{"title":"度偏点对点网络中八卦算法的消息可达性","authors":"Daisuke Yamamasu, Naohiro Hayashibara","doi":"10.1109/PADSW.2014.7097888","DOIUrl":null,"url":null,"abstract":"In peer-to-peer networks, each node directly connects to other nodes without access points. This type of network system is useful for information sharing by using mobile devices (e.g., smart phones). On message delivery over the network, it is very difficult to assume the static routing if each node is assumed to move. In this paper, we suppose to use gossip-style epidemic message dissemination and show the performance evaluation of several gossip algorithms in terms of network topology. Specifically, we focus on the distribution of links in the network. Our results clarified the characteristics of those algorithms on the topologies that are biased the degree distribution locally.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"On message reachability of gossip algorithms in degree-biased peer-to-peer networks\",\"authors\":\"Daisuke Yamamasu, Naohiro Hayashibara\",\"doi\":\"10.1109/PADSW.2014.7097888\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In peer-to-peer networks, each node directly connects to other nodes without access points. This type of network system is useful for information sharing by using mobile devices (e.g., smart phones). On message delivery over the network, it is very difficult to assume the static routing if each node is assumed to move. In this paper, we suppose to use gossip-style epidemic message dissemination and show the performance evaluation of several gossip algorithms in terms of network topology. Specifically, we focus on the distribution of links in the network. Our results clarified the characteristics of those algorithms on the topologies that are biased the degree distribution locally.\",\"PeriodicalId\":421740,\"journal\":{\"name\":\"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PADSW.2014.7097888\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PADSW.2014.7097888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On message reachability of gossip algorithms in degree-biased peer-to-peer networks
In peer-to-peer networks, each node directly connects to other nodes without access points. This type of network system is useful for information sharing by using mobile devices (e.g., smart phones). On message delivery over the network, it is very difficult to assume the static routing if each node is assumed to move. In this paper, we suppose to use gossip-style epidemic message dissemination and show the performance evaluation of several gossip algorithms in terms of network topology. Specifically, we focus on the distribution of links in the network. Our results clarified the characteristics of those algorithms on the topologies that are biased the degree distribution locally.