PROJECT TITLE :
Delay-Optimized Video Traffic Routing in Software-Defined Interdatacenter Networks
Several video streaming applications operate their geo-distributed services in the cloud, profiting from superior connectivities between datacenters to push content closer to users or to relay live video traffic between end users at the next throughput. Within the meantime, inter-datacenter networks conjointly carry high volumes of different sorts of traffic, together with service replication and knowledge backups, e.g., for storage and email services. It's an necessary research topic to optimally engineer and schedule inter-datacenter traffic, taking into consideration the stringent latency necessities of video flows when transmitted along inter-datacenter links shared with different varieties of traffic. Since inter-datacenter networks are typically overprovisioned, unlike previous work that mainly aims to maximize link utilization, we tend to propose a delay-optimized traffic routing scheme to explicitly differentiate path selection for different sessions in step with their delay sensitivities, leading to a software-defined inter-datacenter networking overlay implemented at the application layer. We tend to show that our solution will yield sparse path selection by solely solving linear programs, and therefore, in distinction to prior traffic engineering solutions, does not lead to overly fine-grained traffic splitting, more reducing packet resequencing overhead and the amount of forwarding rules to be put in in each forwarding unit. Real-world experiments based on a deployment on six globally distributed Amazon EC2 datacenters have shown that our system can effectively prioritize and improve the delay performance of inter-datacenter video flows at a low value.
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