In the field of reliable multicast, the design of most current router cache management protocols is limited by network environment with single multicast group. With such protocols, expected targets can not be achieved in Internet environment in which a router is shared by a plurality of multicast groups. ACP is a router cache management protocol suitable for the environment shared by multiple groups. In Internet in which there exists frequently emerged bursty data flow, however, ACP allocation algorithm has such drawbacks as slow convergence and instable allocation results when the number of multicast groups or group members changes. Based on the design and implementation of a dynamic cache allocation algorithm as well as time-out algorithm and packet discard policy, a novel Adaptive and Active Reliable Multicast Protocol (AARM for short) suitable for large-scale multicast network was proposed. Simulation results show that AARM will achieve significant enhancement of performance for multicast network in terms of delayed restoration, bandwidth consumption and network throughput, etc. compared with ACP.
Using the physical layer channel information of wireless devices to establish the highly consistent secret keys is a promising technology for improving the security of wireless networks. Nevertheless, in the time division duplex system, the reciprocity of the wireless channel that is the basic principle of key generation is impaired by nonsimultaneous sampling and noise factors. Existing physical layer key generation approaches rely on hand-crafted feature extraction algorithms, which have high overhead or security issues and are impractical in real-world situations. This paper presents a novel physical layer key generation method to extract highly consistent keys from imperfect channel responses, which exploits channel reciprocity through deep learning. Specifically, we first design the Channel Reciprocity Learning Net (CRLNet), a neural network for efficiently learning channel reciprocity features from the wireless channel in TDD OFDM systems. Later, a new key generation scheme based on CRLNet is developed that can achieve a high key agreement rate. Experiments indicate that the CRLNet-based key generation scheme performs excellently in terms of key generation rate, key error rate, and randomness, confirming that our method has better performance and lower overhead than existing methods.
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