E. Vicente, V.E. Mujica, D. Sisalem, R. Popescu-Zeletin
{"title":"一种用于自组织网络的路由算法","authors":"E. Vicente, V.E. Mujica, D. Sisalem, R. Popescu-Zeletin","doi":"10.1109/WIOPT.2005.32","DOIUrl":null,"url":null,"abstract":"This paper evaluates a self-organizing routing protocol for ad hoc network, called the neuron routing algorithm (NEURAL). NEURAL has been designed taking into account the learning and self-organizing abilities of the brain. More precisely, it was inspired by the synapses process between neurons, when a signal is propagated. Basically, the most significant characteristic of NEURAL is the uniform distribution of the information around the node's location based on the current changes in its neighborhood. Using a 2-hop acknowledgment mechanism, local information is monitored in order to be used for route selection method, classification procedures and learning algorithms.","PeriodicalId":109366,"journal":{"name":"Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'05)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"NEURAL: a self-organizing routing algorithm for ad hoc networks\",\"authors\":\"E. Vicente, V.E. Mujica, D. Sisalem, R. Popescu-Zeletin\",\"doi\":\"10.1109/WIOPT.2005.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper evaluates a self-organizing routing protocol for ad hoc network, called the neuron routing algorithm (NEURAL). NEURAL has been designed taking into account the learning and self-organizing abilities of the brain. More precisely, it was inspired by the synapses process between neurons, when a signal is propagated. Basically, the most significant characteristic of NEURAL is the uniform distribution of the information around the node's location based on the current changes in its neighborhood. Using a 2-hop acknowledgment mechanism, local information is monitored in order to be used for route selection method, classification procedures and learning algorithms.\",\"PeriodicalId\":109366,\"journal\":{\"name\":\"Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'05)\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-04-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WIOPT.2005.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WIOPT.2005.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NEURAL: a self-organizing routing algorithm for ad hoc networks
This paper evaluates a self-organizing routing protocol for ad hoc network, called the neuron routing algorithm (NEURAL). NEURAL has been designed taking into account the learning and self-organizing abilities of the brain. More precisely, it was inspired by the synapses process between neurons, when a signal is propagated. Basically, the most significant characteristic of NEURAL is the uniform distribution of the information around the node's location based on the current changes in its neighborhood. Using a 2-hop acknowledgment mechanism, local information is monitored in order to be used for route selection method, classification procedures and learning algorithms.