Abstract
Due to the rapid growth of the Industrial IoT (IIoT), social media, digitization, and wireless communication technology in various sectors, the volume of data is increasing very rapidly. For handling and processing of the huge volume of data, cloud computing is an emerging solution with the assistance of fog computing. It is a soars of means to improve the quality of services provided to users through cloud computing, which has being more overwhelmed by the massive flow of data. Transmitting all the data to the cloud and getting back from cloud causes high latency and requires high network bandwidth. In the IIoT applications, there is a sufficient amount of energy required in the fog layer which is promising area to be handled by the cloud service providers. An important factor which contributes to the energy consumption in fog servers is the task scheduling. In this paper, we proposed an energy saving task scheduling algorithm based on a meta-heuristic named Harris Hawks optimization technique to improve the QoS in parallel with service level agreement (SLA). The suggested algorithm outperforms in comparison to the other existing algorithms such as PSO, TLBO in terms of energy consumption and other QoS parameters.
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AL-Amodi, S., Patra, S.S., Bhattacharya, S., Mohanty, J.R., Kumar, V., Barik, R.K. (2022). Meta-heuristic Algorithm for Energy-Efficient Task Scheduling in Fog Computing. In: Dhawan, A., Tripathi, V.S., Arya, K.V., Naik, K. (eds) Recent Trends in Electronics and Communication. VCAS 2020. Lecture Notes in Electrical Engineering, vol 777. Springer, Singapore. https://doi.org/10.1007/978-981-16-2761-3_80
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DOI: https://doi.org/10.1007/978-981-16-2761-3_80
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