An intelligent-agent approach for managing congestion in W-CDMA networks
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Resource Management is a crucial aspect in the next generation cellular networks
since the use of W-CDMA technology gives an inherent flexibility in managing the
system capacity. The concept of a “Service Level Agreement” (SLA) also plays a
very important role as it is the means to guarantee the quality of service provided to
the customers in response to the level of service to which they have subscribed.
Hence there is a need to introduce effective SLA-based policies as part of the radio
resource management.
This work proposes the application of intelligent agents in SLA-based control in
resource management, especially when congestion occurs. The work demonstrates the
ability of intelligent agents in improving and maintaining the quality of service to
meet the required SLA as the congestion occurs.
A particularly novel aspect of this work is the use of learning (here Case Based
Reasoning) to predict the control strategies to be imposed. As the system environment
changes, the most suitable policy will be implemented. When congestion occurs, the
system either proposes the solution by recalling from experience (if the event is
similar to what has been previously solved) or recalculates the solution from its
knowledge (if the event is new). With this approach, the system performance will be
monitored at all times and a suitable policy can be immediately applied as the system
environment changes, resulting in maintaining the system quality of service.
Authors
Chantaraskul, SoamsiriCollections
- Theses [3833]