'Internet of tilings' (IoT) operates for all-time availability of network components to provide a wide range of service applications to the network users or clients. IoT operates for a large number of applications, and one of these include the sensor deployment for data support to clients. However, these sensors require a large number of queries to be handled by the network components considering the constraints of memory, energy, and delays. These issues can be easily tackled by deploying unmanned aerial vehicles (UAVs), which serve as dynamic nodes to handle clients' queries by acting as on-demand gateways. However, this UAV-assisted IoT requires efficient localisation to determine the sensor for handling multiple-content queries, which is considered as a problem. A cost function is formed in the proposed approach to generate an optimisation problem which is resolved using a radial basis function kernel support vector machine. The effectiveness of the proposed approach is demonstrated in terms of significant gains attained in terms of error in the cost function, overheads in handling queries, and accuracy in UAV allocation.
ASJC Scopus subject areas
- Electrical and Electronic Engineering