Scalable Application- and User-aware Resource Allocation in Enterprise Networks Using End-host Pacing
This addresses resource allocation challenges for heterogeneous applications in enterprise networks, offering incremental improvements over best-effort approaches.
The paper tackled the problem of scalable user- and application-aware resource allocation in enterprise networks by proposing a system design based on Software-Defined Networking and end-host pacing, which improved minimum and total utility, minimized packet loss and queuing delay, established fairness, and achieved predictable performance at high link utilization.
Scalable user- and application-aware resource allocation for heterogeneous applications sharing an enterprise network is still an unresolved problem. The main challenges are: (i) How to define user- and application-aware shares of resources? (ii) How to determine an allocation of shares of network resources to applications? (iii) How to allocate the shares per application in heterogeneous networks at scale? In this paper we propose solutions to the three challenges and introduce a system design for enterprise deployment. Defining the necessary resource shares per application is hard, as the intended use case and user's preferences influence the resource demand. Utility functions based on user experience enable a mapping of network resources in terms of throughput and latency budget to a common user-level utility scale. A multi-objective MILP is formulated to solve the throughput- and delay-aware embedding of each utility function for a max-min fairness criteria. The allocation of resources in traditional networks with policing and scheduling cannot distinguish large numbers of classes. We propose a resource allocation system design for enterprise networks based on Software-Defined Networking principles to achieve delay-constrained routing in the network and application pacing at the end-hosts. The system design is evaluated against best effort networks with applications competing for the throughput of a constrained link. The competing applications belong to the five application classes web browsing, file download, remote terminal work, video streaming, and Voice-over-IP. The results show that the proposed methodology improves the minimum and total utility, minimizes packet loss and queuing delay at bottlenecks, establishes fairness in terms of utility between applications, and achieves predictable application performance at high link utilization.