Volume 13 , Issue 1 , PP: 28-35, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Vandana Roy 1 *
Doi: https://doi.org/10.54216/JCIM.130103
In recent years, smart computing has emerged as a promising and rapidly expanding field of technology. It senses the environment in real time and gives powerful analytics to perform intelligent decisions. Creating a scheduling algorithm based on priorities in order to decrease IoT process latency was the primary emphasis of the study challenge. The constraints of existing scheduling algorithms were investigated in order to build a scheduling algorithm that is based on priorities. We provide a context-based priority scheduling method to get around these restrictions. In order to determine which steps of the IoT process were crucial, we developed context attributes. Once the criticality has been identified, the proposed scheduling technique is used to schedule the IoT processes. The outcomes of the algorithms were confirmed using a variety of evaluation indicators. As demonstrated by the experimental results, the suggested scheduling algorithms outperformed the state-of-the-art techniques. Smart ATM uses a Case Study technique to analyse the algorithm. We identified the sensors that are part of the ATM and the settings in which they are relevant. We determined the priority value for each sensor. The processes are subsequently categorized according to their priority values. Then, a priority-based FCFS scheduling algorithm is used, and its performance is assessed using metrics like Average TAT, Cost, Energy, and the High critical process TAT ratio.
IoT , TAT , EFCFS , PFCFS , Cost
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