Improving Scalability of Network Emulation through Parallelism and Abstraction

Kiddle, Cameron; Simmonds, Rob; Unger, Brian

doi:10.1109/anss.2005.26

Cited by 8 publications

(3 citation statements)

References 29 publications

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“…which we could run the nario, Figure 10 ulation research, there have ents realized in the form of ulab, GTNetS, PDNS, SSF, ame just a few. Among the ion for higher fidelity, the dilation [1], time jails [9], virtual time [10], real-time interface optimizations [8,11,12], and others [13][14][15][16]. However, we are not aware of prior work on simulation-specific schedulers for simulating multi-core guests on multi-core hosts.…”

Section: Analysis Of Resultsmentioning

confidence: 99%

Efficiently Scheduling Multi-Core Guest Virtual Machines on Multi-Core Hosts in Network Simulation

Yoginath

Perumalla

2011

2011 IEEE Workshop on Principles of Advanced and Distributed Simulation

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Virtual machine (VM)-based simulation is a method used by network simulators to incorporate realistic application behaviors by executing actual VMs as high-fidelity surrogates for simulated end-hosts. A critical requirement in such a method is the simulation timeordered scheduling and execution of the VMs. Prior approaches such as time dilation are less efficient due to the high degree of multiplexing possible when multiple multi-core VMs are simulated on multi-core host systems. We present a new simulation time-ordered scheduler to efficiently schedule multi-core VMs on multi-core real hosts, with a virtual clock realized on each virtual core. The distinguishing features of our approach are: (1) customizable granularity of the VM scheduling time unit on the simulation time axis, (2) ability to take arbitrary leaps in virtual time by VMs to maximize the utilization of host (real) cores when guest virtual cores idle, and (3) empirically determinable optimality in the tradeoff between total execution (real) time and time-ordering accuracy levels. Experiments show that it is possible to get nearly perfect time-ordered execution, with a slight cost in total run time, relative to optimized non-simulation VM schedulers.Interestingly, with our time-ordered scheduler, it is also possible to reduce the time-ordering error from over 50% of non-simulation scheduler to less than 1% realized by our scheduler, with almost the same run time efficiency as that of the highly efficient nonsimulation VM schedulers.

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Section: Analysis Of Resultsmentioning

confidence: 99%

Efficiently Scheduling Multi-Core Guest Virtual Machines on Multi-Core Hosts in Network Simulation

Yoginath

Perumalla

2011

2011 IEEE Workshop on Principles of Advanced and Distributed Simulation

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“…(6) A Ring scenario with 100 nodes arranged in a Ring. (7) A Campus model with a network of connected campus sites, which is often used to evaluate scalability in the field of parallel simulation [18], [44]. We use 20 campuses with a total of 5,480 nodes.…”

Section: Initial Testbed Configurationmentioning

confidence: 99%

Scalable Network Emulation - The NET Approach

Grau¹,

Herrmann²,

Rothermel³

2012

JCM

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Network emulation is an efficient method for evaluating distributed applications and communication protocols bycombining the benefits of real world experiments and networksimulation. The process of network emulation involves the executionof connected virtual nodes running the software under test ina controlled environment. Our Network Emulation Testbed (NET) achieves high scalability by combining efficient node virtualization and adaptive virtual time. In this paper, we provide an overview of our system. First, we introduce our efficient emulation architecture. Second, we present our approaches (NETplace and NETbalance) to minimize the runtime of the network experiments. The idea of NETplace is to minimize the load of the testbed by calculating an initial placement of virtual nodes onto the testbed nodes. During the runtime of the experiment NETbalance adapts this placement to changed resource requirements of the software under test. Finally, we introduce NETcaptain, a graphical user interface to setup, control and visualize network experiments

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“…While NS is monolithic, there are also distributed simulators used in emulation-based experiment setups, such as IP-TNE. IP-TNE is built on IP-TN, which uses CCTKit that implements the Critical Channel Traversing (CCT) algorithm for parallel discrete event simulation [32], [33], [34]. In [35], Bradford et al discusses different methods for reading packets from and writing packets to real networks for network emulators such as IP-TNE.…”

Section: Network Emulation -Mostly Simulated Systemsmentioning

confidence: 99%

A Stance On Emulation And Testbeds, And A Survey Of Network Emulators And Testbeds

Goektuerk¹

2007

ECMS 2007 Proceedings Edited By: I. Zelinka, Z. Oplatkova, A. Orsoni

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Abstract-Emulations and testbeds are popular tools in networking research. However, what differentiates testbeds from emulations is not terminologically clear. In this article, we first discuss the terms emulation and testbed, and present the reflexivity principle for identifying testbeds. We then present a survey of forty two network emulators and testbeds reported in the literature, categorizing them according to the approaches used. Another eighteen that can be added to this survey as future work are also identified.

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Improving Scalability of Network Emulation through Parallelism and Abstraction

Cited by 8 publications

References 29 publications

Efficiently Scheduling Multi-Core Guest Virtual Machines on Multi-Core Hosts in Network Simulation

Efficiently Scheduling Multi-Core Guest Virtual Machines on Multi-Core Hosts in Network Simulation

Scalable Network Emulation - The NET Approach

A Stance On Emulation And Testbeds, And A Survey Of Network Emulators And Testbeds

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