G2LC: Resources Autoscaling for Real Time Bioinformatics Applications in IaaS
Rongdong Hu, Guangming Liu, Jingfei Jiang, Lixin Wang

TL;DR
This paper introduces G2LC, a method for automatically scaling cloud resources in bioinformatics to ensure performance while saving up to 20% of computing resources.
Contribution
G2LC is a novel automated resource provisioning method for real-time bioinformatics applications in cloud environments.
Findings
G2LC guarantees application performance for real-time bioinformatics tasks.
Resource utilization is improved by up to 20.14% using G2LC.
The method is evaluated using real BLAST sequence searching data.
Abstract
Cloud computing has started to change the way how bioinformatics research is being carried out. Researchers who have taken advantage of this technology can process larger amounts of data and speed up scientific discovery. The variability in data volume results in variable computing requirements. Therefore, bioinformatics researchers are pursuing more reliable and efficient methods for conducting sequencing analyses. This paper proposes an automated resource provisioning method, G2LC, for bioinformatics applications in IaaS. It enables application to output the results in a real time manner. Its main purpose is to guarantee applications performance, while improving resource utilization. Real sequence searching data of BLAST is used to evaluate the effectiveness of G2LC. Experimental results show that G2LC guarantees the application performance, while resource is saved up to 20.14%.
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsEarly Modern Spanish Literature · Medieval European Literature and History
