Abstract:
Satellite-assisted IoT networks have emerged as a promising solution to provide global
coverage and seamless connectivity. However, resource allocation and task offloading
in such networks pose significant challenges due to the unique characteristics of
satellite communication systems. The findings of this research contribute to the development
of energy-efficient and reliable satellite-assisted IoT networks. The work
investigates the impact of different Quality of Service (QoS) requirements on resource
allocation and task offloading strategies. It explores the trade-offs between energy efficiency,
network throughput, and fairness in the distribution of resources among IoT
devices. The proposed techniques OAA can enable seamless connectivity and efficient
utilization of resources.The problem under consideration is a concave fractional programming
problem that is transformed into a concave optimization problem using the
Charnes-Cooper transformation. To solve this concave optimization problem, an innovative
outer approximation algorithm is employed.The performance of the epsilonoptimal
solution is evaluated by executing the algorithm with different system parameters,
such as the number of IoT devices, their association, fairness among devices, and
resource block fairness.
