An Integrated Load Balancing Scheme Based on SDN ASR Algorithm

At present,the flow table of the SDN switch is stored in the costly Ternary Content Addressable Memory(TCAM)cache.Due to the cost problem,the number of flow tables that the SDN switch can store is extremely limited,which is far less than the number of traffic,so it is prone to overflow problem,and leads to network paralysis.That has become a bottleneck in restricting the processing capacity of the data center,and will become a weak point focused by attackers.In this paper,we propose an algorithm for the Alarm Switch Remove(ASR)that fully loads the flow table space in SDN,and further put forward an integrated load balancing scheme in SDN.Finally,we use Mininet to verify that the scheme can ease the SDN switch flow table overflow problem and increase network throughput.

Energy-Efficient UAV Trajectory Design for Backscatter Communication: A Deep Reinforcement Learning Approach

Recently,backscatter communication(BC)has been introduced as a green paradigm for Internet of Things(IoT).Meanwhile,unmanned aerial vehicles(UAVs)can serve as aerial base stations(BSs)to enhance the performance of BC system thanks to their high mobility and flexibility.In this paper,we investigate the problem of energy efficiency(EE)for an energy-limited backscatter communication(BC)network,where backscatter devices(BDs)on the ground harvest energy from the wireless signal of a flying rotary-wing quadrotor.Specifically,we first reformulate the EE optimization problem as a Markov decision process(MDP)and then propose a deep reinforcement learning(DRL)algorithm to design the UAV trajectory with the constraints of the BD scheduling,the power reflection coefficients,the transmission power,and the fairness among BDs.Simulation results show the proposed DRL algorithm achieves close-to-optimal performance and significant EE gains compared to the benchmark schemes.

Routing Loop Audit Mechanism Based on SDN

Routing loops can cause packet loss and long delay problems in the traditional network. Even in future networks – Software-Defined Networks, with loop-free implementation mechanism, it still suffers loop problems. In this paper, we propose an architecture to solve the loop problem in SDN. Unlike the existing passive routing loop detection algorithm, this algorithm processes based on the SDN loop-free characteristic, by auditing third-party network forwarding rules’ modification requests to avoids loop generation, thus avoid the network loop problems. Testbed is built to simulate our proposed algorithm. The evaluation shows that the loop audit algorithm proposed in this paper has better performance in extra spatial utilization and smaller number of extra interactions between SDN controller and switches.

An SDN Oriented Loop Detection Mechanism Based on TTL Statistics

The rise of the network has injected new impetus into the development of traditional networks.Due to the complexity of the network itself and its network programmability,there is a risk of routing loops occurring in the SDN network.This paper proposes a loop detection mechanism.According to the Time To Live(TTL)value of the loop packet,there is approximately periodicity in the same loop.We use sFlow to count the number of packets corresponding to each TTL value of a switch in the loop over a period of time,and perform discrete Fourier transform on the obtained finite-length sequence to observe its frequency domain performance and determine whether there are periodic features.By doing so,it is determined whether there is a routing loop,and the purpose of passively detecting the routing loop is achieved.Compared to existing algorithms,it has advantages in real-time,scalability and false positive rate.The experimental results show that the routing loop detection algorithm based on TTL statistics in this paper still maintains high judgment accuracy under the scenarios of lower stream sampling rate and smaller detection period.