Publication | Closed Access
Adaptive Modular Fuzzy-based Handover Decision System for Heterogeneous Wireless Networks
13
Citations
34
References
2013
Year
EngineeringFuzzy ModelingIntelligent SystemsSystems EngineeringFuzzy OptimizationMobility ManagementMulti-access NetworkModular DesignFuzzy LogicFuzzy ComputingHeterogeneous Wireless NetworksFuzzy RulesComputer EngineeringComputer ScienceWireless AccessEdge ComputingFuzzy MathematicsFuzzy Expert SystemFuzzy Ru LesHeterogeneous NetworkMobility Protocol
Future generation wireless networks will demand more intelligent and adaptive handover decision mechanisms to fulfil users' expectations in terms of seamless mobility over extensive area, min imu m price, high data rate, adequate QoS provision and so on. For such a demanding networking environment the handover decision system (HDS) need to be highly intelligent. Fu zzy logic appears to be one of the methods that can be employed to enhance HDS intelligence. However, most existing fuzzy-based HDS designs proposed in the literature are monolithic, i.e. based on a single fu zzy engine. In view of the growing demand for real-t ime applications, it is becoming necessary to include a relatively large number of decision parameters (especially QoS-related) in the handover decision process. However, an increasing nu mber of decision parameters give rise to generating a very large nu mber of fuzzy ru les. This in turn increases computational comp lexity and requires significantly long algorith m execution time, which may not be acceptable for real-t ime applicat ions. Furthermore, if the same fuzzy membership functions (FMFs) and fu zzy ru les are used for all traffic types (e.g. Vo IP, v ideo streaming etc), the HDS may not give the overall best decision results, as each traffic type has a different set of QoS requirements. In order to address the above issues, we are proposing a modular design concept to deal with the algorith m execution time and an adaptive mechanis m to select FMFs and fuzzy rules which are best suited to the incoming traffic. The results show that the modular design significantly reduces the algorithm execution time while an adaptive mechanis m imp roves the network selection performance considerably.
| Year | Citations | |
|---|---|---|
Page 1
Page 1