Serverless Edge Computing for Green Oil and Gas Industry

被引:16
作者
Hussain, Razin Farhan [1 ]
Salehil, Mohsen Amini [1 ]
Semiari, Omid [2 ]
机构
[1] Univ Louisiana Lafayette, Sch Comp & Informat, High Performance Cloud Comp HPCC Lab, Lafayette, LA 70504 USA
[2] Georgia Southern Univ, Dept Elect & Comp Engn, Statesboro, GA 30460 USA
来源
2019 IEEE GREEN TECHNOLOGIES CONFERENCE (GREENTECH) | 2019年
关键词
RESOURCE-ALLOCATION; INDEPENDENT TASKS;
D O I
10.1109/greentech.2019.8767119
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Escalating demand of petroleum led the Oil and Gas (O&G) industry to extend oil extraction operation in the remote reservoirs. Oil extraction is a fault intolerant process where the maximum penalty is disaster impacting the environment seriously. Therefore, efficient and nature-friendly green oil extraction is a challenging operation, especially with location constrained in accessing the sites. To overcome these challenges and protect the environment from pollution, smart oil fields with numerous sensors (e.g., for pipeline pressure, gas leakage, air pollution) are established to achieve clean O&G extraction. Conventionally, cloud datacenters are utilized to process the generated data. High-latency satellite communication are used for data transfer, which is not suitable for time-sensitive operations/tasks. To process such latency-sensitive tasks, edge computing can be a suitable candidate, however, their computational power goes downhill at disaster time due to surge demand of many coordinated activities. Therefore, we propose green smart oil fields that operate based on edge computing. To overcome shortage of resources and rapid deployment of the edge computing systems, we propose to use lightweight serverless computing on a federation of edge computing resources from nearby oil rigs. Our solution coordinates urgent coordinated operations/tasks to prevent disasters in oil fields and enable the idea of green smart oil fields. Evaluation results demonstrate the efficacy of our proposed solution in compare to conventional solutions for smart oil fields.
引用
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页数:4
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