystem architecture design with the five stages, and the designed ecosystem architecture can represent the physical system and business. Several definitions are clarified in the paper, e.g., actor, role, interaction, ecosystem roadmap and expanded/shifted ecosystem, etc. With clear definitions, the proposed methodology provides a visualized, clear structure of behaviors and specifications for a given business ecosystem.

The ubiquitous power Internet of Things (UPIoT) is an intelligent service system with comprehensive state perception, efficient processing, and flexible application of information. It focuses on each link of the power system and makes full use of the mobile internet, artificial intelligence, and other advanced information and communication technologies in order to realize the inter-human interaction of all things in all links of the power system. This article systematically presents to the national and international organizations and agencies in charge of UPIoT layer standardization the status quo of the research on the Internet of Things (IoT)-related industry standards system. It briefly describes the generic standard classification methods, layered architecture, conceptual model, and system tables in the UPIoT application layer. Based on the principles of inheritance, innovation, and practicability, this study divides the application layer into customer service, power grid operation, integrated energy, and enterprise operation, emerging business and analyzes the standard requirements of these five fields. This study also proposes a standard plan. Finally, it summarizes the research report and provides suggestions for a follow-up work.

Lunar habitat design is a complex endeavor characterized by complicated task-composition, numerous internal iterations, and intense task-coupling. The design process of assembled building in terrestrial construction and the system composition of lunar habitats have been constructed. However, there is insufficient experience to fully understand lunar habitat design missions and likewise there is insufficient coordination between architects and various disciplines. The task flow for sequencing optimization can be determined using a design structure matrix (DSM), which is widely used in engineering. The DSM can reveal necessary interfaces within the lunar habitat system as per relevant interface variables and processes. By decomposing the lunar habitat design process, an initial activity-based DSM is established in the present study. Informational interactions between each design task and its respective intensity are statistically investigated to clarify them across the four dimensions of energy, space, materials, and information. A sequencing algorithm is applied to optimize the design process. Finally, 20 design tasks of lunar habitat design are clarified among four phases: Pre-planning, spatial design, environmental design, and optimization. Related disciplines should coordinate in the design process according to the optimization results, and use the optimized task coupling relationship to build the requirement model and design model in an orderly manner to improve the design efficiency.

Resistive random access memory (RRAM) is a promising technology for energy-efficient in-memory computing. However, due to technology limits, RRAM device faces a series of reliability issues. Deep neural network (DNN) computing based on RRAM suffers from accuracy degradation. On the one hand, offline DNN training solutions are difficult to fully consider and simulate all nonidealities. Worse still, new error or nonideality may come up with the usage of RRAM, which further deteriorates the effectiveness of offline training. On the other hand, online training poses great challenges on programming overhead and device lifetime. The iterative write-verify technique to program multi-bit RRAM cells prolongs write latency more than 10 × longer than read latency. To overcome these issues, we propose a compensation architecture and training designs to mitigate the realistic accuracy loss in RRAM chips with negligible hardware resource for RRAM-based DNN computing. Firstly, we add trainable compensation channels in crossbars utilizing the residual resource after original weight mapping. Secondly, an offline training procedure with computing output from hardware is triggered to settle down appropriate weight value in compensation channels. Experimental results demonstrate that the proposed design can guarantee ≤ 0.8% loss of accuracy in DNN even when nonidealities reduce the original accuracy down to ≤ 73%. [ABSTRACT FROM AUTHOR]

Nowadays, organizations need to follow the new trends and concepts to stay in the competitive environment and achieve a higher level of operational efficiency and productivity. Among all of the critical aspects affecting the performance of an enterprise, the technical side of a manufacturing system, from design to the final product, is in the area of this research. A great revolution occurred in manufacturing systems with the appearance of Industry 4.0. Manufacturing techniques are continuously evolving, especially due to shortening the products lifecycle. In fact, mobile robot systems need to be highly flexible. Increasing the mobility and flexibility beside the right design for manufacturing and assembly regarding an autonomous production system simultaneously results in the reduction of the overall manufacturing time and costs. This study aims to investigate the production performance improvement and flexibility growth through the successful integration of mobile manipulators into manufacturing systems. In this regard, a diagnostic method is required to investigate the existence of the prerequisites regarding industry 4.0. Integration should be considered from several different perspectives, such as suitable design for manufacturing and assembly, functionalities, connectivity, control, maintenance, skills, environment typology, management questions, etc. The new functionalities and features offered by this new technology are impressive and will contribute to more performance in the whole lifecycle. However, mobile robots embed a complex technology, and their integration requires a methodological approach. In this article some research topics have been reviewed from literatures: a) Existing mobile robot technologies and new features that will increase the operational performance of industry 4.0-based production systems, b) Integrate a mobile robot into a connected production line considering different phases in product lifecycle, and c) Design a new architecture to help integrating mobile robots into industry 4.0-based production sites. [ABSTRACT FROM AUTHOR]

The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a powerful semantic web construction method, ontology has been widely used to express design information, such as the concepts and the relationships between them. However, traditional graphical MBSE models have a naturalweakness in transforming into ontology. In this paper, a semanticMBSEmethod is proposed to support the transform of the ontology model. Firstly, according to the design characteristics of the aircraft PHM system, a meta-model library of the aircraft PHM system is developed to support the design and evaluation. An MBSE modeling method based on requirement analysis, function analysis, logical architecture design, and physic architecture design is applied in the PHM design process. Secondly, the semantic system modeling language KARMA based on "graph, object, property, point, relationship, role, and extension" (GOPPRRE) is used to transfer the graphicalMBSE model to the semanticMBSE model, which can be easily transformed to an ontology model. Finally, an ontology based on semantic modeling is developed to describe the MBSE entities and to support MBSE design. In this paper, a case study of an aircraft fuel PHM system is carried out to validate the proposed method. Based on the developed meta-model library, a complete MBSE design process for the aircraft PHM system is realized. And then an ontology model supporting PHM systemdesign is generated from the semanticMBSEmodel. The MBSE ontology provides a shareable capability to help designers communicate effectively. Quantitative analysis based on ontology is also provided to verify the complexity and scale of the MBSE design process. Moreover, logical reasoning ability can also be provided to support the early requirement traceability for MBSE design. In general, the case study results show the feasibility and effectiveness of the proposed method for the aircraft PHM system design. [ABSTRACT FROM AUTHOR]

This article explores the wide-ranging impact of inviting architecture students to increase conscious somatic awareness of their body and function, and the effects on their design process. This paper analyses the results of a Movement Awareness Intervention conducted prior to students undertaking their usual architectural design studio at the Queensland University of Technology, Brisbane, Australia. The impact of a global trend in extensive use of digital design tools has resulted in impacts on components in the architecture design process that appear to be slipping under the radar in architecture education and practice. This article addresses issues raised by Juhani Pallasmaa and Paolo Belardi, bolstered by neuroscience research by Harry Mallgrave and colleagues, to explore the impact of heightened conscious bodily awareness upon the cognitive design thinking processes required in the architecture. The case study research using mixed data collection methods on 39 participants draws upon surveys, hand notations, and audio interviews to track participant perceptions of the impact on their design process in action. Analysis of the data produced in this study addresses the concerns raised by theses seminal writers. This paper argues for new approaches to reconfiguring and recalibrating of emotional, cognitive, and physical stimulants that were once invisibly physically embedded in the traditional architectural design process to work with digital design technology. [ABSTRACT FROM AUTHOR]

LunAres Research Station is an analog research station for crewed space mission simulation, located at the abandoned airport in Poland. The facility provides full isolation, allowing for complex research on the psychological and physiological impact of long-term extra-terrestrial human presence. The general objective of LunAres is to create a research platform to support scientific and technological development in human space exploration. A broad range of specialists is involved in the study from fields like extreme medicine, psychology, biotechnology, robotics and engineering, sociology, architecture. The possible observation and control of the indoor environment, as well as telemetry of the crew's physical and psychological states, provide large quantities of data for complex studies. This paper presents an overview of the LunAres Research Station activity since its establishment in 2017. The contribution to scientific research and technology development is included. Based on the presented experience of carried missions and crews' feedback a roadmap regarding the station design advancement is determined. The decision-making process of development is presented finalized with the demonstration of the potential for future projects and studies regarding human missions and sustainability. The conclusions of upgraded functional plans and spaces were determined through research on existing references and the new strategy for LunAres. Detailed drawings regarding architectural and technical solutions as well as future steps will be introduced. • LunAres Research Station gathered feedback on infrastructure during conducted manned missions. • Analog missions can have a significant impact on pursuing SDG on Earth • Analog missions have can investigate the impacts of isolation during pandemic. • Human and environmental telemetry studies are essential for space missions. [ABSTRACT FROM AUTHOR]

Hydrogen energy is considered one of the cleanest and most promising alternatives to fossil fuel because the only combustion product is water. The development of water splitting electrocatalysts with Earth abundance, cost-efficiency, and high performance for large current density industrial applications is vital for H2 production. However, most of the reported catalysts are usually tested within relatively small current densities (< 100 mA cm−2), which is far from satisfactory for industrial applications. In this minireview, we summarize the latest progress of effective non-noble electrocatalysts for large current density hydrogen evolution reaction (HER), whose performance is comparable to that of noble metal-based catalysts. Then the design strategy of intrinsic activities and architecture design are discussed, including self-supporting electrodes to avoid the detachment of active materials, the superaerophobicity and superhydrophilicity to release H2 bubble in time, and the mechanical properties to resist destructive stress. Finally, some views on the further development of high current density HER electrocatalysts are proposed, such as scale up of the synthesis process, in situ characterization to reveal the micro mechanism, and the implementation of catalysts into practical electrolyzers for the commercial application of as-developed catalysts. This review aimed to guide HER catalyst design and make large-scale hydrogen production one step further.

The parallel architecture can improve the training speed of Deep learning models and it is beneficial to model optimization. This research designs Optimal Interleaved Distributed Architecture (OIDA). Its characteristics are (1) the data set that each child node participates in training is fixed and unique; (2) multiple approaches ensure that the model parameters of each child node participating in training each time are always optimal; (3) the computing units of each child node are interleaved for training without stopping. The architecture can be deployed as Single Machine Parallel (SMP) or Multi Machine Distributed (MMD), or a combination of both. The experimental results show that its efficiency is obvious in a multi-machine multi-card environment, and the model speed of training millions of parameters in a 5-machine 10-card lightweight (Graphics Processing Unit (GPU) of 2GB memory) cluster can reach megapixels/s. When training the same amount of training data, GPU can process data faster than Central Processing Unit (CPU) with the same number of clusters. 4-machine 4-core GPU parallel saves 65.61% of time compared with 4-machine 4-core CPU parallel, while 4-machine 8-core GPU saves 83.32% of time compared with 4-machine 4-core CPU parallel. For polarized Synthetic Aperture Radar (SAR) Deep learning data sets, increasing the number of computers in the cluster can effectively save training time. In the experimental environment of this research, there is no situation that when the number of computers in the cluster increases due to network data transmission, the training time does not decrease. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Medical Equipment Journal is the property of Chinese Medical Equipment Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The development of cloud infrastructures inspires the emergence of cloud-native computing. As the most promising architecture for deploying microservices, serverless computing has recently attracted more and more attention in both industry and academia. Due to its inherent scalability and flexibility, serverless computing becomes attractive and more pervasive for ever-growing Internet services. Despite the momentum in the cloud-native community, the existing challenges and compromises still wait for more advanced research and solutions to further explore the potential of the serverless computing model. As a contribution to this knowledge, this article surveys and elaborates the research domains in the serverless context by decoupling the architecture into four stack layers: Virtualization, Encapsule, System Orchestration, and System Coordination. Inspired by the security model, we highlight the key implications and limitations of these works in each layer, and make suggestions for potential challenges to the field of future serverless computing. [ABSTRACT FROM AUTHOR]

The employment of microwave absorbents is highly desirable to address the increasing threats of electromagnetic pollution. Importantly, developing ultrathin absorbent is acknowledged as a linchpin in the design of lightweight and flexible electronic devices, but there are remaining unprecedented challenges. Herein, the self-assembly VS4/rGO heterostructure is constructed to be engineered as ultrathin microwave absorbent through the strategies of architecture design and interface engineering. The microarchitecture and heterointerface of VS4/rGO heterostructure can be regulated by the generation of VS4 nanorods anchored on rGO, which can effectively modulate the impedance matching and attenuation constant. The maximum reflection loss of 2VS4/rGO40 heterostructure can reach − 43.5 dB at 14 GHz with the impedance matching and attenuation constant approaching 0.98 and 187, respectively. The effective absorption bandwidth of 4.8 GHz can be achieved with an ultrathin thickness of 1.4 mm. The far-reaching comprehension of the heterointerface on microwave absorption performance is explicitly unveiled by experimental results and theoretical calculations. Microarchitecture and heterointerface synergistically inspire multi-dimensional advantages to enhance dipole polarization, interfacial polarization, and multiple reflections and scatterings of microwaves. Overall, the strategies of architecture design and interface engineering pave the way for achieving ultrathin and enhanced microwave absorption materials. [ABSTRACT FROM AUTHOR]

We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accuracy and search efficiency under tight time and computing constraints. We propose structured empirical evaluations as the most promising avenue to obtain design principles for deep-learning systems due to the absence of strong theoretical support. From these evaluations, we distill relevant patterns which give rise to neural network design recommendations. In particular, we establish (a) that very wide fully connected layers learn meaningful features faster; we illustrate (b) how the lack of pretraining in audio processing can be compensated by architecture search; we show (c) that in text processing deep-learning-based methods only pull ahead of traditional methods for short text lengths with less than a thousand characters under tight resource limitations; and lastly we present (d) evidence that in very data- and computing-constrained settings, hyperparameter tuning of more traditional machine-learning methods outperforms deep-learning systems.

With the rapid development of computer tech-nology and environmental protection requirements, the mineral resources industry and information technology industry are highly integrated. Since the end of the 20th century, China has vigorously promoted the informatization construction of land and resources, including oil and gas resources, and has achieved good results. As the state puts forward new management requirements for oil and gas mineral properties and begins to implement new mineral properties management system and environmental protection concept, the workload of mineral properties evaluation, mineral properties protection and mineral properties management increases sharply. Taking Changqing Oilfield in China as an example, the existing software system cannot meet the needs of mineral property management of oilfield companies. Therefore, we take the spatial data of mineral property as the main line, introduce the spatial GIS analysis technology, and establish the intelligent mineral property information management platform, combined with the new mineral property policy and the demand of mineral property management, effectively supporting the annual survey, evaluation and management of mineral property of oilfield company. The platform will realize the integration and upgrading of the existing system, realize the efficient management of mineral properties in the oilfield, meet the convergence requirements of the national mineral properties management and environmental protection concept, and meet the internal mineral properties management of the oilfield company, so as to provide comprehensive, efficient and convenient information services for the annual survey, evaluation, and management of mineral properties in the oilfield company. [ABSTRACT FROM AUTHOR]

With the rapid development of communication and the rise of new network services, the resource provisioning of the optical access network becomes more significant than before, especially under the multiple-domain networking situation with the requirement of cross-domain service support. For the sake of high resource utilization to establish more connections of services, this paper proposes a cross-domain resource allocation (CDRA) scheme in a software-defined optical access network to meet the huge bandwidth supporting the requirement of new network services. To achieve this purpose, the global evaluation strategy with the consideration of the traffic situation in each node in its domain is presented in the CDRA scheme, and its interaction process makes decisions for comprehensive optimal resource allocation by integrating radio resources and optical aggregation resources of the entire access network. Furthermore, to manage the resources among multiple domains and support the interaction process of the CDRA scheme, a cross-domain unified control architecture is firstly upgraded by using software-defined networking technology, which includes the further design of CDRA function modules with the global evaluation strategy. The simulation results verify the feasibility of the upgraded architecture and further show that the proposed CDRA scheme can effectively decrease the blocking probability with a 29.35% improvement, balance the network load, and enhance the utilization of network resources of the network.

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Business ecosystem is popularly used to investigate a complex social system with the business perspective, and particularly contributes to the understanding of actors and their relations in the innovation research. However, the aspect of business ecosystem modeling is limited discussed in the literature, although the importance has emerged significantly in recent years due to the emphasis on cross-disciplinary research and digitalization with artificial intelligence. Therefore, this paper proposes a framework for business ecosystem modeling with the discussion of system engineering and ecological modeling. The domain of smart grid is selected to demonstrate how system engineering, especially standards and ontologies contribute to the business ecosystem modeling. The proposed framework of the business ecosystem modeling includes three parts and nine stages that combines theories from system engineering, ecology, and business ecosystem. Part I-Business ecosystem architecture development includes four stages which aims to identify a target business ecosystem and its elements (actors, roles, and interactions). Part II-Factor analysis includes two stages to identify potential changes (and the dimensions of the changes) in the ecosystem. Part III- Ecosystem simulation and reconfiguration aims to use simulations to investigate the transition of an ecosystem and the re-configurated ecosystem. The framework not only provides a systematic approach for modeling a business ecosystem but also provides a methodological foundation for research on the aspect of complex systems in the business ecosystem field.

Abstract The aim of the work is to show the use of BIM in a spatial economy. It will be achieved by carrying out research experience, which involves creation of the concept of functional and spatial architectural design of multi-family building at Czestochowska Street in Bialystok, Poland. The research experiment is carried out with: design intent - which contains: a function of building and its urban context, aesthetics of object, factor 4D and 5D in accordance with the methodology of BIM; evaluation of "existence" of building on today's market development, and number of factors about architecture and spatial economy; In conclusion, the authors described the potential use of BIM technology in one of the areas of spatial economy, which has the greatest influence in the life cycle of buildings - building management. This area is based on close cooperation between specialists in this field with specialists from other fields of AEC industry, and relationships online specialist-client. BIM technology meets the abovementioned factors because BIM software creates the possibility to realize attractive 3D presentation of building, which may increase the chance to sell presented "product"; BIM improves standard methods of presentation, enriching them with the possibility of detailed fit and conclusion of specific contents into individual customer needs and expectations; use of BIM does not require from specialist spend an inordinate amount of time to achieve satisfactory results, due to focusing in one database, which contain different data about building; BIM allows all participants, involved in the life cycle of the building, to work on one BIM model, which can be exported and imported in IFC format; BIM technology is based on cooperation between individual AEC industries, and its spectrum is so vast, that it is a universal tool to solve any issues and problems related to the life cycle of the building. Resumen El objetivo del trabajo es mostrar el uso de BIM en la economía espacial. Se logrará mediante la realización de una experiencia de investigación, que implica la creación del concepto de diseño arquitectónico funcional y espacial del edificio multifamiliar en la calle Częstochowska en Białystok. El experimento de investigación se lleva a cabo con: intención de diseño - que contiene: función del edificio y su contexto urbano, estética del objeto, factor 4D y 5D de acuerdo con la metodología de BIM; evaluación de la "existencia" de construir sobre el desarrollo del mercado actual, y varios factores sobre la arquitectura y la economía espacial; En conclusión, los autores describieron el uso potencial de la tecnología BIM en una de las áreas de economía espacial, que tiene la mayor influencia en el ciclo de vida de los edificios: la administración de edificios. Esta área se basa en una estrecha cooperación entre especialistas en este campo con especialistas de otros campos de la industria de AEC y relaciones en línea con especialistas-clientes. La tecnología BIM cumple con los factores mencionados anteriormente porque: el software BIM crea la posibilidad de realizar una presentación 3D atractiva del edificio, lo que puede aumentar la posibilidad de vender el "producto" presentado; BIM mejora los métodos estándar de presentación, enriqueciéndolos con la posibilidad de un ajuste detallado y la conclusión de contenido específico en las necesidades y expectativas individuales del cliente; el uso de BIM no requiere que los especialistas dediquen una cantidad excesiva de tiempo para lograr resultados satisfactorios, debido al enfoque en una base de datos, que contiene datos diferentes sobre la construcción; BIM permite a todos los participantes, involucrados en el ciclo de vida del edificio, trabajar en un modelo BIM, que se puede exportar e importar en formato IFC; La tecnología BIM se basa en la cooperación entre industrias AEC individuales, y su espectro es tan amplio, que es una herramienta universal para resolver cualquier problema o problema relacionado con el ciclo de vida del edificio.

The in-cessation trend of railways ramification calls for railway sensing on an urgent basis. Railway sense is required to keep suspecting potential danger in a large scope and provide a safe transportation environment. The fundamental infrastructure to realize railway sensing comprises of space and terrestrial integrated network (STIN) nodes, such as high-speed railway, trackside equipment, unmanned aerial vehicle, airship, and remote sensing satellite. This architecture needs to support diverse applications flexibly and ensure efficient infrastructure management. Inspired by the philosophy of software-defined network, which attempts to give more flexibility to networks, we propose a software-defined sensing and integrated architecture for such a network. We decouple the railway sensing application from the physical infrastructure. Besides, we designed centralized controllers to manage physical facilities and supply APIs of data processing, including acquisition, transmission, computation, and storage. Various applications can share common infrastructure with such properties, and each of these applications can customize its data acquisition, transmission, and computing by requesting APIs of controllers. This paper includes discussions of the design details of the proposed architecture and benefits. We also proposed some open problems and the potential solutions to solve them, which we hope to provide railway sensing research in a new direction.

The emergence of augmented reality (AR), autonomous driving and other new applications have greatly enriched the functionality of the vehicular networks. However, these applications usually require complex calculations and large amounts of storage, which puts tremendous pressure on traditional vehicular networks. Mobile edge computing (MEC) is proposed as a prospective technique to extend computing and storage resources to the edge of the network. Combined with MEC, the computing and storage capabilities of the vehicular network can be further enhanced. Therefore, in this paper, we explore the novel collaborative vehicular edge computing network (CVECN) architecture. We first review the work related to MEC and vehicular networks. Then we discuss the design principles of CVECN. Based on the principles, we present the detailed CVECN architecture, and introduce the corresponding functional modules, communication process, as well as the installation and deployment ideas. Furthermore, the promising technical challenges, including collaborative coalition formation, collaborative task offloading and mobility management, are presented. And some potential research issues for future research are highlighted. Finally, simulation results are verified that the proposed CVECN can significantly improve network performance.