1,282 research outputs found
FLAIM: A Multi-level Anonymization Framework for Computer and Network Logs
FLAIM (Framework for Log Anonymization and Information Management) addresses
two important needs not well addressed by current log anonymizers. First, it is
extremely modular and not tied to the specific log being anonymized. Second, it
supports multi-level anonymization, allowing system administrators to make
fine-grained trade-offs between information loss and privacy/security concerns.
In this paper, we examine anonymization solutions to date and note the above
limitations in each. We further describe how FLAIM addresses these problems,
and we describe FLAIM's architecture and features in detail.Comment: 16 pages, 4 figures, in submission to USENIX Lis
Congestion Control using FEC for Conversational Multimedia Communication
In this paper, we propose a new rate control algorithm for conversational
multimedia flows. In our approach, along with Real-time Transport Protocol
(RTP) media packets, we propose sending redundant packets to probe for
available bandwidth. These redundant packets are Forward Error Correction (FEC)
encoded RTP packets. A straightforward interpretation is that if no losses
occur, the sender can increase the sending rate to include the FEC bit rate,
and in the case of losses due to congestion the redundant packets help in
recovering the lost packets. We also show that by varying the FEC bit rate, the
sender is able to conservatively or aggressively probe for available bandwidth.
We evaluate our FEC-based Rate Adaptation (FBRA) algorithm in a network
simulator and in the real-world and compare it to other congestion control
algorithms
Implementation and Deployment of a Distributed Network Topology Discovery Algorithm
In the past few years, the network measurement community has been interested
in the problem of internet topology discovery using a large number (hundreds or
thousands) of measurement monitors. The standard way to obtain information
about the internet topology is to use the traceroute tool from a small number
of monitors. Recent papers have made the case that increasing the number of
monitors will give a more accurate view of the topology. However, scaling up
the number of monitors is not a trivial process. Duplication of effort close to
the monitors wastes time by reexploring well-known parts of the network, and
close to destinations might appear to be a distributed denial-of-service (DDoS)
attack as the probes converge from a set of sources towards a given
destination. In prior work, authors of this report proposed Doubletree, an
algorithm for cooperative topology discovery, that reduces the load on the
network, i.e., router IP interfaces and end-hosts, while discovering almost as
many nodes and links as standard approaches based on traceroute. This report
presents our open-source and freely downloadable implementation of Doubletree
in a tool we call traceroute@home. We describe the deployment and validation of
traceroute@home on the PlanetLab testbed and we report on the lessons learned
from this experience. We discuss how traceroute@home can be developed further
and discuss ideas for future improvements
Traffic Management Applications for Stateful SDN Data Plane
The successful OpenFlow approach to Software Defined Networking (SDN) allows
network programmability through a central controller able to orchestrate a set
of dumb switches. However, the simple match/action abstraction of OpenFlow
switches constrains the evolution of the forwarding rules to be fully managed
by the controller. This can be particularly limiting for a number of
applications that are affected by the delay of the slow control path, like
traffic management applications. Some recent proposals are pushing toward an
evolution of the OpenFlow abstraction to enable the evolution of forwarding
policies directly in the data plane based on state machines and local events.
In this paper, we present two traffic management applications that exploit a
stateful data plane and their prototype implementation based on OpenState, an
OpenFlow evolution that we recently proposed.Comment: 6 pages, 9 figure
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
T3P: Demystifying Low-Earth Orbit Satellite Broadband
The Internet is going through a massive infrastructural revolution with the
advent of low-flying satellite networks, 5/6G, WiFi7, and hollow-core fiber
deployments. While these networks could unleash enhanced connectivity and new
capabilities, it is critical to understand the performance characteristics to
efficiently drive applications over them. Low-Earth orbit (LEO) satellite
mega-constellations like SpaceX Starlink aim to offer broad coverage and low
latencies at the expense of high orbital dynamics leading to continuous latency
changes and frequent satellite hand-offs. This paper aims to quantify
Starlink's latency and its variations and components using a real testbed
spanning multiple latitudes from the North to the South of Europe. We identify
tail latencies as a problem. We develop predictors for latency and throughput
and show their utility in improving application performance by up to 25%. We
also explore how transport protocols can be optimized for LEO networks and show
that this can improve throughput by up to 115% (with only a 5% increase in
latency). Also, our measurement testbed with a footprint across multiple
locations offers unique trigger-based scheduling capabilities that are
necessary to quantify the impact of LEO dynamics.Comment: 16 page
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