تقرير
Crowd tracking and monitoring middleware via Map-Reduce
| العنوان: | Crowd tracking and monitoring middleware via Map-Reduce |
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| المؤلفون: | Gazis, Alexandros, Katsiri, Eleftheria |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Distributed, Parallel, and Cluster Computing, K.6.3, C.5.2, C.5.3, C.5.5, C.5.m, C.5.0 |
| الوصف: | This paper presents the design, implementation, and operation of a novel distributed fault-tolerant middleware. It uses interconnected WSNs that implement the Map-Reduce paradigm, consisting of several low-cost and low-power mini-computers (Raspberry Pi). Specifically, we explain the steps for the development of a novice, fault-tolerant Map-Reduce algorithm which achieves high system availability, focusing on network connectivity. Finally, we showcase the use of the proposed system based on simulated data for crowd monitoring in a real case scenario, i.e., a historical building in Greece (M. Hatzidakis' residence).The technical novelty of this article lies in presenting a viable low-cost and low-power solution for crowd sensing without using complex and resource-intensive AI structures or image and video recognition techniques. Comment: 18 pages, 7 figures, 4 tables, 23 references, This is an Accepted Manuscript of an article published by Taylor & Francis Group in the International Journal of Parallel, Emergent & Distributed Systems on 2022, available online: http://www.tandfonline.com/10.1080/17445760.2022.2034163 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.1080/17445760.2022.2034163 |
| URL الوصول: | http://arxiv.org/abs/2201.09550 |
| رقم الأكسشن: | edsarx.2201.09550 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.1080/17445760.2022.2034163 |
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