Fog Computing for Bioinformatics Applications
Hafeez Ur Rehman, Asad Ullah Khan, Usman Habib · 2020
In bioinformatics, many high-throughput technologies, such as next-generation sequencing, result in an avalanche of sequences coming from diverse sources that remain uncharacterized. Processing this huge amount of sequencing data with conventional methods is a tedious and daunting task. In addition, processing of large, complex, heterogeneous data requires extensive resources. Analysis of such data might take hours or days to produce results. To speed up the processing of data, bioinformatics research, in general, relies on high computational and storage platforms. Traditionally, cloud computing comes to the rescue and provides service-oriented architectures in the form of hardware platforms, application platforms, and operating environment platforms. The difficulties encountered by bioinformatics researchers in order to carry out their research in a cost-effective and fast manner can be resolved, to some extent, with the help of cloud computing services. However, the scientists need to port their data and algorithms to the cloud environment in order to perform analysis. Recently, the emerging trend of on-the-fly solutions for bioinformatics problems, as well as rising privacy concerns, require reducing the remoteness between computing platforms and the users' data by bringing the computational resources closer to the users. Fog computing, as an extension of cloud computing, brings the services to the edge of the network. This essentially brings the advantages and power of the cloud closer to the place where the data is created, thus helping and speeding up on-the-fly solutions for bioinformatics applications. In this chapter, we first provide an overview of broader cloud computing techniques along with the current state of the art, applied to solving bioinformatics problems. In addition, we discuss how fog computing as an extension of cloud computing can be used in the field of bioinformatics to solve complex problems on the fly. Furthermore, this chapter also elaborates on the potential use of fog computing to overcome the limitations of cloud computing and to solve impending problems of the field, such as microorganism detection in real-time environments.