Reinforcement Learning-Based Handover Scheme with Neighbor Beacon Frame Transmission

Mobility support to change the connection from one access point(AP)to the next(i.e.,handover)becomes one of the important issues in IEEE 802.11 wireless local area networks(WLANs).During handover,the channel scanning procedure,which aims to collect neighbor AP(NAP)information on all available channels,accounts for most of the delay time.To reduce the channel scanning procedure,a neighbor beacon frame transmission scheme(N-BTS)was proposed for a seamless handover.N-BTS can provide a seamless handover by removing the channel scanning procedure.However,N-BTS always requires operating overhead even if there are few mobile stations(MSs)for the handover.Therefore,this paper proposes a reinforcement learning-based handover scheme with neighbor beacon frame transmission(MAN-BTS)to properly consider the use of N-BTS.The optimization equation is defined to maximize the expected reward tofind the optimal policy and is solved using Q-learning.Simulation results show that the proposed scheme outperforms the comparison schemes in terms of the expected reward.

Position-assisted fast handover schemes for LTE-advanced network under high mobility scenarios

Two position-assisted fast handover schemes, scheme A and scheme B, for LTE-A system under very high mobility scenarios, are proposed, together with their performance evaluation. Scheme A is designed to reduce handover delay by making handover preparation before handover starts. Scheme B aims at reducing unnecessary handovers and improving handover success rate, by calculating the geographically best target handover cell, which makes it easier for mobile terminals to access the target cell. A system level simulation is conducted to evaluate the performance of these two schemes. It is shown that, scheme A could reduce inter-site handover delay by about 50 ms, while scheme B could cut down nearly 50% of all handovers when time-to-trigger （TTT） is 0 ms. Besides, as TTT gets larger, Scheme B has much better success rate.

A Secure and Efficient Cluster-Based Authentication Scheme for Internet of Things(IoTs)

IPv6 over Low PowerWireless Personal Area Network(6LoWPAN)provides IP connectivity to the highly constrained nodes in the Internet of Things(IoTs).6LoWPANallows nodeswith limited battery power and storage capacity to carry IPv6 datagrams over the lossy and error-prone radio links offered by the IEEE 802.15.4 standard,thus acting as an adoption layer between the IPv6 protocol and IEEE 802.15.4 network.The data link layer of IEEE 802.15.4 in 6LoWPAN is based on AES(Advanced Encryption Standard),but the 6LoWPANstandard lacks and has omitted the security and privacy requirements at higher layers.The sensor nodes in 6LoWPANcan join the network without requiring the authentication procedure.Therefore,from security perspectives,6LoWPAN is vulnerable to many attacks such as replay attack,Man-in-the-Middle attack,Impersonation attack,and Modification attack.This paper proposes a secure and efficient cluster-based authentication scheme(CBAS)for highly constrained sensor nodes in 6LoWPAN.In this approach,sensor nodes are organized into a cluster and communicate with the central network through a dedicated sensor node.The main objective of CBAS is to provide efficient and authentic communication among the 6LoWPAN nodes.To ensure the low signaling overhead during the registration,authentication,and handover procedures,we also introduce lightweight and efficient registration,de-registration,initial authentication,and handover procedures,when a sensor node or group of sensor nodes join or leave a cluster.Our security analysis shows that the proposed CBAS approach protects against various security attacks,including Identity Confidentiality attack,Modification attack,Replay attack,Man-in-the-middle attack,and Impersonation attack.Our simulation experiments show that CBAS has reduced the registration delay by 11%,handoff authentication delay by 32%,and signaling cost by 37%compared to the SGMS(Secure GroupMobility Scheme)and LAMS(Light-Wight Authentication&Mobility Scheme).