{"id":712570,"date":"2020-12-14T10:14:25","date_gmt":"2020-12-14T18:14:25","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=712570"},"modified":"2023-09-17T15:16:22","modified_gmt":"2023-09-17T22:16:22","slug":"cost-effective-cloud-edge-traffic-engineering-with-cascara","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/cost-effective-cloud-edge-traffic-engineering-with-cascara\/","title":{"rendered":"Cost-Effective Cloud Edge Traffic Engineering with CASCARA"},"content":{"rendered":"

Inter-domain bandwidth costs comprise a significant amount of the operating expenditure of cloud providers, but have received little attention in research and practice. Traffic engineering systems at the cloud edge must strike a fine balance between minimizing costs and maintaining the latency expected by clients. The nature of this tradeoff is complex due to non-linear pricing schemes prevalent in the market for inter-domain bandwidth. We quantify this tradeoff and uncover several key insights from the link-utilization between a large cloud provider and Internet service providers. Based on these insights, we propose CASCARA, a cloud edge traffic engineering framework to optimize inter-domain bandwidth allocations with non-linear pricing schemes. CASCARA exploits the abundance of latency-equivalent peer links on the cloud edge to minimize costs without impacting latency significantly. Extensive evaluation on production traffic demands of a commercial cloud provider shows that CASCARA saves 11\u201350% in bandwidth costs per cloud PoP, while bounding the increase in client latency by 3 milliseconds.<\/p>\n","protected":false},"excerpt":{"rendered":"

Inter-domain bandwidth costs comprise a significant amount of the operating expenditure of cloud providers, but have received little attention in research and practice. Traffic engineering systems at the cloud edge must strike a fine balance between minimizing costs and maintaining the latency expected by clients. The nature of this tradeoff is complex due to non-linear 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