Big Data Scientific Workflows in the Cloud: Challenges and Future Prospects

  • Samiya Khan
  • Syed Arshad Ali
  • Nabeela Hasan
  • Kashish Ara Shakil
  • Mansaf Alam
Part of the Studies in Big Data book series (SBD, volume 49)


The concept of workflows was implemented to mitigate the complexities involved in tasks related to scientific computing and business analytics. With time, they have found applications in many diverse fields and domains. Handling big data has given rise to many other issues like growing computing complexity, increasing data size, provisioning of resources and the need for such systems to enable working together of heterogeneous systems. As a result, traditional systems are deemed obsolete for this purpose. To meet the variable resource requirements, cloud has emerged as an ostensible solution. Execution and deployment of big data scientific workflows in the cloud is an area that requires research attention before a synergistic model for the same can be presented. This paper identifies open research problems associated with this domain, giving insights on specific issues like workflow scheduling and execution and deployment of big data scientific workflows in a multi-site cloud environment.


Scientific workflows SWfMS Big data Cloud computing Workflow scheduling Multisite cloud 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Samiya Khan
    • 1
  • Syed Arshad Ali
    • 1
  • Nabeela Hasan
    • 1
  • Kashish Ara Shakil
    • 2
  • Mansaf Alam
    • 1
  1. 1.Department of Computer ScienceJamia Millia IslamiaNew DelhiIndia
  2. 2.Department of Computer Science and EngineeringJamia HamdardNew DelhiIndia

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