S. Bhattacharjee, Boudhayan Bhattacharya, Saunak Sengupta, Owijesh Outta Majumder
{"title":"基于排队模型的MLFFA配送时间延迟分析","authors":"S. Bhattacharjee, Boudhayan Bhattacharya, Saunak Sengupta, Owijesh Outta Majumder","doi":"10.1109/ReTIS.2011.6146889","DOIUrl":null,"url":null,"abstract":"In this paper, we described the Queuing delay in our own MLFFA architecture based on data fusion and analyzed different data fusion filter architectures available in the literature with our new Multi-level Federated Architecture (MLFFA) to improve the filtration of each signaling sensor for a reference sensor (RS) within its fusion domain. It is done by sending the individual sensor data through multiple levels of local filters (LF). This process reduces both Rate of Data Loss and eases the load on Master Fusion Filter (MFF). This article presents a comparison of other existing data fusion architectures - Centralised, Cascaded, Federated, and Distributed with our MLFFA which shows improvement with respect to the existing architectures in term of queuing delay.","PeriodicalId":137916,"journal":{"name":"2011 International Conference on Recent Trends in Information Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Delivery time delay analysis of MLFFA based on queuing model\",\"authors\":\"S. Bhattacharjee, Boudhayan Bhattacharya, Saunak Sengupta, Owijesh Outta Majumder\",\"doi\":\"10.1109/ReTIS.2011.6146889\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we described the Queuing delay in our own MLFFA architecture based on data fusion and analyzed different data fusion filter architectures available in the literature with our new Multi-level Federated Architecture (MLFFA) to improve the filtration of each signaling sensor for a reference sensor (RS) within its fusion domain. It is done by sending the individual sensor data through multiple levels of local filters (LF). This process reduces both Rate of Data Loss and eases the load on Master Fusion Filter (MFF). This article presents a comparison of other existing data fusion architectures - Centralised, Cascaded, Federated, and Distributed with our MLFFA which shows improvement with respect to the existing architectures in term of queuing delay.\",\"PeriodicalId\":137916,\"journal\":{\"name\":\"2011 International Conference on Recent Trends in Information Systems\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Recent Trends in Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ReTIS.2011.6146889\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Recent Trends in Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ReTIS.2011.6146889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Delivery time delay analysis of MLFFA based on queuing model
In this paper, we described the Queuing delay in our own MLFFA architecture based on data fusion and analyzed different data fusion filter architectures available in the literature with our new Multi-level Federated Architecture (MLFFA) to improve the filtration of each signaling sensor for a reference sensor (RS) within its fusion domain. It is done by sending the individual sensor data through multiple levels of local filters (LF). This process reduces both Rate of Data Loss and eases the load on Master Fusion Filter (MFF). This article presents a comparison of other existing data fusion architectures - Centralised, Cascaded, Federated, and Distributed with our MLFFA which shows improvement with respect to the existing architectures in term of queuing delay.