利用移动人群计算实现可持续边缘计算:智能暖通空调用例的概念验证

Pijush Kanti Dutta Pramanik, Saurabh Pal, Moutan Mukhopadhyay, Prasenjit Choudhury
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引用次数: 0

摘要

随着基于公用事业的实时应用的广泛采用,有必要大规模部署边缘计算基础设施。众包边缘计算被认为是一条合适的出路。另一方面,集合当今功能强大的智能移动设备(SMD)可以累积提供高性能计算。公共所有的 SMD 可伺机利用,形成一个动态的临时计算网格,即移动人群计算(MCC)。本文旨在为 MCC 作为可持续边缘计算解决方案(MCC-edge)的可行性和使用建立概念验证。实验案例考虑了一栋办公楼的典型智能暖通空调系统。我们的目标是使用楼内的 MCC-edge 设置实时处理暖通空调数据,以便自动调节空调控制器并发出错误通知。为了保持住户的理想舒适度,我们利用房间的露点和热指数进行了大量计算。我们介绍了用于暖通空调的 MCC-edge 高级分层架构以及 MCC-edge 的总体框架。我们详尽报告了模块化设计和实施程序。在成本、能耗、延迟和环境影响方面,我们将 MCC-edge 的性能与商业边缘计算和云计算解决方案进行了统计比较,结果表明,MCC-edge 在这两方面具有显著优势。每个模块的设计、开发和实施的每一个程序细节都得到了细致的介绍,这将有助于感兴趣的读者和研究人员重建这样一个应用程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Sustainable edge computing with mobile crowd computing: a proof-of-concept with a smart HVAC use case

Sustainable edge computing with mobile crowd computing: a proof-of-concept with a smart HVAC use case

The widespread adoption of utility-based real-time applications has placed the necessity of widescale deployment of edge computing infrastructure. Crowdsourced edge computing is deemed a suitable way out. On the other hand, a collection of today’s powerful smart mobile devices (SMDs) can cumulatively offer high-performance computing. The public-owned SMDs are utilized opportunistically to form a dynamic ad-hoc computing grid known as mobile crowd computing (MCC). This paper aspires to establish a proof-of-concept for the feasibility and use of MCC as a sustainable edge computing solution (MCC-edge). A typical smart HVAC system of an office building has been considered for the experiment case. We aim to process the HVAC data in real-time using the MCC-edge setup within the building for auto adjustment of the AC controller and error notifications. To maintain the ideal comfort level of the occupants, we present an extensive calculation using the dew point and heat index of the room. A high-level layered architecture of the MCC-edge for HVAC is presented along with a general framework of the MCC-edge. We report the module-wise design and implementation procedures with exhaustive details. The performance of MCC-edge is statistically compared with the commercial edge and cloud computing solutions in terms of cost, energy consumption, latency, and environmental impact, showing a significant advantage over the two. Every procedural detail of each module's design, development, and implementation is meticulously presented, which would aid interested readers and researchers in rebuilding such an application.

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