Data collection from WSNs to the cloud based on mobile Fog elements

被引:100
作者
Wang, Tian [1 ]
Zeng, Jiandian [1 ]
Lai, Yongxuan [2 ]
Cai, Yiqiao [1 ]
Tian, Hui [1 ]
Chen, Yonghong [1 ]
Wang, Baowei [3 ]
机构
[1] Huaqiao Univ, Coll Comp Sci & Technol, Xiamen, Fujian, Peoples R China
[2] Xiamen Univ, Sch Comp & Software, Xiamen, Fujian, Peoples R China
[3] Univ Informat Sci & Technol, Nanjing, Jiangsu, Peoples R China
来源
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE | 2020年 / 105卷
关键词
Fog computing; Mobile sinks; Sensor-cloud; Data collection; SENSOR-CLOUD; COVERAGE; SEARCH;
D O I
10.1016/j.future.2017.07.031
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The powerful computing and storage capability of cloud computing can inject new vitality into wireless sensor networks (WSNs) and have motivated a series of new applications. However, data collection from WSNs to the Cloud is a bottleneck because the poor communication ability of WSNs, especially in delay-sensitive applications, limits their further development and applications. We propose a fog structure composed of multiple mobile sinks. Mobile sinks act as fog nodes to bridge the gap between WSNs and the Cloud. They cooperate with each other to set up a multi-input multi-output (MIMO) network, aiming to maximize the throughput and minimize the transmission latency. We district collecting zones for all sinks and then assign sensors to the corresponding sinks. For those assigned sensors, hops and energy consumption are considered to solve the hopspot problem. Sensor data are uploaded to the Cloud synchronously through sinks. The problem is proved to be NP-hard, and we design an approximation algorithm to solve this problem with several provable properties. We also designed a detailed routing algorithm for sensors considering hops and energy consumption. We compare our method to several traditional solutions. Extensive experimental results suggest that the proposed method significantly outperforms traditional solutions. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:864 / 872
页数:9
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