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  • RESEARCH ARTICLE
    Shuyi MA, Jin LI, Jianping LI, Min XIE
    Frontiers of Engineering Management, https://doi.org/10.1007/s42524-023-0272-2

    Cloud systems, which are typical cyber–physical systems, consist of physical nodes and virtualized facilities that collaborate to fulfill cloud computing services. The advent of virtualization technology engenders resource sharing and service parallelism in cloud services, introducing novel challenges to system modeling. In this study, we construct a systematic model that concurrently evaluates system reliability, performance, and power consumption (PC) while delineating cloud service disruptions arising from random hardware and software failures. Initially, we depict system states using a birth–death process that accommodates resource sharing and service parallelism. Given the relatively concise service duration and regular failure distributions, we employ transient-state transition probabilities instead of steady-state analysis. The birth–death process effectively links system reliability, performance, and PC through service durations governed by service assignment decisions and failure/repair distributions. Subsequently, we devise a multistage sample path randomization method to estimate system metrics and other factors related to service availability. The findings highlight that the trade-off between performance and PC, under the umbrella of reliability guarantees, hinges on the equilibrium between service duration and unit power. To further delve into the subject, we formulate optimization models for service assignment and juxtapose optimal decisions under varying availability scenarios, workload levels, and service attributes. Numerical results indicate that service parallelism can improve performance and conserve energy when the workload remains moderate. However, as the workload escalates, the repercussions of resource sharing-induced performance loss become more pronounced due to resource capacity limitations. In cases where system availability is constrained, resource sharing should be approached cautiously to ensure adherence to deadline requirements. This study theoretically analyzes the interrelations among system reliability, performance, and PC, offering valuable insights for making informed decisions in cloud service assignments.

  • RESEARCH ARTICLE
    Qiufeng HE, Zezhou WU, Xiangsheng CHEN
    Frontiers of Engineering Management, https://doi.org/10.1007/s42524-023-0274-0

    With the burgeoning emphasis on sustainable construction practices in China, the demand for green building assessment has significantly escalated. The overall evaluation process comprises two key components: The acquisition of evaluation data and the evaluation of green scores, both of which entail considerable time and effort. Previous research predominantly concentrated on automating the latter process, often neglecting the exploration of automating the former in accordance with the Chinese green building assessment system. Furthermore, there is a pressing requirement for more streamlined management of structured standard knowledge to facilitate broader dissemination. In response to these challenges, this paper presents a conceptual framework that integrates building information modeling, ontology, and web map services to augment the efficiency of the overall evaluation process and the management of standard knowledge. More specifically, in accordance with the Assessment Standard for Green Building (GB/T 50378-2019) in China, this study innovatively employs visual programming software, Dynamo in Autodesk Revit, and the application programming interface of web map services to expedite the acquisition of essential architectural data and geographic information for green building assessment. Subsequently, ontology technology is harnessed to visualize the management of standard knowledge related to green building assessment and to enable the derivation of green scores through logical reasoning. Ultimately, a residential building is employed as a case study to validate the theoretical and technical feasibility of the developed automated evaluation conceptual framework for green buildings. The research findings hold valuable utility in providing a self-assessment method for applicants in the field.

  • COMMENTS
    Min WANG, Zi-Ke ZHANG
    Frontiers of Engineering Management, https://doi.org/10.1007/s42524-023-0277-x

    Reaching consensus within larger social network groups has emerged as a pivotal concern in the digital age of connectivity. This article redefines group consensus as the emergence of collective intelligence resulting from self-organizing actions and interactions of individuals within a social network group. In our exploration of extant research on group consensus, we illuminate two frequently underestimated, yet noteworthy facets: Dynamism and emergence. In contrast to the conventional perspective of consensus as a mere outcome, we perceive it as an ongoing, dynamic process. This process encompasses self-organized communication and interaction among group members, collectively guiding the group towards cognitive convergence and viewpoint integration. Consequently, it is imperative to redirect our focus from the outcomes of group interactions to an examination of the relationships and processes underpinning consensus formation, thus elucidating the mechanisms responsible for the generation of group consensus. The amalgamation of cognitive contexts and accurate simplification of real-world scenarios for simulation and experimental analysis offers a pragmatic operational approach. This study contributes novel theoretical underpinnings and quantitative insights for establishing and sustaining group consensus within the realm of engineering management practices. Concurrently, it holds substantial importance for advancing the broader research landscape pertaining to social consensus.

  • RESEARCH ARTICLE
    Jingjing XUE, Bin ZHENG, Sijie LI
    Frontiers of Engineering Management, https://doi.org/10.1007/s42524-023-0261-5

    Using the Hotelling model and evolutionary game theory, this paper studies the optimal production strategy of duopoly auto manufacturers and explores the impacts of two government policies (manufacturer and consumer subsidies) on strategies related to the production of electric vehicles (EVs) or fuel vehicles (FVs). The study finds that consumers’ environmental preferences have direct effects on manufacturers’ market shares and profits, which in turn, affect the manufacturers’ production strategy selection. Specifically, when consumer environmental preference is sufficiently high, both auto manufacturers will eventually choose to produce EVs; when it is moderate, only one with a cost advantage will choose to produce EVs. Finally, when it is low, neither auto manufacturer will produce EVs. The findings further reveal that the more significant the difference in EV production costs is, the more inclined auto manufacturers are to choose a different final stable strategy. Regardless of whether the government subsidizes manufacturers or consumers, the policy only works if subsidies reach a certain threshold. The study also identifies the conditions under which government subsidies are considered more cost-effective.