By Topic

Large-Scale Network Parameter Configuration Using an On-Line Simulation Framework

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

As the Internet infrastructure grows to support a variety of services, its legacy protocols are being overloaded with new functions such as traffic engineering. Today, operators engineer such capabilities through clever, but manual parameter tuning. In this paper, we propose a back-end support tool for large-scale parameter configuration that is based on efficient parameter state space search techniques and on-line simulation. The framework is useful when the network protocol performance is sensitive to its parameter settings, and its performance can be reasonably modeled in simulation. In particular, our system imports the network topology, relevant protocol models and latest monitored traffic patterns into a simulation that runs on-line in a network operations center (NOC). Each simulation evaluates the network performance for a particular setting of protocol parameters. We propose an efficient large-dimensional parameter state space search technique called ldquorecursive random search (RRS).rdquo Each sample point chosen by RRS results in a single simulation. An important feature of this framework is its flexibility: it allows arbitrary choices in terms of the simulation engines used (e.g., ns-2, SSFnet), network protocols to be simulated (e.g., OSPF, BGP), and in the specification of the optimization objectives. We demonstrate the flexibility and relevance of this framework in three scenarios: joint tuning of the RED buffer management parameters at multiple bottlenecks, traffic engineering using OSPF link weight tuning, and outbound load-balancing of traffic at peering/transit points using BGP LOCAL_PREF parameter.

Published in:

Networking, IEEE/ACM Transactions on  (Volume:16 ,  Issue: 4 )