Ankit Singla

Information-centric networking: seeing the forest for the trees

There have been many recent papers on data-oriented or content-centric network architectures. Despite the voluminous literature, surprisingly little clarity is emerging as most papers focus on what differentiates them from other proposals. We begin this paper by identifying the existing commonalities and important differences in these designs, and then discuss some remaining research issues. After our review, we emerge skeptical (but open-minded) about the value of this approach to networking.

OSA: an optical switching architecture for data center networks with unprecedented flexibility

A detailed examination of evolving traffic characteristics, operator requirements, and network technology trends suggests a move away from nonblocking interconnects in data center networks (DCNs). As a result, recent efforts have advocated oversubscribed networks with the capability to adapt to traffic requirements on-demand. In this paper, we present the design, implementation, and evaluation of OSA, a novel Optical Switching Architecture for DCNs. Leveraging runtime reconfigurable optical devices, OSA dynamically changes its topology and link capacities, thereby achieving unprecedented flexibility to adapt to dynamic traffic patterns. Extensive analytical simulations using both real and synthetic traffic patterns demonstrate that OSA can deliver high bisection bandwidth (60%-100% of the nonblocking architecture). Implementation and evaluation of a small-scale functional prototype further demonstrate the feasibility of OSA.

Proteus: a topology malleable data center network

Full-bandwidth connectivity between all servers of a data center may be necessary for all-to-all traffic patterns, but such interconnects suffer from high cost, complexity, and energy consumption. Recent work has argued that if all-to-all traffic is uncommon, oversubscribed network architectures that can adapt the topology to meet traffic demands, are sufficient. In line with this work, we propose Proteus, an all-optical architecture targeting unprecedented topology-flexibility, lower complexity and higher energy efficiency.

The Internet at the Speed of Light

For many Internet services, reducing latency improves the user experience and increases revenue for the service provider. While in principle latencies could nearly match the speed of light, we find that infrastructural inefficiencies and protocol overheads cause todays Internet to be much slower than this bound: typically by more than one, and often, by more than two orders of magnitude. Bridging this large gap would not only add value to todays Internet applications, but could also open the door to exciting new applications. Thus, we propose a grand challenge for the networking research community: a speed-of-light Internet. To inform this research agenda, we investigate the causes of latency inflation in the Internet across the network stack. We also discuss a few broad avenues for latency improvement.

Scalable routing on flat names

We introduce a protocol which routes on flat, location-independent identifiers with guaranteed scalability and low stretch. Our design builds on theoretical advances in the area of compact routing, and is the first to realize these guarantees in a dynamic distributed setting.

Practical DCB for Improved Data Center Networks

Storage area networking is driving commodity data center switches to support lossless Ethernet (DCB). Unfortunately, to enable DCB for all traffic on arbitrary network topologies, we must address several problems that can arise in lossless networks, e.g., large buffering delays, unfairness, head of line blocking, and deadlock. We propose TCP-Bolt, a TCP variant that not only addresses the first three problems but reduces flow completion times by as much as 70%. We also introduce a simple, practical deadlock-free routing scheme that eliminates deadlock while achieving aggregate network throughput within 15% of ECMP routing. This small compromise in potential routing capacity is well worth the gains in flow completion time. We note that our results on deadlock-free routing are also of independent interest to the storage area networking community. Further, as our hardware testbed illustrates, these gains are achievable today, without hardware changes to switches or NICs.

Measuring and understanding throughput of network topologies

High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available.

Feasibility study on topology malleable data center networks (DCN) using optical switching technologies

We recently presented a highly advantageous DCN architecture that supports ondemand, run-time topology malleability using WDM and optical space/wavelength switching technologies. We further investigate some implementation-related issues including scalability, hop-by-hop latency and optical power budget.

Beyond fat-trees without antennae, mirrors, and disco-balls

Recent studies have observed that large data center networks often have a few hotspots while most of the network is underutilized. Consequently, numerous data center network designs have explored the approach of identifying these communication hotspots in real-time and eliminating them by leveraging flexible optical or wireless connections to dynamically alter the network topology. These proposals are based on the premise that statically wired network topologies, which lack the opportunity for such online optimization, are fundamentally inefficient, and must be built at uniform full capacity to handle unpredictably skewed traffic. We show this assumption to be false. Our results establish that state-of-the-art static networks can also achieve the performance benefits claimed by dynamic, reconfigurable designs of the same cost: for the skewed traffic workloads used to make the case for dynamic networks, the evaluated static networks can achieve performance matching full-bandwidth fat-trees at two-thirds of the cost. Surprisingly, this can be accomplished even without relying on any form of online optimization, including the optimization of routing configuration in response to the traffic demands. Our results substantially lower the barriers for improving upon todays data centers by showing that a static, cabling-friendly topology built using commodity equipment yields superior performance when combined with well-understood routing methods.

Measuring throughput of data center network topologies

High throughput is a fundamental goal of network design. While myriad network topologies have been proposed to meet this goal, particularly in data center and HPC networking, a consistent and accurate method of evaluating a designs throughput performance and comparing it to past proposals is conspicuously absent. In this work, we develop a framework to benchmark the throughput of network topologies and apply this methodology to reveal insights about network structure. We show that despite being commonly used, cut-based metrics such as bisection bandwidth are the wrong metrics: they yield incorrect conclusions about the throughput performance of networks. We therefore measure flow-based throughput directly and show how to evaluate topologies with nearly-worst-case traffic matrices. We use the flow-based throughput metric to compare the throughput performance of a variety of computer networks. We have made our evaluation framework freely available to facilitate future work on design and evaluation of networks.