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3.1.- Traffic Engineering  

Performance objetives associated with Traffic Engineering (TE) are:
  1. Traffic oriented
     
      Traffic oriented objetives include aspects that enhance the QoS of traffic streams. These are:
     
     
    1. Minimization of packet loss.
       
    2. Minimization of delay.
       
    3. Maximization of throughput.
       
    4. Enforcement of service level agreements.
    		  
    		 
  2. Resource oriented
     
      Resource oriented objetives include aspects pertaining to the optimization of resource utilization. These are:
     
     
    1. Efficient management of network resources. It is very important that subsets of network resources do not become overutilized and congested while other subsets along alternate feasible paths remain underutilized.
       
    2. Recognize bandwidth as a crucial resource in contemporary networks; then a central function of TE is to efficiently manage bandwidth resources.
    		  
    		 
Minimizing congestion is a primary performance objetive. Congestion manifest under two scenarios:
  1. Network resources are insufficient of inadequate to accomodate offered load.
     
      This causality of congestion can be addressed as follows:
     
     
    1. Expansion of capacity, or
       
    2. Application of classical congestion control techniques, such as:
       
       
      1. Rate limiting.
         
      2. Window flow control.
         
      3. Router queue management.
         
      4. Scheduled-based control.
      		  

      or,
       

    3. Both of them.
    		  
    		 
  2. Traffic streams are inefficiently mapped onto available resources causing some resources to become over-utilized while other remain under-utilized.
     
      This causality of congestion problems, namely those resulting from inefficient resource allocation, can usually be addresssed through Traffic Engineering.

    In general, congestion resulting from inefficient resource allocation can be reduced by adopting load balancing policies. When congestion is minimized through efficient resource allocation, packet loss decreases, transit delay decreases, and aggregate throughput increases. Thereby the perception of network service quality experienced by end users becomes significantly enhanced.    		  
 
Traffic and Resource Control
 
   

 
In the TE process model, the Traffic Engineer, or a situable automaton, acts as the controller in an adaptive feedback control system. The Traffic Engineer formulates a control policy, observes the state of the network through the monitoring system, characterizes the traffic, and applies control actions to drive the network to a desire state, in accordance with the control policy. This can be accomplished reactively by taking action in response to the current state of the network, or pro-actively by using forecasting techniques to anticipate future trends and applying action to obviate the predicted undesirable future states.
Limitation of current IGP control mechanisms
IGP control capabilities are not adequate for TE. On the contrary, IGPs based on SPF algorithms contribute significantly to congestion problems in the AS. SPF algorithms generally optimize based on a simple additive metric and bandwidth availability and traffic characteristics are factors not considered in routing decisions. Consequently, congestion frequently occurs when:
  1. The shortest paths of multiple traffic streams converge on specific links or router interfaces, or
     
  2. A given traffic stream is routed through a link or router interface which does not have enough bandwidth to accomodate it.
 

 
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