Abstract-We present a Start-time Fair Qneueing (SFQ) algorithm that is computationally efficient and achieves fairness regardless of variation in a server capacity. We analyze its single server and end-to-end deadline guarantee for variable rate Fluctuation Constrained (FC) and Exponentially Bounded Fluctuation (EBF) servers. To support heterogeneous services and multiple protocol families in integrated services networks, we present a hierarchical SFQ scheduler and derive ifs performance bounds. Our analysis demonstrates that SFQ is suitable for integrated services networks since itz 1) achieves low average as well as maximum delay for low-throughput applications (eg., interactive audio, telnet, etc.); 2) provides fairness which is desirable for VBR video; 3) provide fairness, regardless of variation in server capacity, for throughput-intensive, flow-controlled data applications; 4) enables hierarchical link sharjng which Is desirable for managing heterogeneity; and 5) is computationalIy efficient.Index Terms-Fair queueiug, integrated services networks, packet scheduling.

-Dynamic capacity provisioning is a useful technique for handling the multi-time-scale variations seen in Internet workloads. In this paper, we propose a novel dynamic provisioning technique for multi-tier Internet applications that employs (i) a flexible queuing model to determine how much resources to allocate to each tier of the application, and (ii) a combination of predictive and reactive methods that determine when to provision these resources, both at large and small time scales. We propose a novel data center architecture based on virtual machine monitors to reduce provisioning overheads. Our experiments on a forty-machine Xen/Linux-based hosting platform demonstrate the responsiveness of our technique in handling dynamic workloads. In one scenario where a flash crowd caused the workload of a three-tier application to double, our technique was able to double the application capacity within five minutes, thus maintaining response time targets. Our technique also reduced the overhead of switching servers across applications from several minutes to less than a second, while meeting the performance targets of residual sessions.

As IP technologies providing both tremendous capacity and the ability to establish dynamic secure associations between endpoints emerge, Virtual Private Networks (VPNs) are going through dramatic growth. The number of endpoints per VPN is growing and the communication pattern between endpoints is becoming increasingly hard to forecast. Consequently, users are demanding dependable, dynamic connectivity between endpoints, with the network expected to accommodate any traffic matrix, as long as the traffic to the endpoints does not overwhelm the rates of the respective ingress and egress links. We propose a new service interface, termed a hose, to provide the appropriate performance abstraction. A hose is characterized by the aggregate traffic to and from one endpoint in the VPN to the set of other endpoints in the VPN, and by an associated performance guarantee.Hoses provide important advantages to a VPN customer: (i) flexibility to send traffic to a set of endpoints without having to specify the detailed traffic matrix, and (ii) reduction in the size of access links through multiplexing gains obtained from the natural aggregation of the flows between endpoints.As compared with the conventional point to point (or customer-pipe) model for managing &OS, hoses provide reduction in the state information a customer must maintain.On the other hand, hoses would appear to increase the complexity of the already difficult problem of resource management to support &OS. To manage network resources in the face of this increased uncertainty, we consider both conventional statistical multiplexing techniques, and a new resiring technique based on online measurements.To study these performance issues, we run trace driven simulations, using traffic derived from AT&T's voice network, and from a large corporate data network. From the customer's perspective, we fmd that aggregation of traffic at the hose level provides significant multiplexing gains. From the provider's perspective, we find that the statistical multiplexing and resizing techniques deal effectively with uncertainties about the traffic, providing significant gains over the conventional alternative of a mesh of statically sized customer-pipes between endpoints.

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