{"title":"GreedyFlow:分布式贪婪分组路由在ddn的地标之间","authors":"Kang-Peng Chen, Haiying Shen","doi":"10.1109/MASS.2015.67","DOIUrl":null,"url":null,"abstract":"Delay Tolerant Networks (DTNs) have attracted significant interests due to the adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily (i.e., Require base stations or the global traffic distribution). Therefore, in this paper, we propose a distributed greedy routing algorithm, namely Greedy Flow, for efficient packet routing between landmarks. Greedy Flow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node's knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. It is constructed by collecting encountered nodes' transit frequencies between these landmarks. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. Extensive real trace driven experiments demonstrate the high efficiency of Greedy Flow.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"GreedyFlow: Distributed Greedy Packet Routing between Landmarks in DTNs\",\"authors\":\"Kang-Peng Chen, Haiying Shen\",\"doi\":\"10.1109/MASS.2015.67\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Delay Tolerant Networks (DTNs) have attracted significant interests due to the adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily (i.e., Require base stations or the global traffic distribution). Therefore, in this paper, we propose a distributed greedy routing algorithm, namely Greedy Flow, for efficient packet routing between landmarks. Greedy Flow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node's knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. It is constructed by collecting encountered nodes' transit frequencies between these landmarks. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. Extensive real trace driven experiments demonstrate the high efficiency of Greedy Flow.\",\"PeriodicalId\":436496,\"journal\":{\"name\":\"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MASS.2015.67\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASS.2015.67","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GreedyFlow: Distributed Greedy Packet Routing between Landmarks in DTNs
Delay Tolerant Networks (DTNs) have attracted significant interests due to the adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily (i.e., Require base stations or the global traffic distribution). Therefore, in this paper, we propose a distributed greedy routing algorithm, namely Greedy Flow, for efficient packet routing between landmarks. Greedy Flow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node's knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. It is constructed by collecting encountered nodes' transit frequencies between these landmarks. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. Extensive real trace driven experiments demonstrate the high efficiency of Greedy Flow.