SELIS BDA: Big Data Analytics for the Logistics Domain

被引:1
作者
Provatas, Nikodimos [1 ]
Kassela, Evdokia [1 ]
Chalvantzis, Nikolaos [1 ]
Bakogiannis, Anastasios [1 ]
Giannakopoulos, Ioannis [1 ]
Koziris, Nectarios [1 ]
Konstantinou, Ioannis [2 ]
机构
[1] Natl Tech Univ Athens, Athens, Greece
[2] Univ Thessaly, Lamia, Greece
来源
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年
基金
欧盟地平线“2020”;
关键词
Logistics; Cloud Computing; Analytics;
D O I
10.1109/BigData50022.2020.9378421
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we present the SELIS Big Data Analytics and Machine Learning System (BDA), an open-source cloud-enabled elastic system that has been designed and implemented in order to address data related issues from the logistics domain. By taking into consideration real-life data analytics needs from more than 40 EU logistics providers we present the detailed SELIS BDA architecture along with the generic data and execution model devised to accommodate their diverse needs. We describe the main technologies we have utilized to realize the respective offering and justify our choices from the wider open-source Big Data systems community. We experimentally test our offering under various workloads where we prove that it can scale to serve a large number of concurrent requests while its abstraction/orchestration poses a very small overhead compared to the stand-alone Big Data systems. We believe that the SELIS BDA can be an easy-to-use entry point for the big data analytics world for any logistics company especially from the SME domain.
引用
收藏
页码:2416 / 2425
页数:10
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