1. Joint Call Admission Control and Adaptive Bandwidth Management Scheme to Enhance QoS in Heterogeneous Wireless Networks Olabisi E. Falowo and H. Anthony Chan Department of Electrical Engineering University of Cape Town

2. Presentation Overview   Introduction   Need for Joint Call Admission Control   Comparison of RAT selection methods   Proposed Scheme   System Model   Performance Evaluation

3. Admission Control   University- Students   Hospital- Patients   Hotel- Guests   Conference- Papers   Airline- Passengers   Communication network- Calls Ensure QoS Ensure Efficient utilization Limited resources

4. Call Admission Control   New call arrival   Handoff call arrival   Bearer modification A call admission control (CAC) algorithm decides whether or not a call be accepted into a resource- constrained network without violating the service commitment made to already admitted calls Generally, CAC algorithms are triggered by any of the following events:

5. Call Admission Control   CAC has been extensively studied in homogeneous wireless networks   For heterogeneous wireless networks, not many approaches to joint call admission (JCAC) problem are available in the literature   This work combines JCAC and adaptive bandwidth management to enhance QoS and System utilization

6. Need for JCAC Algorithm   Existing homogeneous CAC algorithms can only make call admission decisions   Problem of RAT selection does not occur in homogeneous networks RAT 1 RAT 2 RAT J Which network?

7. Need for JCAC Algorithm   In heterogeneous wireless network, there is need to make RAT selection decision in addition to call admission decision JCAC Call admission decision RAT selection decision Can the arriving call be admitted or not? Into which RAT should the call be admitted?

8. Need for JCAC JCAC in heterogeneous wireless network is necessary for the following reasons:   Efficient radio resource utilization - Increased revenue   Enhanced QoS provisioning – Improved users’ satisfaction   Overall service cost reduction   Overall network stability RAT 1 RAT 2 RAT J

9. Existing JCAC Algorithms   Initial RAT selection Algorithms   Fuzzy logic JCAC algorithms   RAT-specific JCAC algorithms

10. RAT Selection Methods   Random selection   Network load   Call service class   Service cost JCAC Call admission decision RAT selection decision

11. Comparison of the 3 JCAC Algorithms   Three JCAC algorithms are analyzed, evaluated and compared   These algorithms are: Load-based JCAC Service-class-based JCAC Random-selection-based JCAC

12. Algorithm Description   Load-based JCAC algorithm selects the least loaded RAT for an incoming call   Service-class-based JCAC selects a RAT for the incoming call based on its service class   Random-selection-based JCAC randomly selects a RAT for an incoming call JCAC Dropped Blocked Admitted RAT 2 RAT 1 RAT J

13. Comparison of Call Blocking Probabilities

14. Comparison of Call Dropping Probabilities

15. Conclusion   Load-based JCAC has the best QoS whereas random-selection based JCAC has the least QoS performance

16. Presentation Overview   Introduction   Need for Joint Call Admission Control   Comparison of RAT selection methods   Proposed Scheme   System Model   Performance Evaluation

17. + Load-Based JCAC Adaptive Bandwidth Management Proposed Adaptive JCAC Scheme = AJCAC scheme

18. Objectives of the AJCAC Scheme   Guarantee the QoS requirements of all accepted calls   Prioritize handoff calls over new calls   Improve system utilization   Enhance connection-level QoS   Enhance overall network stability Load-based JCAC Adaptive bandwidth management +

19. System Model   The heterogeneous network comprises J number of RATs   It supports K classes of calls   Each class-i call requires a value, b i,w, where b i,w belongs to the set B i = {b i,w } for i =1, 2,…,K and w =1, 2, …,W i   W i is the number of different bandwidth values that a class-i call can be allocated   For example, B 1 ={16, 32, 64} in Kbps b 1,min = b 1,1 =16, b 1,2 = 32, b 1,max = b 1,3 = 64

20. System Model RAT 1 RAT 2 RAT 3 Class-2 calls JRRM Class-1 calls Class-1 calls An example of heterogeneous network A two-class three- RAT heterogeneous network

21. Components of the Proposed AJCAC Scheme   Joint call admission controller   Bandwidth allocation Unit   Bandwidth adaptation Unit

22. JCAC DroppedBlocked Admitted RAT 2 RAT 1 RAT J JCAC Controller

23. Bandwidth Allocation Unit jBttttt jjkjijijj   ,),1(,,1,0... RAT 1 RAT 2 Access networks Available bandwidth t 01 t 11 t 02 t 12 B 2 =t 22 B 1 =t 21 RAT N t 1N B N =t 2N t 2N Fixed or dynamic

24. Bandwidth Adaptation Unit b i,min = b i,1 b i,max = b i,Ni b i,r =1<r<Ni For adaptive class-i calls For non-adaptive class-i calls b i,min =b i,max

25. State Space

26.   New call blocking probability   Handoff call dropping probability Performance Evaluation   Average system utilization

27. New Call Blocking Probability

28. Handoff Call Dropping Probability

29. Call Blocking/Dropping Probability

30. Normalized Average System Utilization

31. Conclusion   We investigate three RAT selection algorithms for heterogeneous wireless networks: load-based, service- class-based and random-selection-based JCAC   Results show that load-based JCAC has the best connection-level QoS performance whereas random- selection-based JCAC has the least QoS performance

32. Conclusion   We propose load-based JCAC and adaptive bandwidth management scheme for heterogeneous wireless networks   Results show that the proposed AJCAC scheme enhances connection-level QoS and overall system utilization   Future work includes optimization of the AJCAC scheme using linear programming technique

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