Spatio-Fog: A green and timeliness-oriented fog computing model for geospatial query resolution

被引：9

作者：

Das, Jaydeep ^{[1
]}

Mukherjee, Anwesha ^{[2
]}

Ghosh, Soumya K. ^{[3
]}

Buyya, Rajkumar ^{[4
]}

机构：

[1] Indian Inst Technol Kharagpur, Adv Technol Dev Ctr, Kharagpur 721302, W Bengal, India

[2] Mahishadal Raj Coll, Dept Comp Sci, Purba Medinipur 721628, W Bengal, India

[3] Indian Inst Technol Kharagpur, Dept Comp Sci & Engn, Kharagpur 721302, W Bengal, India

[4] Univ Melbourne, Sch Comp & Informat Syst, Cloud Comp & Distributed Syst CLOUDS Lab, Melbourne, Vic 3010, Australia

来源：

SIMULATION MODELLING PRACTICE AND THEORY | 2020年 / 100卷

关键词：

Geospatial query; Fog computing; Cloud computing; Delay-sensitive; Power-efficient; REAL-TIME; FEMTOLET; RECOMMENDATION; CHALLENGES; FRAMEWORK; QUADTREE; LOCALITY; SERVICE;

D O I：

10.1016/j.simpat.2019.102043

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Geospatial data analysis is an emerging area of research today. Systems need to respond to user requests in a timely manner. In this paper we have proposed a fog computing framework namely Spatio-Fog, where the fog devices contain the geospatial data of their current region and process geospatial queries using resources in the proximity. The geospatial query resolution is performed by the fog device either itself or using cloud servers or fog device of other region depending on the geographical region related to the geospatial query. We have performed both empirical study and experimental analysis to demonstrate feasibility of our proposed approach. The empirical study illustrates that the proposed architecture Spatio-Fog reduces the power consumption and delay by approximately 43-47% and 47-83% respectively over the use of existing geospatial query resolution system. The experimental analysis demonstrates that the proposed framework reduces the power consumption and delay by 30-60% approximately than the existing geospatial query resolution system.

引用

页数：23