5 research outputs found
Faithful reproduction of network experiments
The proliferation of cloud computing has compelled the research community to rethink fundamental aspects of network systems and architectures. However, the tools commonly used to evaluate new ideas have not kept abreast of the latest developments. Common simulation and emulation frameworks fail to provide scalability, fidelity, reproducibility and execute unmodified code, all at the same time.
We present SELENA, a Xen-based network emulation framework that offers fully reproducible experiments via its automation interface and supports the use of unmodified guest operating systems. This allows out-of-the-box compatibility with common applications and OS components, such as network stacks and filesystems. In order to faithfully emulate faster and larger networks, SELENA adopts the technique of time-dilation and transparently slows down the passage of time for guest operating systems. This technique effectively virtualizes the availability of host’s hardware resources and allows the replication of scenarios with increased I/O and computational demands. Users can directly control the tradeoff between fidelity and running-times via intuitive tuning knobs. We evaluate the ability of SELENA to faithfully replicate the behaviour of real systems and compare it against existing popular experimentation platforms. Our results suggest that SELENA can accurately model networks with aggregate link speeds of 44 Gbps or more, while improving by four times the execution time in comparison to ns3 and exhibits near-linear scaling properties.This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2658260.265827
Faster Control Plane Experimentation with Horse
Simulation and emulation are popular approaches for experimentation in
Computer Networks. However, due to their respective inherent drawbacks,
existing solutions cannot perform both fast and realistic control plane
experiments. To close this gap, we introduce Horse. Horse is a hybrid solution
with an emulated control plane, for realism, and simulated data plane, for
speed. Our decoupling of the control and data plane allows us to speed up the
experiments without sacrificing control plane realism
Software-driven definition of virtual testbeds to validate emergent network technologies
This paper is an extended version of our paper published in XIII Jornadas de Ingeniería Telemática (JITEL 2017), Valencia, Spain, 27–29 September 2017, “Definición de Testbeds Virtualizados Utilizando Perfiles de Actividad de Red”The lack of privileged access to emergent and operational deployments is one of the key matters during validation and testing of novel telecommunication systems and technologies. This matter jeopardizes the repeatability of experiments, which results in burdens for innovation and research in these areas. In this light, we present a method and architecture to make the software-driven definition of virtual testbeds easier. As distinguishing features, our proposal can mimic operational deployments by using high-dimensional activity patterns. These activity patterns shape the effect of a control module that triggers agents for the generation of network traffic. This solution exploits the capabilities of network emulation and virtualization systems, which nowadays can be easily deployed in commodity servers. With this, we accomplish a reproducible definition of realistic experimental conditions and the introduction of real agent implementations in a cost-effective fashion. We evaluate our solution in a case study that is comprised of the validation of a network-monitoring tool for Voice over IP (VoIP) deployments. Our experimental results support the viability of the method and illustrate how this formulation can improve the experimentation in emergent technologies.This work has been partially funded by the SpanishMinistry of Economy and Competitiveness
and the European Regional Development Fund under the projects TRÁFICA (MINECO/FEDER TEC2015-69417-C2-1-R) and RACING DRONES (MINECO/FEDER RTC-2016-4744-7
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Latency-driven performance in data centres
Data centre based cloud computing has revolutionised the way businesses use computing infrastructure. Instead of building their own data centres, companies rent computing resources
and deploy their applications on cloud hardware. Providing customers with well-defined application performance guarantees is of paramount importance to ensure transparency and to build
a lasting collaboration between users and cloud operators. A user’s application performance is
subject to the constraints of the resources it has been allocated and to the impact of the network
conditions in the data centre.
In this dissertation, I argue that application performance in data centres can be improved through
cluster scheduling of applications informed by predictions of application performance for given
network latency, and measurements of current network latency in data centres between hosts.
Firstly, I show how to use the Precision Time Protocol (PTP), through an open-source software
implementation PTPd, to measure network latency and packet loss in data centres. I propose
PTPmesh, which uses PTPd, as a cloud network monitoring tool for tenants. Furthermore, I
conduct a measurement study using PTPmesh in different cloud providers, finding that network
latency variability in data centres is still common. Normal latency values in data centres are
in the order of tens or hundreds of microseconds, while unexpected events, such as network
congestion or packet loss, can lead to latency spikes in the order of milliseconds.
Secondly, I show that network latency matters for certain distributed applications even in small
amounts of tens or hundreds of microseconds, significantly reducing their performance. I propose a methodology to determine the impact of network latency on distributed applications
performance by injecting artificial delay into the network of an experimental setup. Based on
the experimental results, I build functions that predict the performance of an application for a
given network latency.
Given the network latency variability observed in data centers, applications’ performance is
determined by their placement within the data centre. Thirdly, I propose latency-driven, application performance-aware, cluster scheduling as a way to provide performance guarantees
to applications. I introduce NoMora, a cluster scheduling architecture that leverages the predictions of application performance dependent upon network latency combined with dynamic
network latency measurements taken between pairs of hosts in data centres to place applications. Moreover, I show that NoMora improves application performance by choosing better
placements than other scheduling policies.MEASUREMENT FOR EUROPE: TRAINING AND RESEARCH FOR INTERNET COMMUNICATIONS SCIENCE, European Commission FP7 Marie Curie Innovative Training Networks (ITN)
ENDEAVOUR, European Commission Horizon 2020 (H2020) Industrial Leadership (IL