753 research outputs found
Combined Intra- and Inter-domain Traffic Engineering using Hot-Potato Aware Link Weights Optimization
A well-known approach to intradomain traffic engineering consists in finding
the set of link weights that minimizes a network-wide objective function for a
given intradomain traffic matrix. This approach is inadequate because it
ignores a potential impact on interdomain routing. Indeed, the resulting set of
link weights may trigger BGP to change the BGP next hop for some destination
prefixes, to enforce hot-potato routing policies. In turn, this results in
changes in the intradomain traffic matrix that have not been anticipated by the
link weights optimizer, possibly leading to degraded network performance.
We propose a BGP-aware link weights optimization method that takes these
effects into account, and even turns them into an advantage. This method uses
the interdomain traffic matrix and other available BGP data, to extend the
intradomain topology with external virtual nodes and links, on which all the
well-tuned heuristics of a classical link weights optimizer can be applied. A
key innovative asset of our method is its ability to also optimize the traffic
on the interdomain peering links. We show, using an operational network as a
case study, that our approach does so efficiently at almost no extra
computational cost.Comment: 12 pages, Short version to be published in ACM SIGMETRICS 2008,
International Conference on Measurement and Modeling of Computer Systems,
June 2-6, 2008, Annapolis, Maryland, US
Game-based communication in Network Control Systems
Network based Control Systems (NCSs) are more and more often selected in designing distributed control systems due to both economic and practical reasons. Today designs of NCSs frequently involve the non-expensive wireless communication instead of traditional wired links. Such systems are usually calledWireless Sensor Networks (WSNs) and are used for many other purposes as well. While convenient in installation and management, wireless links are susceptible to noise and not
very reliable. While common approach of data delivery relies on routing (proactive or reactive), this paper presents a different approach to designing wireless NCSs. In the proposed approach every node takes an independent decision as a result of a game between the nodes. Unlike the routing solutions, the nodes never create any path, and even have no knowledge concerning network topology
Reinforcing Reachable Routes
This paper studies the evaluation of routing algorithms from the perspective of reachability routing, where the goal is to determine all paths between a sender and a receiver. Reachability routing is becoming relevant with the changing dynamics of the Internet and the emergence of low-bandwidth wireless/ad-hoc networks. We make the
case for reinforcement learning as the framework of choice to realize reachability routing, within the confines of the current Internet infrastructure. The setting of the reinforcement learning problem offers several advantages,including loop resolution, multi-path forwarding capability, cost-sensitive routing, and minimizing state overhead,
while maintaining the incremental spirit of current backbone routing algorithms. We identify research issues in reinforcement learning applied to the reachability routing problem to achieve a fluid and robust backbone routing framework. This paper also presents the design, implementation and evaluation of a new reachability routing algorithm that uses a model-based approach to achieve cost-sensitive multi-path forwarding; performance assessment of the algorithm in various troublesome topologies shows consistently superior performance over classical reinforcement learning algorithms. The paper is targeted toward practitioners seeking to implement a reachability routing algorithm
Aspects of proactive traffic engineering in IP networks
To deliver a reliable communication service over the Internet
it is essential for
the network operator to manage the traffic situation in the network.
The traffic situation is controlled by
the routing function which determines what path traffic follows from source
to destination.
Current practices for setting routing parameters in IP networks are
designed to be simple to manage. This can lead to congestion in
parts of the network while other parts of the network are
far from fully utilized. In this thesis we explore issues related
to optimization of the routing function to balance load in the network
and efficiently deliver a reliable communication service to the users.
The optimization takes into account not only the traffic situation under
normal operational conditions, but also traffic situations that appear
under a wide variety of circumstances deviating from the nominal case.
In order to balance load in the network knowledge of the traffic
situations is needed. Consequently, in this thesis
we investigate methods for efficient derivation of the
traffic situation. The derivation is based on estimation of
traffic demands from link load measurements. The advantage
of using link load measurements is that they are easily obtained and consist
of a limited amount of data that need to be processed. We evaluate and demonstrate how estimation
based on link counts gives the operator a fast and accurate description
of the traffic demands. For the evaluation we have access to a unique data
set of complete traffic demands from an operational
IP backbone.
However, to honor service level agreements at all times the variability
of the traffic needs to be accounted for in the load balancing.
In addition, optimization techniques are often sensitive to errors and
variations in input data. Hence, when an optimized routing setting is
subjected to real traffic demands in the network, performance often
deviate from what can be anticipated from the optimization. Thus,
we identify and model different traffic uncertainties and describe
how the routing setting can be optimized, not only for a nominal case,
but for a wide range of different traffic situations that might appear
in the network.
Our results can be applied in MPLS enabled networks as well as in
networks using link state routing protocols such as the widely used
OSPF and IS-IS protocols. Only minor changes may be needed in current
networks to implement our algorithms.
The contributions of this thesis is that we: demonstrate that it is
possible to estimate the traffic matrix with acceptable precision, and
we develop methods and models for common traffic uncertainties to
account for these uncertainties in the optimization of the routing
configuration. In addition, we identify important properties in the
structure of the traffic to successfully balance uncertain and
varying traffic demands
Traffic matrix estimation with enhanced origin destination generator algorithm using simulation of real network
The rapid growth of the Internet has made the issue of ensuring reliability and redundancy a big challenge. Studies of these issues using Traffic Engineering and simulation have been extensively done. In Traffic Matrix Estimation (TME), the Origin–Destination Generator algorithm (ODGen) is limited to the number of hops, where the Expectation Maximization (EM) accuracy is 92%. Most studies have not taken into account real traffic parameters and integration of TME models with routing protocols in their simulation models. Also, there is no a comprehensive model consisting of TME, Border Gateway Protocol (BGP) and Hot Potato (HP) routing in the NS-2 network simulator based on real networks. In this research, Integrated Simulated Model (ISM) is introduced consisting of ODGen-HP algorithm and BGP integrated into the NS-2 network simulator. ISM is then used to simulate the infrastructure of a real production network using actual captured traffic data parameters. Validation is then done against the changes in network topology based on packet loss, delay and throughput. Results gave the average error for packet sent by simulated and production networks of 0% and the average error for packet received by simulation and production networks of 3.61%. The network is modelled with a baseline topology where 5 main nodes were connected together, with redundant links for some nodes. The simulations were repeated for link failures, node addition, and node removal. TME used in ISM is based on ODGen, that is optimized with unlimited number of hops, the accuracy of EM increases to 97% and Central Processing Unit complexity is reduced. HP helps in improving the node which experiences a link failure to select shorter distance route to egress router. In the case of a link failure, HP switching time between the links is 0.05 seconds. ISM performance was evaluated by comparing trace file before and after link failure or by adding nodes (up to 32) or removing nodes. The parameters used for comparison are the packets loss, delay and throughput. The ISM error percentage obtained for packets loss is 0.025%, delay 0.013% and throughput 0.003%
Towards Robust Traffic Engineering in IP Networks
To deliver a reliable communication service it is essential for
the network operator to manage how traffic flows in the network.
The paths taken by the traffic is controlled by the routing function.
Traditional ways of tuning routing in IP networks are designed
to be simple to manage and are not designed to adapt to the
traffic situation in the network. This can lead to congestion in
parts of the network while other parts of the network is
far from fully utilized. In this thesis we explore issues related
to optimization of the routing function to balance load in the network.
We investigate methods for efficient derivation of the
traffic situation using link count measurements. The advantage
of using link counts is that they are easily obtained and yield
a very limited amount of data. We evaluate and show that estimation
based on link counts give the operator a fast and accurate description
of the traffic demands. For the evaluation we have access to a unique data
set of complete traffic demands from an operational
IP backbone.
Furthermore, we evaluate performance of search heuristics to
set weights in link-state routing protocols. For the evaluation
we have access to complete traffic data from a Tier-1 IP network.
Our findings confirm previous studies who use partial traffic data or
synthetic traffic data. We find that optimization using estimated
traffic demands has little significance to the performance of
the load balancing.
Finally, we device an algorithm that finds a routing setting that is
robust to shifts in traffic patterns due to changes in the
interdomain routing. A set of worst case scenarios caused by the interdomain routing changes
is identified and used to solve a robust routing problem. The evaluation
indicates that performance of the robust routing is close to optimal for
a wide variety of traffic scenarios.
The main contribution of this thesis is that we demonstrate that it is
possible to estimate the traffic matrix with good accuracy and to develop
methods that optimize the routing settings to give strong and robust network
performance. Only minor changes might be necessary in order to implement our
algorithms in existing networks
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