A Network Selection Algorithm for supporting Drone Services in 5G Network Architectures

Flying Ad-hoc Networks (FANETs) use 5G network access technologies to fulfill the requirements of their services. In this environment, Drone to Infrastructure (D21) communication is supported, while each drone could use both Disaster Management (DM) and non-Disaster Management (nDM) services. Efficient network selection algorithms are required to satisfy the constraints of the used services, since the presence of DM services affects the importance of nDM services in situations where a natural disaster occurs. This paper proposes a network selection algorithm which is called Dynamic Trapezoidal Fuzzy Topsis with Adaptive Criteria Weights (DTFT-ACW). DTFT-ACW accomplishes the ranking of the candidate networks considering the importance of each service, as well as the weights of the corresponding selection criteria, as they are obtained with respect to the severity level of a natural disaster occurred. Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) are used for the criteria evaluation. Experimental results show that the suggested method outperforms existing algorithms by satisfying the constraints of DM services when a disaster becomes severe. Furthermore, DTFT-ACW eliminates the computational complexity of the network selection by considering past decisions.