Recently, Multipath TCP (MPTCP) has been proposed as an alternative transport approach for datacenter networks. MPTCP provides the ability to split a flow into multiple paths thus providing better performance and resilience to failures. Usually, MPTCP is combined with flow-based Equal-Cost Multi-Path Routing (ECMP), which uses random hashing to split the MPTCP subflows over different paths. However, random hashing can be suboptimal as distinct subflows may end up using the same paths, while other available paths remain unutilized. In this paper, we explore an MPTCP-aware SDN controller that facilitates an alternative routing mechanism for the MPTCP subflows. The controller uses packet inspection to provide deterministic subflow assignment to paths. Using the controller, we show that MPTCP can deliver significantly improved performance when connections are not limited by the access links of hosts. To lessen the effect of throughput limitation due to access links, we also investigate the usage of multiple interfaces at the hosts. We demonstrate, using our modification of the MPTCP Linux Kernel, that using multiple subflows per pair of IP addresses can yield improved performance in multi-interface settings.
@cite_2 study the use of multiple host interfaces in datacenters. The authors do not use multihoming (hosts being connected to more than one switch) because it increases the overall costs due to extra switches. Instead, the authors proposed GRIN, a datacenter architecture based on VL2 @cite_8 , which interconnects free interfaces between hosts. Intuitively, a host in GRIN can utilize another host's interface when that interface is not being utilized, thus opportunistically increasing its bandwidth. By design, GRIN provides significant performance improvements only when a considerable percentage of hosts are not heavily utilizing their interfaces. On the other hand, we demonstrate that our dual-homed solution (DH-Jellyfish) can achieve significant performance improvements when all hosts are fully utilizing their interfaces. Note that our approach can deliver the full merits of multihoming without increasing costs (same number of switches).
@cite_8 @cite_2
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Various full bisection designs have been proposed for datacenter networks. They are provisioned for the worst case in which every server sends flat out and there is no congestion anywhere in the network. However, these topologies are prone to considerable underutilisation in the average case encountered in practice. To utilise spare capacity we propose GRIN, a simple, cheap and easily deployable solution that simply wires up any free ports datacenter servers may have. GRIN allows each server to use up to a maximum amount of bandwidth dependent on the number of available ports and the distribution of idle uplinks in the network. Our evaluation found significant benefits for bandwidth-hungry applications running over our testbed, as well as on 1000 EC2 instances. GRIN can be used to augment any existing datacenter network, with a small initial effort and no additional maintenance costs. Multi-tenant datacenters predominantly use equal-cost multipath (ECMP) routing to distribute traffic over multiple network paths. However, ECMP static hashing causes unequal load-balancing and collisions, leading to low throughput and high latencies. Recently proposed alternatives for load-balancing perform better, but are impractical as they require either changing the tenant VM network stacks (e.g., MPTCP) or replacing all the network switches (e.g., CONGA). In this paper, we argue that the end-host hypervisor provides a sweet spot for implementing a spectrum of load-balancing algorithms that are fine-grained, congestion-aware, and reactive to network dynamics at round-trip timescales. We propose CLOVE, a scalable hypervisor-based load-balancer that requires no changes to guest VMs or to physical network switches. CLOVE uses standard ECMP in the physical network, learns about equal-cost network paths using a traceroute mechanism, and learns about congestion state along these paths using standard switch features such as ECN. It then manipulates packet header fields in the hypervisor virtual switch to route traffic over less congested paths. We introduce different variants of CLOVE that differ in the way they learn about congestion in the physical network. Using extensive simulations, we show that CLOVE captures some 80 of the performance gain of best-of-breed hardware-based load-balancing algorithms without the need for expensive hardware replacement. In theory, multi homed Internet hosts, that is, hosts simultaneously connected to multiple Internet service providers (ISP) should see increased access capacity, be able to circumvent possible last-mile congestion problems, and experience improved end-to-end quality of service (QoS). In practice however, the advantages one can gain from multi homing are highly dependent on the path switching mechanism used, that is, on dynamically deciding which ISP should be used as a first-hop. This paper is a first step toward understanding the trade-off between performance improvements multi homing can help achieve and the complexity of the decisions that must be made. We measure changes in end-to-end network layer metrics (loss, latency, jitter) over the different paths available from a multi homed host to a large population of Internet hosts. Our measurements indicate that (1) in over 60 of the cases, one only needs to reevaluate the service provided by each ISP every minute to improve the performance of a specific metric, and that (2) in approximately 85 of the cases, decisions to switch from one ISP to another can be treated independently of the service metric of interest. We conclude that multi homing could in practice result in noticeable performance improvements. Current capacity planning practices based on heavy over-provisioning of power infrastructure hurt (i) the operational costs of data centers as well as (ii) the computational work they can support. We explore a combination of statistical multiplexing techniques to improve the utilization of the power hierarchy within a data center. At the highest level of the power hierarchy, we employ controlled underprovisioning and over-booking of power needs of hosted workloads. At the lower levels, we introduce the novel notion of soft fuses to flexibly distribute provisioned power among hosted workloads based on their needs. Our techniques are built upon a measurement-driven profiling and prediction framework to characterize key statistical properties of the power needs of hosted workloads and their aggregates. We characterize the gains in terms of the amount of computational work (CPU cycles) per provisioned unit of power Computation per Provisioned Watt (CPW). Our technique is able to double the CPWoffered by a Power Distribution Unit (PDU) running the e-commerce benchmark TPC-W compared to conventional provisioning practices. Over-booking the PDU by 10 based on tails of power profiles yields a further improvement of 20 . Reactive techniques implemented on our Xen VMM-based servers dynamically modulate CPU DVFS states to ensure power draw below the limits imposed by soft fuses. Finally, information captured in our profiles also provide ways of controlling application performance degradation despite overbooking. The 95th percentile of TPC-W session response time only grew from 1.59 sec to 1.78 sec--a degradation of 12 .