{"title":"浮游生物:一个有效的DTN路由算法","authors":"Xiangfa Guo, M. Chan","doi":"10.1109/SAHCN.2013.6645027","DOIUrl":null,"url":null,"abstract":"In this paper, we present an efficient routing algorithm, Plankton, for Delay/Disruptive Tolerant Network (DTN). Plankton utilizes replica control to reduce overhead and contact probability estimates to improve performance. Plankton has two major features. First, it uses a combination of both short-term bursty contacts and long-term association based statistics for contact prediction. Second, it dynamically adjusts replication quotas based on estimated contact probabilities and delivery probabilities. Our evaluation on extensive traces shows that Plankton achieves significantly better prediction accuracy than existing algorithms for contact probability prediction. In addition, we show that while Plankton incurs much lower communication overhead compared to Spray-and-Wait, MaxProp and RAPID with savings from 14% to 88%, it can also achieve similar if not better delivery ratios and latencies.","PeriodicalId":206294,"journal":{"name":"2013 IEEE International Conference on Sensing, Communications and Networking (SECON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Plankton: An efficient DTN routing algorithm\",\"authors\":\"Xiangfa Guo, M. Chan\",\"doi\":\"10.1109/SAHCN.2013.6645027\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present an efficient routing algorithm, Plankton, for Delay/Disruptive Tolerant Network (DTN). Plankton utilizes replica control to reduce overhead and contact probability estimates to improve performance. Plankton has two major features. First, it uses a combination of both short-term bursty contacts and long-term association based statistics for contact prediction. Second, it dynamically adjusts replication quotas based on estimated contact probabilities and delivery probabilities. Our evaluation on extensive traces shows that Plankton achieves significantly better prediction accuracy than existing algorithms for contact probability prediction. In addition, we show that while Plankton incurs much lower communication overhead compared to Spray-and-Wait, MaxProp and RAPID with savings from 14% to 88%, it can also achieve similar if not better delivery ratios and latencies.\",\"PeriodicalId\":206294,\"journal\":{\"name\":\"2013 IEEE International Conference on Sensing, Communications and Networking (SECON)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-06-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Sensing, Communications and Networking (SECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAHCN.2013.6645027\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Sensing, Communications and Networking (SECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAHCN.2013.6645027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we present an efficient routing algorithm, Plankton, for Delay/Disruptive Tolerant Network (DTN). Plankton utilizes replica control to reduce overhead and contact probability estimates to improve performance. Plankton has two major features. First, it uses a combination of both short-term bursty contacts and long-term association based statistics for contact prediction. Second, it dynamically adjusts replication quotas based on estimated contact probabilities and delivery probabilities. Our evaluation on extensive traces shows that Plankton achieves significantly better prediction accuracy than existing algorithms for contact probability prediction. In addition, we show that while Plankton incurs much lower communication overhead compared to Spray-and-Wait, MaxProp and RAPID with savings from 14% to 88%, it can also achieve similar if not better delivery ratios and latencies.