Abstract
Fog computing seeks the attention of researchers by bringing a revolution in the Internet of Things (IoT). Fog computing emerged as a complement to cloud computing. It extends cloud services to the network edge and processes large and complex tasks near end users. Furthermore, fog computing can help process workflow tasks on its nodes only rather than sending them to the cloud, which helps to reduce the time consumed to request and process at the cloud layer. Scientific Workflow is used to represent data flow in scientific applications, which are very time-critical. This paper has proposed an energy-efficient load balancing approach for fog computing to reduce energy consumption in scientific workflow applications. The proposed algorithm works to reduce energy consumption in fog nodes by equal distribution of workload in fog resources. Genome and SIPHT workflow applications have been considered to evaluate in iFogSim.
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Kaur, M., Aron, R. (2022). An Energy-Efficient Load Balancing Approach for Fog Environment Using Scientific Workflow Applications. In: Majhi, S., Prado, R.P.d., Dasanapura Nanjundaiah, C. (eds) Distributed Computing and Optimization Techniques. Lecture Notes in Electrical Engineering, vol 903. Springer, Singapore. https://doi.org/10.1007/978-981-19-2281-7_16
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DOI: https://doi.org/10.1007/978-981-19-2281-7_16
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