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AMPLE An Adaptive Traffic Engineering System Based on Virtual Routing Topologies.

Platform : WIRELESS COMMUNICATIONS

IEEE Projects Years : 2012

AMPLE An Adaptive Traffic Engineering System Based on Virtual Routing Topologies.

Abstract
Handling traffic dynamics in order to avoid network congestion and
subsequent service disruptions is one of the key tasks performed by contemporary
network management systems. Given the simple but rigid routing and forwarding
functionalities in IP base environments, efficient resource management and
control solutions against dynamic traffic conditions is still yet to be obtained. In
this article, we introduce AMPLE — an efficient traffic engineering and
management system that performs adaptive traffic control by using multiple
virtualized routing topologies. The proposed system consists of two
complementary components: offline link weight optimization that takes as input
the physical network topology and tries to produce maximum routing path
diversity across multiple virtual routing topologies for long term operation
through the optimized setting of link weights. Based on these diverse paths,
adaptive traffic control performs intelligent traffic splitting across individual
routing topologies in reaction to the monitored network dynamics at short
timescale. According to our evaluation with real network topologies and traffic
traces, the proposed system is able to cope almost optimally with unpredicted
traffic dynamics and, as such, it constitutes a new proposal for achieving better
quality of service and overall network performance in IP networks.
Architecture
Existing system
In Existing System, IGP-based TE mechanisms are only confined to
offline operation and hence cannot cope efficiently with significant traffic dynamics.
There are well known reasons for this limitation: IGP-based TE only allows for static
traffic delivery through native IGP paths, without flexible traffic splitting for dynamic
load balancing. In addition, changing IGP link weights in reaction to emerging network
congestion may cause routing re-convergence problems that potentially disrupt ongoing
traffic sessions. In effect, it has been recently argued that dynamic/online route re
computation is to be considered harmful even in the case of network failures, let alone for
dealing with traffic dynamics.
Proposed System
In proposed system consists of two complementary components: offline link
weight optimization that takes as input the physical network topology and tries to produce
maximum routing path diversity across multiple virtual routing topologies for long term
operation through the optimized setting of link weights. Based on these diverse paths,
adaptive traffic control performs intelligent traffic splitting across individual routing
topologies in reaction to the monitored network dynamics at short timescale.
According to our evaluation with real network topologies and traffic traces, the proposed
system is able to cope almost optimally with unpredicted traffic dynamics and, as such, it
constitutes a new proposal for achieving better quality of service and overall network
performance in IP networks.
Modules
1. Virtual traffic allocation
2. Offline Link Weight Optimization
3. Network Monitoring
4. Adaptive Traffic Control
Virtual Traffic Allocation
In this Module, the diverse MT-IGP paths according to the link weights computed
by OLWO. Monitored network and traffic data such as incoming traffic volume and link
utilizations. At each short-time interval, ATC computes a new traffic splitting ratio across
individual VRTs for re-assigning traffic in an optimal way to the diverse IGP paths
between each S-D pair. This functionality is handled by a centralized TE manager who
has complete knowledge of the network topology and periodically gathers the up-to-date
monitored traffic conditions of the operating network. These new splitting ratios are then
configured by the TE manager to individual source PoP nodes, who use this configuration
for remarking the multi-topology identifiers (MTIDs) of their locally originated traffic
accordingly.
Offline Link Weight Optimization
In this module, to determine the definition of “path diversity” between PoPs for
traffic engineering. Let’s consider the following two scenarios of MT-IGP link weight
configuration. In the first case, highly diverse paths (e.g. end-to-end disjoint ones) are
available for some Pop-level S-D pairs, while for some other pairs individual paths are
completely overlapping with each other across all VRTs. In the second case, none of the
S-D pairs have disjoint paths, but none of them are completely overlapping either.
Obviously, in the first case if any “critical” link that is shared by all paths becomes
congested, its load cannot be alleviated through adjusting traffic splitting ratios at the
associated sources, as their traffic will inevitably travel through this link no matter which
VRT is used. Hence, our strategy targets the second scenario by achieving “balanced”
path diversity across all S-D pairs.
Network Monitoring
In this Module, Network monitoring is responsible for collecting up-to-date traffic
conditions in real-time and plays an important role for supporting the ATC operations.
AMPLE adopts a hop-by-hop based monitoring mechanism that is similar to the
proposal.
The basic idea is that a dedicated monitoring agent deployed at every PoP node is
responsible for monitoring:
 The volume of the traffic originated by the local customers toward other PoPs
(intra- PoP traffic is ignored).
 The utilization of the directly attached inter-PoP links
Adaptive Traffic Control
In this Module, Measure the incoming traffic volume and the network load for the
current interval as compute new traffic splitting ratios at individual PoP source nodes
based on the splitting ratio configuration in the previous interval, according to the newly
measured traffic demand and the network load for dynamic load balancing.
System Requirements:
Hardware Requirements:
· System : Pentium IV 2.4 GHz.
· Hard Disk : 40 GB.
· Floppy Drive : 1.44 Mb.
· Monitor : 15 VGA Color.
· Mouse : Logitech.
· Ram : 512 Mb.
Software Requirements:
· Operating system : - Windows XP.
· Coding Language : C#.Net


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