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To predict weather precisely, meteorologists need to collect and analyze meteorological data from wireless sensor devices installed in different areas. Today, cloud computing provides efficient storage and processing tasks for large-scaled sensor data. However, wireless sensors are constrained with bandwidth to transmit data to the cloud. Therefore, we propose a system model called cloud-based meteorological sensor network with aggregator approach which combines data from sensors and forwards to the cloud with better bandwidth. In this paper, the two main problems are considered for proposed system model. First, optimization approach to capacity planning of aggregators is addressed to obtain optimal number of aggregators for providing enough services to sensor data while reducing high investment. Second, optimal data transmission (ODT) algorithm based on multi-objective optimization approach is also proposed to minimize cost for provisioning resources and delay for transferring and processing when data from aggregators are allocated to multiple cloud providers. Then, the extensive numerical studies are performed for each problem. The numerical
results provide not only optimal number of aggregators with the minimum total cost but also optimal data transmission from aggregators to the
cloud with the minimum total cost and delay for the proposed system model.
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