Radhika Mittal

Empowering developers to estimate app energy consumption

Battery life is a critical performance and user experience metric on mobile devices. However, it is difficult for app developers to measure the energy used by their apps, and to explore how energy use might change with conditions that vary outside of the developers control such as network congestion, choice of mobile operator, and user settings for screen brightness. We present an energy emulation tool that allows developers to estimate the energy use for their mobile apps on their development workstation itself. The proposed techniques scale the emulated resources including the processing speed and network characteristics to match the app behavior to that on a real mobile device. We also enable exploring multiple operating conditions that the developers cannot easily reproduce in their lab. The estimation of energy relies on power models for various components, and we also add new power models for components not modeled in prior works such as AMOLED displays. We also present a prototype implementation of this tool and evaluate it through comparisons with real device energy measurements.

Low latency via redundancy

Low latency is critical for interactive networked applications. But while we know how to scale systems to increase capacity, reducing latency --- especially the tail of the latency distribution --- can be much more difficult. In this paper, we argue that the use of redundancy is an effective way to convert extra capacity into reduced latency. By initiating redundant operations across diverse resources and using the first result which completes, redundancy improves a systems latency even under exceptional conditions. We study the tradeoff with added system utilization, characterizing the situations in which replicating all tasks reduces mean latency. We then demonstrate empirically that replicating all operations can result in significant mean and tail latency reduction in real-world systems including DNS queries, database servers, and packet forwarding within networks.

TIMELY: RTT-based Congestion Control for the Datacenter

Datacenter transports aim to deliver low latency messaging together with high throughput. We show that simple packet delay, measured as round-trip times at hosts, is an effective congestion signal without the need for switch feedback. First, we show that advances in NIC hardware have made RTT measurement possible with microsecond accuracy, and that these RTTs are sufficient to estimate switch queueing. Then we describe how TIMELY can adjust transmission rates using RTT gradients to keep packet latency low while delivering high bandwidth. We implement our design in host software running over NICs with OS-bypass capabilities. We show using experiments with up to hundreds of machines on a Clos network topology that it provides excellent performance: turning on TIMELY for OS-bypass messaging over a fabric with PFC lowers 99 percentile tail latency by 9X while maintaining near line-rate throughput. Our system also outperforms DCTCP running in an optimized kernel, reducing tail latency by

Revisiting network support for RDMA

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Restructuring endpoint congestion control

X. To the best of our knowledge, TIMELY is the first delay-based congestion control protocol for use in the datacenter, and it achieves its results despite having an order of magnitude fewer RTT signals (due to NIC offload) than earlier delay-based schemes such as Vegas.

SPReAD: On Spherical Part Recognition by Axial Discretization in 4D Hough Space

The advent of RoCE (RDMA over Converged Ethernet) has led to a significant increase in the use of RDMA in datacenter networks. To achieve good performance, RoCE requires a lossless network which is in turn achieved by enabling Priority Flow Control (PFC) within the network. However, PFC brings with it a host of problems such as head-of-the-line blocking, congestion spreading, and occasional deadlocks. Rather than seek to fix these issues, we instead ask: is PFC fundamentally required to support RDMA over Ethernet? We show that the need for PFC is an artifact of current RoCE NIC designs rather than a fundamental requirement. We propose an improved RoCE NIC (IRN) design that makes a few simple changes to the RoCE NIC for better handling of packet losses. We show that IRN (without PFC) outperforms RoCE (with PFC) by 6-83% for typical network scenarios. Thus not only does IRN eliminate the need for PFC, it improves performance in the process! We further show that the changes that IRN introduces can be implemented with modest overheads of about 3-10% to NIC resources. Based on our results, we argue that research and industry should rethink the current trajectory of network support for RDMA.

Recursively cautious congestion control

This paper describes the implementation and evaluation of a system to implement complex congestion control functions by placing them in a separate agent outside the datapath. Each datapath---such as the Linux kernel TCP, UDP-based QUIC, or kernel-bypass transports like mTCP-on-DPDK---summarizes information about packet round-trip times, receptions, losses, and ECN via a well-defined interface to algorithms running in the off-datapath Congestion Control Plane (CCP). The algorithms use this information to control the datapaths congestion window or pacing rate. Algorithms written in CCP can run on multiple datapaths. CCP improves both the pace of development and ease of maintenance of congestion control algorithms by providing better, modular abstractions, and supports aggregation capabilities of the Congestion Manager, all with one-time changes to datapaths. CCP also enables new capabilities, such as Copa in Linux TCP, several algorithms running on QUIC and mTCP/DPDK, and the use of signal processing algorithms to detect whether cross-traffic is ACK-clocked. Experiments with our user-level Linux CCP implementation show that CCP algorithms behave similarly to kernel algorithms, and incur modest CPU overhead of a few percent.

Universal Packet Scheduling

A novel algorithm is proposed to locate the sets of adjacent co-spherical triangles for a given object, which enables us to detect spheres and spherical parts constituting the object. An extension of the idea of Hough transform has been used, aided by axial discretization and restricted searching, along with the geometric data structure of doubly connected edge list. The algorithm has been analyzed and shown to achieve significant efficiency in space and run-time. On testing the algorithm with various 3D objects, it is found to produce the desired result. Effects of different input parameters have been explained and the robustness of the algorithm has been shown for rough/noisy surfaces.