{"title":"Network adaptability to disasters by exploiting degraded-service tolerance","authors":"B. Mukherjee, S. Savas, Ning-Hai Bao","doi":"10.1109/ICOCN.2014.6987124","DOIUrl":null,"url":null,"abstract":"This paper studies optimal traffic provisioning under service heterogeneity to alleviate the dramatic decrease in network resources, a.k.a. resource crunch, caused by large-area network failures or a traffic surge. Some services are sensitive to capacity provided, while others (e.g., video streaming) can operate with reduced bandwidth (degraded service). Degraded-service-tolerant connections can be admitted and recovered with reduced service under resource crunch. Our adaptive solutions distribute capacity among competing services when some may get degraded service under resource crunch but satisfying the Service-Level Objectives (SLOs).","PeriodicalId":364683,"journal":{"name":"2014 13th International Conference on Optical Communications and Networks (ICOCN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 13th International Conference on Optical Communications and Networks (ICOCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCN.2014.6987124","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper studies optimal traffic provisioning under service heterogeneity to alleviate the dramatic decrease in network resources, a.k.a. resource crunch, caused by large-area network failures or a traffic surge. Some services are sensitive to capacity provided, while others (e.g., video streaming) can operate with reduced bandwidth (degraded service). Degraded-service-tolerant connections can be admitted and recovered with reduced service under resource crunch. Our adaptive solutions distribute capacity among competing services when some may get degraded service under resource crunch but satisfying the Service-Level Objectives (SLOs).