With the diversification of 5G networks, the accurate classification of network traffic is of great significance to network management and optimization. Based on the study of classical volumes and neural networks, this paper proposes a lightweight, low convolutional neural network traffic classification algorithm-LWLC-CNN, to complete network traffic classification. Experimental results show that the proposed algorithm significantly reduces the computer's training capacity and model size, and has a good effect on network traffic classification.

At present, the research on the method of improving the obstacle avoidance ability of UAV mainly focuses on digital simulation and sensor-dependent technology. However, in complex and unpredictable environments, sensors may be affected by strong light, bad weather and other factors, resulting in ineffective obstacle avoidance and so on. Therefore, this paper proposes an obstacle avoidance method based on virtual-real combination technology, and constructs a virtual-real combination obstacle avoidance test platform, in the case of sensor failure, the test platform will control the UAV for obstacle avoidance operation. Therefore, the obstacle avoidance performance of UAV in complex environment can be greatly improved, and the purpose of safe and efficient flight can be realized.

Summary Raft is a consensus algorithm that implements highly available replicas. As raft requires a leader to drive the protocol execution, it usually employs a round‐robin leader election mechanism to select a random leader among all nodes. However, when the elected leader suffers from performance issues, the protocol will temporarily lose aliveness. To address this issue, we propose a multi‐strategy leader election mechanism that allows nodes to proactively trigger a new round of election when they believe the leader suffers from performance issues, and replace this leader with a new one in a designated priority queue. The formal analysis and experimental results show that the mechanism can improve the system's throughput/latency without additional election time overhead.

State machine replication (SMR) allows nodes to jointly maintain a consistent ledger, even when a part of nodes are Byzantine. To defend against and/or limit the impact of attacks launched by Byzantine nodes, there have been blocks that combine reputation mechanisms to SMR, where each node has a reputation value based on its historical behaviours, and the node’s voting power will be proportional to its reputation. Despite the promising features of reputation-based SMR, existing studies do not provide formal treatment on the reputation mechanism on SMR protocols, including the types of behaviours affecting the reputation, the security properties of the reputation mechanism, and the extra security properties of SMR using reputation mechanisms.In this paper, we provide the first formal study on the reputation-based SMR. We define the security properties of the reputation mechanism w.r.t. these misbehaviours. Based on the formalisation of the reputation mechanism, we formally define the reputation-based SMR, and identify a new property reputation-consistency that is necessary for ensuring reputation-based SMR’s safety. We then design a simple reputation mechanism that achieves all security properties in our formal model. To demonstrate the practicality, we combine our reputation mechanism to the Sync-HotStuff SMR protocol, yielding a simple and efficient reputation-based SMR at the cost of only an extra ∆ in latency, where ∆ is the maximum delay in synchronous networks.