用于物联网环境中复杂事件质量感知评估的混合仿真平台

IF 3.5 2区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Simulation Modelling Practice and Theory Pub Date : 2024-03-04 DOI:10.1016/j.simpat.2024.102919
Dimitris Gkoulis, Cleopatra Bardaki, Mara Nikolaidou, George Kousiouris, Anargyros Tsadimas
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引用次数: 0

摘要

复杂事件处理(CEP)是将传感器产生的简单物联网事件转化为有意义的复杂业务事件的一种成功方法。为提高可用性,在 CEP 模型中集成了事件制造机制,生成合成事件以抵消缺失数据,从而形成质量感知的 CEP 模型。在该模型中,生成的复杂事件具有质量属性,即完整性和及时性。为了通过实验对复杂事件的质量进行实证评估,我们开发了一个混合模拟平台。该平台的双重性质源于其独特的方法,即在模拟传感器行为的同时运行质量感知 CEP 物联网平台。用户可以进行近似实际操作场景的实验,并实时全面了解和控制所有相关方面,包括复合转换、质量评估、事件制造及其有效性以及汇总报告。为了展示该平台的实用性,我们介绍了在一个物联网温室中进行的具有代表性的缺失事件实验。混合仿真平台有两方面的贡献:a)提供复杂事件的质量评估,为物联网环境使用两个既定的质量属性和特定的计算公式;b)提供全面的测试平台,涵盖典型物联网设置的所有方面,以进行实际实验。这些要素结合在一起,使研究人员和从业人员能够预先优化物联网系统的运行效率和决策,从而带来显著的成本效益优势。
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A Hybrid Simulation Platform for quality-aware evaluation of complex events in an IoT environment

Complex Event Processing (CEP) is a successful method to transform simple IoT events created by sensors into meaningful complex business events. To enhance availability, an event fabrication mechanism is integrated within the CEP model, generating synthetic events to offset missing data, resulting in a quality-aware CEP model. In this model, generated complex events are characterized by quality properties, namely completeness and timeliness. To empirically assess the quality of complex events through experimentation, we have developed a hybrid simulation platform. The platform’s dual nature stems from its distinctive approach of simulating sensor behaviors while concurrently running the quality-aware CEP IoT platform. Users can conduct experiments that closely mimic actual operational scenarios and have, in real-time, full visibility and control over all involved aspects, including composite transformations, quality assessment, event fabrication and its effectiveness, and aggregated reports. A representative experiment in an IoT-enabled greenhouse with missing events is presented to demonstrate the usefulness of the platform. The contribution of the hybrid simulation platform is twofold: provide (a) quality assessment of complex events, using two established quality properties for IoT environments with specific computation formulas and (b) a comprehensive testbed covering all aspects of a typical IoT setup for realistic experimentation. Together, these elements provide significant cost–benefit advantages by enabling researchers and practitioners to pre-optimize operational efficiency and decision-making in IoT systems.

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来源期刊
Simulation Modelling Practice and Theory
Simulation Modelling Practice and Theory 工程技术-计算机:跨学科应用
CiteScore
9.80
自引率
4.80%
发文量
142
审稿时长
21 days
期刊介绍: The journal Simulation Modelling Practice and Theory provides a forum for original, high-quality papers dealing with any aspect of systems simulation and modelling. The journal aims at being a reference and a powerful tool to all those professionally active and/or interested in the methods and applications of simulation. Submitted papers will be peer reviewed and must significantly contribute to modelling and simulation in general or use modelling and simulation in application areas. Paper submission is solicited on: • theoretical aspects of modelling and simulation including formal modelling, model-checking, random number generators, sensitivity analysis, variance reduction techniques, experimental design, meta-modelling, methods and algorithms for validation and verification, selection and comparison procedures etc.; • methodology and application of modelling and simulation in any area, including computer systems, networks, real-time and embedded systems, mobile and intelligent agents, manufacturing and transportation systems, management, engineering, biomedical engineering, economics, ecology and environment, education, transaction handling, etc.; • simulation languages and environments including those, specific to distributed computing, grid computing, high performance computers or computer networks, etc.; • distributed and real-time simulation, simulation interoperability; • tools for high performance computing simulation, including dedicated architectures and parallel computing.
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