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Offloading coalition formation for scheduling scientific workflow ensembles in fog environments

Siar, H ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1007/s10723-021-09574-y
  3. Publisher: Springer Science and Business Media B.V , 2021
  4. Abstract:
  5. Fog computing provides a distributed computing paradigm that executes interactive and distributed applications, such as the Internet of Things (IoT) applications. Large-scale scientific applications, often in the form of workflow ensembles, have a distributed and interactive nature that demands a dispersed execution environment like fog computing. However, handling a large-scale application in heterogeneous environment of fog computing requires harmonizing heterologous resources over the continuum from the IoT to the cloud. This paper investigates offloading and task allocation problems for orchestrating the resources in a fog computing environment where the IoT application is considered in the form of workflow ensembles. We called Offload-Location a mechanism which has been designed to find offloading coalition structure alongside a matching algorithm for allocating the offloaded tasks to fog/cloud resources. The introduced solution attempts to minimize the execution time and minimize the price paid to servers for executing the tasks provided that Quality of Service (QoS) requirements of the ensemble’s deadline and budget are retaining. These objectives lead to maximizing the number of completed workflows of the ensemble as an ultimate goal. The appropriate performance of this mechanism is studied under different workflow applications and circumstances. © 2021, The Author(s), under exclusive licence to Springer Nature B.V
  6. Keywords:
  7. Budget control ; Fog ; Internet of things ; Quality of service ; Computing environments ; Distributed applications ; Execution environments ; Heterogeneous environments ; Internet of thing (IOT) ; Large-scale applications ; Qualityof-service requirement (QoS) ; Scientific applications ; Fog computing
  8. Source: Journal of Grid Computing ; Volume 19, Issue 3 , 2021 ; 15707873 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s10723-021-09574-y?utm_source=xmol&utm_medium=affiliate&utm_content=meta&utm_campaign=DDCN_1_GL01_metadata