Elastic scaling and load balancing with efficient switch migration are critical to enable the elasticity of software-defined networking (SDN) controllers, but learning how to improve migration efficiency remains a difficult problem. To address this issue, a switch migration-based decision-making (SMDM) scheme is put forward that could be made aware of the load imbalance by a switch migration trigger metric; the migration efficiency model for this scheme is built to make a tradeoff between migration costs and the load balance rate. An efficiency-aware switch migration algorithm based on greedy method is designed to utilize the migration efficiency model and thus guide the choice of possible migration actions. We implement a proof of the scheme and present a numerical evaluation using Mininet emulator to demonstrate the effectiveness of our proposal.

Drone base stations (DBSs) can provide wireless coverage on the ground. In this letter, we propose an energy efficient placement algorithm for a DBS that serves a set of ground users, using minimum required transmit power. We obtain the optimal drone position by decoupling the deployment problem in the horizontal and vertical dimensions. Simulations are performed for hotspot and non-hotspot scenarios to evaluate the performance of our proposed algorithm, and the results show significant reductions in transmit power of the DBS. Furthermore, the optimal drone altitude is proportional to the minimum horizontal distance of the edge users from the DBS, and the slope depends on the environment.

The ultra-dense network (UDN) is one of the most promising technologies in the fifth generation (5G) to address the network system capacity issue. However, it is a new challenge that the user equipment (UE) secure access UDN composed of the access points (APs) which characterized with autonomy, temporary, and dynamic. In 5G UDN, the APs are independent and equal. The UDN can be regarded as a decentralized access network. Compared with the traditional base station, the AP has a smaller coverage. There has an issue that the interaction between the UE and APs will be more frequent when UE moves. However, the existing 4G authentication and key agreement algorithm cannot adapt to this fast and frequent authentication requirement. If the UE moves smoothly in a trusted APs group (APG) without frequent authentication, this problem will be solved very well. In order to achieve this goal, we propose a security authentication scheme of 5G UDN based on the block chaining technologies. In this paper, an APG-PBFT algorithm based on the block chaining technology with Byzantine fault tolerance (PBFT) consensus algorithm is proposed. In the algorithm, the consensus mechanism will be optimized and a new reverse screening method will be embedded. In our solution, a trusted chain APG can be generated with APs by APG-PBFT algorithm, and the authentication results can be shared in the APG using the blockchain message propagation mechanism. The principle of fast authentication with APG-PBFT algorithm is present in this paper. The scheme can reduce the authentication frequency when UE moves among the APs and improve the access efficiency. Finally, we analyze the performance of APG-PBFT algorithm and compare it with the traditional PBFT algorithm. The simulation results show that the APG-PBFT algorithm can improve the APG generation efficiency and reduce the authentication frequency of UE, which will be valuably applied to the UDN environment.

Integrating unmanned aerial vehicles (UAVs) into emergency communications is a promising way to accomplish efficient network recovery with the advantages of UAV flexibility. To ensure information forwarding from the disaster area, this article considers an emergency communication scenario where a UAV provides uplink relaying services based on nonorthogonal multiple access (NOMA) for a set of disconnected ground wireless access points (APs) under the urban environment. To maximize the system uplink throughput, the UAV altitude, power control, as well as the bandwidth allocation between the access and backhaul links are jointly optimized. Especially, the constraint for the uplink rate fairness is also considered. Our formulated problem is nonconvex due to the complex uplink co-channel interference under the Line-of-Sight (LoS) probability-based Air-to-Ground (AtG) channel. To tackle this issue, we change our formulated problem into an equivalent form by coping with the information-causality and fairness constraints. Then, a joint altitude and resource allocation (JARA) algorithm is developed, which iteratively solves the altitude optimization subproblem and resource optimization subproblem until convergence. For each subproblem, we further introduce auxiliary variables so that it can be solved by using the successive convex approximation (SCA) method. Finally, two benchmarks are used for the throughput comparison, and simulation results verify that the system uplink throughput of our proposed algorithm is improved through the AtG LoS propagation advantage, uplink power control, as well as the bandwidth allocation between the access and backhaul links.

Unmanned aerial vehicle (UAV) relaying is an efficient solution to provide wireless access for emergency communications due to the high flexibility. The system reliability is usually constrained under limited bandwidth and power resources. Downlink non-orthogonal multiple access (NOMA) can improve the system reliability through a higher resource utilization. To this end, we introduce downlink NOMA to a UAV-enabled mobile relaying system and investigate a scenario where a fixed-wing UAV flies in a circular trajectory to serve as a mobile decode-and-forward (DF) relay in an emergency situation. Since guaranteeing a reliable link is necessary in an emergency situation, our formulated problem is to minimize the maximum outage probability among all links, taking into account the bandwidth and power allocations based on downlink NOMA. Specially, the condition for successful successive interference cancellation (SIC) is also considered. By making change of variables and introducing slack variables, we reformulate our problem into a more tractable form, then we propose an iteration algorithm to solve our problem based on the successive convex optimization (SCO) technique. The optimized bandwidth and power allocation schemes as well as the min-max outage probability along the UAV trajectory are obtained, respectively. Two benchmarks are designed to reveal the performance of our proposed algorithm, and the reliability gain can be obtained by comparing the min-max outage probability and the overall average outage probability.