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Cloud computing (CC) enables enumerable services to manipulate sensor data generated from X-internet of things (IoT) applications. It is accomplished by selecting an accurate decision-making system, sensors, and VMs. This paper reviews energy-efficient sensor, resource-based VM selection approaches for X-IoT applications. It is prompted to distinguish measurement functions, architectures, VM scheduling mechanism challenges. The first field was surveyed to identify the technical measurement variables of agriculture and the second field to distinguish the difficulties of sensor selection, communication impact on the rate of sensor data generation. The last field represents VM consolidation approaches based on a type of task, resource, and energy utilization rate impact on balancing the resources of VMs during sudden changes in the network field. The precise implementation details of selected articles are bounded with sensor energy consumption, edge computing modules, and communication strategies. The outcomes of investigation consolidate a sensor-cloud framework that implies prevailing solution to CC for X-IoT.
Mekala et al. (2018) studied this question.