Optimal reliable relay selection in multiuser cooperative relaying networks

Halabian, Hassan; Changiz, Reyhaneh; Yu, F. Richard; Lambadaris, Ioannis; Tang, Helen

doi:10.1007/s11276-012-0421-8

Cited by 6 publications

(5 citation statements)

References 25 publications

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“…Also, ARSL-V can prevent malicious vehicles from getting specific weights distribution through trial-and-error. Different from the schemes [14,15,31,32], ARSL-V can also effectively mitigate on-off attacks and collusion attacks caused by potentially malicious vehicles bypassing the assessment mechanism by acquiring the reputation variability and historical behaviors of different vehicles. And, we also set a sliding time window to prevent malicious vehicles from manipulating reputation at low cost through intelligent and dishonest behaviors.…”

Section: Theoretical Analysismentioning

confidence: 99%

“…Furthermore, to improve the overall cooperative transmission success rate and throughput of the system, ARSL-V designs a relay selection method based on the improved K-M algorithm. Compared with other schemes [13,32], ARSL-V can model and optimize the matching based on the constructed weighted bipartite graph, and increase the total number of feasible edges by adding the top label of nodes. This ensures that our scheme can select the appropriate relays when the relay vehicles (R) are greater than, equal to, or less than the target vehicles (T ).…”

Section: Theoretical Analysismentioning

confidence: 99%

“…Secondly, we compare the packet loss rate of each scheme in the cooperative transmission to verify the effectiveness of the dynamic adjustment of the strategy. Finally, the performance of cooperative transmission is measured by comparing it with OPRS [32] and other schemes in terms of transmission success rate and throughput.…”

Section: Experimental Simulation and Analysismentioning

confidence: 99%

“…To better demonstrate that our scheme can adapt to different road environments, we compare ARSL-V with the optimal relay matching scheme proposed by Halabian et al [32]. As shown in Fig.…”

Section: Transmission Performance Of Relay Vehicles In Different Envi...mentioning

confidence: 99%

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ARSL-V: A Risk-aware Relay Selection Scheme using Reinforcement Learning in VANETs

Liu

Wang

Chen

et al. 2022

Preprint

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In high-speed and dynamic Vehicular Ad-hoc Networks (VANETs), cooperative transmission mechanism is a promising scheme to ensure the sustainable transmission of data. However, due to the possible malicious behavior of vehicles and the dynamic network topology of VANETs, not all vehicles are trustworthy to become relays and perform the cooperative transmission task reliably. Therefore, how to ensure the security and reliability of the selected vehicles is still an urgent problem to be solved in the relay selection research area. In this paper, we propose a risk-aware relay selection scheme (ARSL-V) using reinforcement learning in VANETs. Specifically, we design a risk assessment mechanism based on multiple parameters to dynamically assess the potential risk of relay vehicles by considering the reputation variability, abnormal behavior, and environmental impact of vehicles. Also, we model the relay selection problem as an improved Kuhn-Munkres algorithm based on the risk assessment to realize relay selection in multi-relay and multi-target vehicle scenarios. Besides, we use a reinforcement learning algorithm combined with feedback data to achieve dynamic adjustment of parameter weights. Simulation results show that compared with the existing schemes, ARSL-V can improve the detection rate of malicious behavior and cooperative transmission success rate by about 25% and 6%, respectively.

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Section: Theoretical Analysismentioning

confidence: 99%

Section: Theoretical Analysismentioning

confidence: 99%

Section: Experimental Simulation and Analysismentioning

confidence: 99%

“…To better demonstrate that our scheme can adapt to different road environments, we compare ARSL-V with the optimal relay matching scheme proposed by Halabian et al [32]. As shown in Fig.…”

Section: Transmission Performance Of Relay Vehicles In Different Envi...mentioning

confidence: 99%

See 2 more Smart Citations

ARSL-V: A Risk-aware Relay Selection Scheme using Reinforcement Learning in VANETs

Liu

Wang

Chen

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The stability problems in wireless queueing systems have been studied in m any papers [1,[3][4][5][6][7][8][9][10][11][12][13]16,17,[19][20][21][23][24][25][26][27][29][30][31][32][33][35][36][37][38][39][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. However, in m ost of th e research conducted in this area, the goal was to determ ine the optimal resource al...…”

Section: Research M Otivation and T Hesis C Ontributionsmentioning

confidence: 99%