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Modelling and simulation of Opportunistic IoT Services with Aggregate Computing

机译:聚合计算的机会物联网服务建模与仿真

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The Internet of Things (IoT) is emerging as a ubiquitous and dense ecosystem in which novel devices and smart objects interoperate to establish smart cities, smart buildings, etc. In such application contexts, a plethora of innovative services are expected to stand out, deeply impacting our daily routine. In particular, real IoT drivers will be cyberphysical, collective, highly dynamic and contextualised services, called in the following Opportunistic IoT Services. This work proposes a full-fledged approach for their development, based on (i) a technology-agnostic yet detailed modelling phase, which allows opportunistic properties to emerge since the preliminary service analysis; and (ii) the implementation and further simulation of IoT services through Aggregate Computing, a distributed computing paradigm and engineering stack able to harness, in practice, the dynamic, collective and context-driven nature of Opportunistic IoT Services. A mass event case study, related to the real-world scenario of a large scale urban crowds detection and steering, provides evidence of the huge potential of the approach: indeed, simulation results highlight the effectiveness, flexibility, scalability and resilience of the Aggregate Computing-based approach to the design of Opportunistic IoT Services. (C) 2018 Elsevier B.V. All rights reserved.
机译:物联网(IoT)正在崛起,成为一个无处不在且密集的生态系统,其中新颖的设备和智能对象可以互通以建立智能城市,智能建筑等。在这样的应用环境中,有望有大量创新服务深刻地脱颖而出。影响我们的日常工作。特别是,真正的物联网驱动程序将是网络物理,集体,高度动态和上下文相关的服务,在以下机会物联网服务中称为。这项工作基于以下方面提出了一种成熟的开发方法:(i)与技术无关的详细建模阶段,该阶段允许在进行初步服务分析后出现机会属性; (ii)通过聚合计算(一种可以在实践中利用机会性IoT服务的动态,集体和上下文驱动的特性的分布式计算范例和工程堆栈)来实现和进一步仿真IoT服务。大规模事件案例研究与大规模城市人群检测和控制的真实场景相关,提供了该方法巨大潜力的证据:确实,仿真结果突出了聚合计算的有效性,灵活性,可扩展性和弹性物联网服务设计的基于方法。 (C)2018 Elsevier B.V.保留所有权利。

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