Intelligent Routing Application – Enabling Service Guarantees

Intelligent Routing for MPLS Networks

IP networks are becoming increasingly important to carriers as the means for providing a universal network for delivering cost effective services such as telephony, video and other broadband data services. These next generation services require more and more bandwidth and also an increase in performance of the network in order to meet rising customer expectations. These rising customer expectations of network performance and reliability will place increasing pressure on the operator's service and network management systems. As the demand for highly reliable broadband services continues to grow, network operators will come under increasing pressure to avoid or minimize network congestion which impacts detrimentally on the service performance experienced by the customer. Customers whose businesses depend on high quality data services are demanding service guarantees leaving service providers with the need to actively manage traffic streams through their IP network.

The problem with shortest path routing
The need to develop new revenue streams and maximize return on investment for existing infrastructure, means that past approaches to network management, in which the operators would simply expand the capacity of their networks in order to cope with increasing traffic loads, will not suffice in the future. Part of the reason for this past methodology is due to the reliance of IP networks on shortest path routing protocols that do not take into account network traffic levels.

These protocols work well when offered traffic levels are small compared to the network capacity, but network performance degrades as traffic levels rise, because the shortest path routing can introduce congestion hot spots. In order to avoid performance problems resulting from network congestion, network operators have commonly over-provisioned their networks. However, this network 'over-engineering' is a costly solution and does not guarantee that congestion hot spots will not arise, particularly during network element failure situations.

MPLS combined with intelligent routing solves the problem
A more economical approach is to use intelligent routing algorithms to route traffic according to network state and traffic conditions. Multi-Protocol Label Switching (MPLS) introduces traffic-engineering capabilities for IP networks that enables the use of intelligent routing. MPLS allows network operators to explicitly select paths between end-points in the network. When MPLS is combined with intelligent routing algorithms, to choose the underlying paths, the goal of providing routing solutions that take into account the state of the network and the offered traffic levels can be achieved.

The Elanti Network Optimization System (ENOS) is an Intelligent Routing Solution that offers a technique for MPLS networks, which use a global view of the network state and traffic load, to provide efficient use of network resources for eliminating congestion hot spots that arise due to shifting traffic patterns and network element failures. The Elanti Network Optimization System is unique in that it is capable of providing an optimal set of paths for the network in real-time, which means that the network can adapt to changing situations as they arise. The solution is flexible and can be extended to support changing requirements when new products and services are introduced, e.g. service differentiation through multi-class of service traffic.

Elanti Network Optimization System Overview

The Elanti Network Optimization System’s intelligent routing solution uses LSPs to carry all the offered traffic. The system is able to directly obtain a measure of the traffic distribution between all origin-destination (OD) pairs in the network simply by requesting the individual LSP packet counts from the head-end routers. The system selects the actual paths to be used for the measured traffic distribution by using a patented intelligent route selection technique. In practice, the solution periodically contacts the head-end routers for traffic levels, computes the best paths for the current network load and configures the required paths onto the head-end routers.

The advantages of this approach are that:

the system has complete control over all the traffic flowing in the network and can therefore make routing decisions which make best use of the network resources;
the system uses the actual traffic distribution as input to its routing decisions which is more accurate than relying on theoretical traffic models or estimated traffic values;
the system simplifies the process of traffic management by automating the complete tasks of data collection, path determination and configuration.

Unlike the distributed calculation done by the routers using shortest path routing, the Elanti Network Optimization System uses a global optimization to select the paths which lead to the best network performance and most effective use of network.

Enabling Service Guarantees
For many years the prevailing consensus among network operators has been that the only practical way to manage the performance of IP networks is to ensure that sufficient spare capacity is available in the network to deal with unforeseen traffic increases or network element failures. The reason for this was presumably due to the lack of the appropriate tools to manage traffic flows on IP networks and the acceptance that IP networks simply provided a best effort service for all users.

With the advent of MPLS there is now a shift away from this simplistic approach. Over-provisioned networks have been recognized as an uneconomical way of providing services in a competitive environment and now the emphasis is on maximizing revenue by providing different classes of service whereby customers pay according to the class of service they select.

Managing the network performance by the simple strategy of over-provisioning can work against this objective because it can lead the operator towards dimensioning the network to meet the performance expectations of the most demanding customers. However, the excess network capacity creates the problem that sufficient spare capacity will remain in the network so that all customers receive the same effective quality of service, thereby negating the incentive for customers to pay more for supposed better performance.

Optimization of IP/MPLS networks for the current single class of service environment can be used to achieve significant improvements in network efficiency and performance experienced by the customer.

The Elanti Network Optimization System moves the service operator towards service differentiation by making it possible to incorporate multiple classes of service into the intelligent routing solution. In a multi-class of service MPLS network, the Elanti Network Optimization System can be used to select different paths for different classes of service, such that for instance, the highest priority traffic class will travel over paths composed of links with the lowest utilization, while the next highest priority class would travel over links with commensurately higher utilizations, and so on. The network performance experienced by each class of service can then be graded according to its priority.

As well as ensuring best use of resources and providing service differentiation in a multi-class of service environment, the Elanti Network Optimization System can lead to other advantages:

Service Level Agreement (SLA) Management: The current generation of SLAs provides guarantees on the performance of the network from a network-centric view point. For instance many SLAs state that the delay between certain designated points within the network will not exceed a given amount, or that the overall loss in the network will be below a certain figure. When this is translated to the actual performance experienced by an individual customer, the reality can vary considerably. By combining intelligent route selection with service differentiation and SLA information for individual customers, the Elanti Network Optimization System can tailor path selection to meet on-going SLA requirements for certain highly valued customers. This can be particularly important in situations when a network outage has caused some SLAs to come close to their limits during a given billing cycle.

Congestion Prediction: When network optimization is performed on a periodic basis the system ensures optimal use of network resources for the measured traffic levels. A trade-off exists between the frequency of optimization and the data collection burden placed on network systems. However if optimization is not performed regularly enough there is the risk that rapid rises in traffic levels will lead to congestion between optimization cycles. By combining optimization with trend analysis the Elanti Network Optimization System can regulate its data collection frequency in anticipation of the emergence of hot spots.

The Elanti Network Optimization System enables service providers to offer service guarantees and reduce their capital and operational expenditures related to their IP MPLS core network.