{"title":"共享风险链路组物理长度对光网络可用性影响的蒙特卡罗模拟评价","authors":"V. Miletić, B. Mikac, M. Dzanko","doi":"10.1109/NOC-OCI.2013.6582897","DOIUrl":null,"url":null,"abstract":"In optical networks a group of logically distinct links can unintentionally share a physical resource (e.g, a cable or a duct). Such a group, called shared risk link group (SRLG), introduces a situation where a single failure of common resource can cause multiple failures. Failure of common resource usually occurs due to physical force (e.g, digging or earthquake) and causes failures of multiple links. Specifically, such a failure can cause both working and spare wavelength path of a logical connection between two edge nodes to fail at the same time, leaving them disconnected until a repair is done. The usual approach to solving this problem consists of introducing more spare capacity to the network and also using a routing algorithm that takes SRLGs into account when computing paths. Such a routing algorithm avoids creating working and spare path pairs that have links contained in the same SRLG, to minimize the negative impact of SRLG failure on logical connection availability. In this paper the impact of physical length of the SRLGs on network availability is evaluated using Monte Carlo simulation. New simulation model for availability evaluation is implemented by discrete-event network simulator ns-3. Implementation approach is discussed, and an overview of model features is provided. For simple cases, Monte Carlo simulation results obtained by using the model are compared to analytical results. The availability results for the general case are obtained using Monte Carlo simulation and discussed.","PeriodicalId":57196,"journal":{"name":"光通信研究","volume":"121 1","pages":"249-256"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation\",\"authors\":\"V. Miletić, B. Mikac, M. Dzanko\",\"doi\":\"10.1109/NOC-OCI.2013.6582897\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In optical networks a group of logically distinct links can unintentionally share a physical resource (e.g, a cable or a duct). Such a group, called shared risk link group (SRLG), introduces a situation where a single failure of common resource can cause multiple failures. Failure of common resource usually occurs due to physical force (e.g, digging or earthquake) and causes failures of multiple links. Specifically, such a failure can cause both working and spare wavelength path of a logical connection between two edge nodes to fail at the same time, leaving them disconnected until a repair is done. The usual approach to solving this problem consists of introducing more spare capacity to the network and also using a routing algorithm that takes SRLGs into account when computing paths. Such a routing algorithm avoids creating working and spare path pairs that have links contained in the same SRLG, to minimize the negative impact of SRLG failure on logical connection availability. In this paper the impact of physical length of the SRLGs on network availability is evaluated using Monte Carlo simulation. New simulation model for availability evaluation is implemented by discrete-event network simulator ns-3. Implementation approach is discussed, and an overview of model features is provided. For simple cases, Monte Carlo simulation results obtained by using the model are compared to analytical results. The availability results for the general case are obtained using Monte Carlo simulation and discussed.\",\"PeriodicalId\":57196,\"journal\":{\"name\":\"光通信研究\",\"volume\":\"121 1\",\"pages\":\"249-256\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"光通信研究\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.1109/NOC-OCI.2013.6582897\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"光通信研究","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1109/NOC-OCI.2013.6582897","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation
In optical networks a group of logically distinct links can unintentionally share a physical resource (e.g, a cable or a duct). Such a group, called shared risk link group (SRLG), introduces a situation where a single failure of common resource can cause multiple failures. Failure of common resource usually occurs due to physical force (e.g, digging or earthquake) and causes failures of multiple links. Specifically, such a failure can cause both working and spare wavelength path of a logical connection between two edge nodes to fail at the same time, leaving them disconnected until a repair is done. The usual approach to solving this problem consists of introducing more spare capacity to the network and also using a routing algorithm that takes SRLGs into account when computing paths. Such a routing algorithm avoids creating working and spare path pairs that have links contained in the same SRLG, to minimize the negative impact of SRLG failure on logical connection availability. In this paper the impact of physical length of the SRLGs on network availability is evaluated using Monte Carlo simulation. New simulation model for availability evaluation is implemented by discrete-event network simulator ns-3. Implementation approach is discussed, and an overview of model features is provided. For simple cases, Monte Carlo simulation results obtained by using the model are compared to analytical results. The availability results for the general case are obtained using Monte Carlo simulation and discussed.