5 research outputs found
Multilevel MDA-Lite Paris Traceroute
Since its introduction in 2006-2007, Paris Traceroute and its Multipath
Detection Algorithm (MDA) have been used to conduct well over a billion IP
level multipath route traces from platforms such as M-Lab. Unfortunately, the
MDA requires a large number of packets in order to trace an entire topology of
load balanced paths between a source and a destination, which makes it
undesirable for platforms that otherwise deploy Paris Traceroute, such as RIPE
Atlas. In this paper we present a major update to the Paris Traceroute tool.
Our contributions are: (1) MDA-Lite, an alternative to the MDA that
significantly cuts overhead while maintaining a low failure probability; (2)
Fakeroute, a simulator that enables validation of a multipath route tracing
tool's adherence to its claimed failure probability bounds; (3) multilevel
multipath route tracing, with, for the first time, a Traceroute tool that
provides a router-level view of multipath routes; and (4) surveys at both the
IP and router levels of multipath routing in the Internet, showing, among other
things, that load balancing topologies have increased in size well beyond what
has been previously reported as recently as 2016. The data and the software
underlying these results are publicly available.Comment: Preprint. To appear in Proc. ACM Internet Measurement Conference 201
EdgeNet: A Multi-Tenant and Multi-Provider Edge Cloud
International audienceEdgeNet is a public Kubernetes cluster dedicated to network and distributed systems research, supporting experiments that are deployed concurrently by independent groups. Its nodes are hosted by multiple institutions around the world. It represents a departure from the classic Kubernetes model, where the nodes that are available to a single tenant reside in a small number of well-interconnected data centers. The free open-source EdgeNet code extends Kubernetes to the edge, making three key contributions: multi-tenancy, geographical deployments, and single-command node installation. We show that establishing a public Kubernetes cluster over the internet, with multiple tenants and multiple hosting providers is viable. Preliminary results also indicate that the EdgeNet testbed that we run provides a satisfactory environment to run a variety of experiments with minimal network overhead
Performance Analysis of Multipath BGP
Multipath BGP (M-BGP) allows a BGP router to install multiple 'equally-good'
paths, via parallel inter-domain border links, to a destination prefix. M-BGP
differs from the multipath routing techniques in many ways, e.g. M-BGP is only
implemented at border routers of Autonomous Systems (ASes); and while it shares
traffic to different IP addresses in a destination prefix via different border
links, any traffic to a given destination IP always follows the same border
link. Recently we studied Looking Glass data and reported the wide deployment
of M-BGP in the Internet; in particular, Hurricane Electric (AS6939) has
implemented over 1,000 cases of M-BGP to hundreds of its peering ASes.
In this paper, we analyzed the performance of M-BGP. We used RIPE Atlas to
send traceroute probes to a series of destination prefixes through Hurricane
Electric's border routers implemented with M-BGP. We examined the distribution
of Round Trip Time to each probed IP address in a destination prefix and their
variation during the measurement. We observed that the deployment of M-BGP can
guarantee stable routing between ASes and enhance a network's resilience to
traffic changes. Our work provides insights into the unique characteristics of
M-BGP as an effective technique for load balancing.Comment: IEEE Global Internet (GI) Symposium 202
Evaluating and Improving Internet Load Balancing with Large-Scale Latency Measurements
Load balancing is used in the Internet to distribute load across resources at different levels, from global load balancing that distributes client requests across servers at the Internet level to path-level load balancing that balances traffic across load-balanced paths. These load balancing algorithms generally work under certain assumptions on performance similarity. Specifically, global load balancing divides the Internet address space into client aggregations and assumes that clients in the same aggregation have similar performance to the same server; load-balanced paths are generally selected for load balancing as if they have similar performance. However, as performance similarity is typically achieved with similarity in path properties, e.g., topology and hop count, which do not necessarily lead to similar performance, performance between clients in the same aggregation and between load-balanced paths could differ significantly.
This dissertation evaluates and improves global and path-level load balancing in terms of performance similarity. We achieve this with large-scale latency measurements, which not only allow us to systematically identify and evaluate the performance issues of Internet load balancing at scale, but also enable us to develop data-driven approaches to improve the performance. Specifically, this dissertation consists of three parts. First, we study the issues of existing client aggregations for global load balancing and then design AP-atoms, a data-driven client aggregation learned from passive large-scale latency measurements. Second, we show that the latency imbalance between load-balanced paths, previously deemed insignificant, is now both significant and prevalent. We present Flipr, a network prober that actively collects large-scale latency measurements to characterize the latency imbalance issue. Lastly, we design another network prober, Congi, that can detect congestion at scale and use Congi to study the congestion imbalance problem at scale. For both latency and congestion imbalance, we demonstrate that they could greatly affect the performance of various applications.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168012/1/yibo_1.pd