Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network
Aiming at the instability of communication link caused by the high-speed movement of vehicle nodes in vehicular delay tolerant network （VDTN）， considering the characteristics of regularity and periodicity of vehicle nodes movement， a VDTN routing algorithm based on optimized multi-period Bayesian ne...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-12-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021222/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539180937609216 |
|---|---|
| author | Jiagao WU Yahang GUO Shenlei CAI Linfeng LIU |
| author_facet | Jiagao WU Yahang GUO Shenlei CAI Linfeng LIU |
| author_sort | Jiagao WU |
| collection | DOAJ |
| description | Aiming at the instability of communication link caused by the high-speed movement of vehicle nodes in vehicular delay tolerant network （VDTN）， considering the characteristics of regularity and periodicity of vehicle nodes movement， a VDTN routing algorithm based on optimized multi-period Bayesian network （BN） was proposed.Firstly， a new multi-period BN model and its dynamic reward mechanism for node classification were proposed to describe the movement pattern of vehicle nodes with higher accuracy.Then， two novel time-optimal-partition algorithms of multi-period BN were proposed including binary search K2GA （BS-K2GA） algorithm and simulated annealing K2GA （SA-K2GA） algorithm， where BS-K2GA algorithm had the advantages of simplicity and efficiency， while SA-K2GA could effectively avoid falling into the local optimal solution and further optimize the performance.The simulation results show that the proposed VDTN routing algorithm based on optimized multi-period BN model can significantly improve the message delivery ratio and reduce the delivery delay.Thus， the effectiveness of the approach is validated. |
| format | Article |
| id | doaj-art-2eaffbe2a9bb4e33a16f51f7e360bed7 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-12-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-2eaffbe2a9bb4e33a16f51f7e360bed72025-01-14T07:23:19ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-12-014210912059746737Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian networkJiagao WUYahang GUOShenlei CAILinfeng LIUAiming at the instability of communication link caused by the high-speed movement of vehicle nodes in vehicular delay tolerant network （VDTN）， considering the characteristics of regularity and periodicity of vehicle nodes movement， a VDTN routing algorithm based on optimized multi-period Bayesian network （BN） was proposed.Firstly， a new multi-period BN model and its dynamic reward mechanism for node classification were proposed to describe the movement pattern of vehicle nodes with higher accuracy.Then， two novel time-optimal-partition algorithms of multi-period BN were proposed including binary search K2GA （BS-K2GA） algorithm and simulated annealing K2GA （SA-K2GA） algorithm， where BS-K2GA algorithm had the advantages of simplicity and efficiency， while SA-K2GA could effectively avoid falling into the local optimal solution and further optimize the performance.The simulation results show that the proposed VDTN routing algorithm based on optimized multi-period BN model can significantly improve the message delivery ratio and reduce the delivery delay.Thus， the effectiveness of the approach is validated.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021222/vehicle delay tolerant networkBayesian networkrouting algorithmbinary searchsimulated annealing |
| spellingShingle | Jiagao WU Yahang GUO Shenlei CAI Linfeng LIU Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network Tongxin xuebao vehicle delay tolerant network Bayesian network routing algorithm binary search simulated annealing |
| title | Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network |
| title_full | Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network |
| title_fullStr | Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network |
| title_full_unstemmed | Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network |
| title_short | Vehicular delay tolerant network routing algorithm based on optimized multi-period Bayesian network |
| title_sort | vehicular delay tolerant network routing algorithm based on optimized multi period bayesian network |
| topic | vehicle delay tolerant network Bayesian network routing algorithm binary search simulated annealing |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021222/ |
| work_keys_str_mv | AT jiagaowu vehiculardelaytolerantnetworkroutingalgorithmbasedonoptimizedmultiperiodbayesiannetwork AT yahangguo vehiculardelaytolerantnetworkroutingalgorithmbasedonoptimizedmultiperiodbayesiannetwork AT shenleicai vehiculardelaytolerantnetworkroutingalgorithmbasedonoptimizedmultiperiodbayesiannetwork AT linfengliu vehiculardelaytolerantnetworkroutingalgorithmbasedonoptimizedmultiperiodbayesiannetwork |