1. Load Distribution and Channel Assignment in IEEE 802.11 Wireless Local Area Networks Ph.D. Dissertation Defense Presented by Mohamad Haidar Department of Applied Science George W. Donaghey College of Engineering and Information Technology, University of Arkansas at Little Rock November 9, 2007

2. 11/09/2007Ph.D. Defense2 Presentation Outline Introduction Introduction Wireless Local Area Networks (WLANs) Wireless Local Area Networks (WLANs) Access Points (APs) Congestion Access Points (APs) Congestion Channel Assignment Channel Assignment Related Work Related Work Contributions Contributions Problems Statements Problems Statements 1. Congestion Problem Proposed Solution Proposed Solution Problem Formulation Problem Formulation Algorithm Algorithm Numerical Analysis and Results Numerical Analysis and Results Simulations (OPNET) Simulations (OPNET)

3. 11/09/2007Ph.D. Defense3 Presentation Outline (Cont’d) 2. Channel Assignment Problem Proposed Solution Proposed Solution Problem Formulation Problem Formulation Algorithm Algorithm Numerical Analysis and Results Numerical Analysis and Results Simulations (OPNET) Simulations (OPNET) Dynamic Model Dynamic Model Scenario 1 (variable data rate) Scenario 1 (variable data rate) Scenario 2 (dynamic user distribution) Scenario 2 (dynamic user distribution) Conclusion Conclusion Future Work Future Work

4. 11/09/2007Ph.D. Defense4 Introduction Wireless Local Area Networks (WLANs) Wireless Local Area Networks (WLANs) Airports Airports Hotels Hotels Campuses Campuses WLANs are divided into 3 categories: WLANs are divided into 3 categories: IEEE 802.11a in the 5 GHz band (54 Mbps) IEEE 802.11a in the 5 GHz band (54 Mbps) IEEE 802.11b in the 2 GHz band (11 Mbps) IEEE 802.11b in the 2 GHz band (11 Mbps) IEEE 802.11g in the 2 GHz band (54 Mbps) IEEE 802.11g in the 2 GHz band (54 Mbps) Example of WLAN

5. 11/09/2007Ph.D. Defense5 Introduction (Cont’d) What is Access Point (AP) congestion? What is Access Point (AP) congestion? Some times referred to as “Hot Spot” Some times referred to as “Hot Spot” C AP = (R 1 + R 2+..+ R N )/BW C AP : Congestion at AP R : Data rate of a user connected to the AP BW: Bandwidth (11 Mbps for IEEE 802.11b) Channel Assignment Channel Assignment Minimize interference Minimize interference To improve QoS (less delay and higher throughput) To improve QoS (less delay and higher throughput) 3 non-overlapping channels in IEEE 802.11b/g (1, 6, and 11) 3 non-overlapping channels in IEEE 802.11b/g (1, 6, and 11) Frequency Spectrum for IEEE 802.11b/g

6. 11/09/2007Ph.D. Defense6 Limitation of Previous Research AP Placement AP Placement The main objective was to use a minimum number of APs for adequate coverage of the desired area. The main objective was to use a minimum number of APs for adequate coverage of the desired area. Did not account for channel assignment and/or load distribution. Did not account for channel assignment and/or load distribution. Channel Assignment Channel Assignment Based on minimizing co-channel interference. Based on minimizing co-channel interference. Limited to either minimizing total interference between APs or maximizing the sum of interference at a given AP. Limited to either minimizing total interference between APs or maximizing the sum of interference at a given AP. When integrated and applied simultaneously with AP placement, better results were achieved than dealing with them sequentially. When integrated and applied simultaneously with AP placement, better results were achieved than dealing with them sequentially. User distribution was not accounted for in the channel assignment. User distribution was not accounted for in the channel assignment.

7. 11/09/2007Ph.D. Defense7 (Cont’d) Load Balancing/Distribution Load Balancing/Distribution Balancing the load based on the number of active users Balancing the load based on the number of active users performs poorly because the data rate of users was not taken into consideration. performs poorly because the data rate of users was not taken into consideration. Minimizing the congestion at the most congested AP by redistributing users. Minimizing the congestion at the most congested AP by redistributing users. Improves the load ONLY at the MCAP. Improves the load ONLY at the MCAP. Load balanced agents installed at the APs that broadcast periodically their load. APs are either under-loaded, balanced, or overloaded. Load balanced agents installed at the APs that broadcast periodically their load. APs are either under-loaded, balanced, or overloaded. Static user distribution and no power management. Static user distribution and no power management. All APs involved should be equipped with the LBA software. All APs involved should be equipped with the LBA software. Cell breathing technique used to reduce the cell size to achieve a better load distribution. Cell breathing technique used to reduce the cell size to achieve a better load distribution. Connects to the next higher RSSI: is not always the best choice. Connects to the next higher RSSI: is not always the best choice. Static user distribution. Static user distribution. No channel assignment was considered. Interference was not accounted for. No channel assignment was considered. Interference was not accounted for.

8. Contributions of the Current Research A new Load Balancing scheme based on Power Management. As long as the received power exceeds a certain threshold, that AP is a potential for association. Channel Assignment based on Maximizing the SIR at the users. Users involved in the assignment of channels. Different user distributions will lead to different channel assignment.

9. 11/09/2007Ph.D. defense9 (Cont’d) Combining both load balancing based on power management and the channel assignment based on SIR: A Novel Scheme. Verified the performance predicted from optimization versus realistic OPNET-based network simulations: New contribution Developed a realistic dynamic model approach that accounts for variable users’ data rates and users’ behavior: New contribution

10. 11/09/2007Ph.D. Defense10 A New Heuristic Algorithm Initial Channel Assignment Users enter to network Load Balancing based on PM Re-Assign channels based on SIR Sort arriving users and departing users in ascending order in a list Check list ArriveDepart Add user to listRemove user from list Results End of list

11. 11/09/2007Ph.D. Defense11 1 st Problem AP Congestion Problem AP Congestion Problem Degrades network throughput Degrades network throughput Slowest station will make other stations wait longer. Slowest station will make other stations wait longer. Unfair load distribution over the network causes bottlenecks at hot spots. Unfair load distribution over the network causes bottlenecks at hot spots. Inefficient bandwidth utilization of the network. Inefficient bandwidth utilization of the network.

12. 11/09/2007Ph.D. Defense12 Proposed Solution Reduce congestion at the hot spots by decrementing the power transmitted by the Most Congested AP (MCAP) in discrete steps until one or more users can no longer associate with any AP or their data rate can no longer be accommodated. Reduce congestion at the hot spots by decrementing the power transmitted by the Most Congested AP (MCAP) in discrete steps until one or more users can no longer associate with any AP or their data rate can no longer be accommodated. The final transmitted power of each AP is set to the best balance index, , achieved. The final transmitted power of each AP is set to the best balance index, , achieved. Advantages: Advantages: Load is fairly distributed. Load is fairly distributed. Increase in data rate throughput per user. Increase in data rate throughput per user. Less adjacent and co-channel interference. Less adjacent and co-channel interference.

13. 11/09/2007Ph.D. Defense13 Problem Formulation MCAP NLIP formulation MCAP NLIP formulation for j= 1,…, M for i= 1,…,N

14. 11/09/2007Ph.D. Defense14 Algorithm Compute Received Signal Strength Indicator (RSSI) at each user. Compute Received Signal Strength Indicator (RSSI) at each user. Generate a binary matrix that assigns “1” if a user’s RSSI exceeds the threshold value or “0” otherwise. Generate a binary matrix that assigns “1” if a user’s RSSI exceeds the threshold value or “0” otherwise. Invoke LINGO to solve the NLIP. Invoke LINGO to solve the NLIP. Identify the MCAP and compute . Identify the MCAP and compute . Decrement its transmitted power by 1 dBm. Decrement its transmitted power by 1 dBm. Repeat previous steps until one or more user can no longer associate with an AP or their data rate can no longer be accommodated. Repeat previous steps until one or more user can no longer associate with an AP or their data rate can no longer be accommodated. Observe the power levels at each AP and the best user’s association at the best . Observe the power levels at each AP and the best user’s association at the best .

15. 11/09/2007Ph.D. Defense15 Numerical Analysis and Results User Number AP1AP2AP3AP4 11110 20010 30001 40001 51111 61100 70100 80011 90010 100101 Receiver Sensitivity at the user is -90 dBm Receiver Sensitivity at the user is -90 dBm Transmitted Power at each AP is 20 dbm Transmitted Power at each AP is 20 dbm 4 1 2 User-AP candidate association

16. 11/09/2007Ph.D. Defense16 Numerical Analysis and Results (Cont’d) Service Area Map Traffic is randomly generated between 1 Mbps and 6 Mbps for each user Traffic is randomly generated between 1 Mbps and 6 Mbps for each user User Number Traffic (Kbps) 11752 25698 34265 41994 53558 63176 75319 81559 92982 102263 Data rate of users

17. 11/09/2007Ph.D. Defense17 Numerical Analysis and Results Each user is associated to one and ONLY one AP. Each user is associated to one and ONLY one AP. User Number AP1AP2AP3AP4 10100 20010 30001 40001 50100 61000 70100 80001 90010 100100 1 1 1 Optimal user-AP association

18. 11/09/2007Ph.D. Defense18 Numerical Analysis and Results (Cont’d) Initial Congestion factor: (No Power Mgmt) Congestion factor solution according to [2] Congestion factor with Power Mgmt AP1 0.63190.52340.3793 AP2 0.4100 0.3617 AP3 0.2117 0.3167 AP4 0.20260.31100.3985  81.15%90.84%99.31% Congestion Factor comparison Load is distributed fairly among APs. Load is distributed fairly among APs. Final transmitted power levels at each AP is: 12 dBm, 18 dBm, 20 dBm and 17 dBm, respectively. Final transmitted power levels at each AP is: 12 dBm, 18 dBm, 20 dBm and 17 dBm, respectively.

19. 11/09/2007Ph.D. Defense19 Numerical Analysis and Results (Cont’d) Different radii sizes after power adjustment Different radii sizes after power adjustment Users do NOT always associate to the closest AP. Users do NOT always associate to the closest AP. Service area map after Power Mgmt

20. 11/09/2007 *published at IEEE Sarnoff Conference May'0720 Numerical Analysis and Results (Cont’d) 4 APs9 APs 16 APs

21. 11/09/2007*Not published yet21 Simulation Scenarios (OPNET) Unbalanced Load v.s. Balanced Load Unbalanced Load v.s. Balanced Load 20 dBm Transmitted power 20 dBm Transmitted power -90 dBm Receiver threshold -90 dBm Receiver threshold FTP clients and APs FTP clients and APs are stationary File of 50 Kbytes uploaded continuously. File of 50 Kbytes uploaded continuously. Simulation time is 40 mins Simulation time is 40 mins Steady state after 15 mins Steady state after 15 mins WLAN scenario in OPNET, 4 APs and 20 Users

22. 11/09/2007Ph.D. Defense22 Simulation Results (OPNET) Overall load on the network was reduced by “load balancing”  Reduced overall congestion Overall load on the network was reduced by “load balancing”  Reduced overall congestion After applying load balancing, client 9 associated with BSS2, and improved its throughput. After applying load balancing, client 9 associated with BSS2, and improved its throughput. Overall load at the network Throughput of FTP client 9

23. 11/09/2007Ph.D. Defense23 2 nd Problem Channel Assignment Channel Assignment Careful consideration must be given to assigning channels to APs. Otherwise the followings may result: Careful consideration must be given to assigning channels to APs. Otherwise the followings may result: High interference between APs’ overlapping zones. High interference between APs’ overlapping zones. Users in the overlapping region of two or more interfering APs will suffer: Users in the overlapping region of two or more interfering APs will suffer: Delay Delay Low data rates Low data rates This is due to the huge increased requests by the user in retransmitting damaged/unsuccessful packets.

24. 11/09/2007Ph.D. Defense24 Proposed Solution Two folds: Two folds: Assign channels at the design stage (no users) with the objective to minimize the total sum of interference between neighboring APs. Assign channels at the design stage (no users) with the objective to minimize the total sum of interference between neighboring APs. Re-Assign channels when users exist on the network. Re-Assign channels when users exist on the network.

25. 11/09/2007*Formulation not yet published25 Problem Formulation (initial stage) Objective Objective Subject to Subject to i = 1, …, M j = 1,…, M i  j

26. 11/09/2007Ph.D. Defense26 Problem Formulation (with users) Objective Objective Subject to Subject to

27. 11/09/2007Ph.D. Defense27 Heuristic Algorithm Apply initial channel assignment Apply initial channel assignment Users enter the network Users enter the network Apply load balancing algorithm based on power management. Apply load balancing algorithm based on power management. Save final transmitted powers at APs. Save final transmitted powers at APs. Re-compute received signal at users. Re-compute received signal at users. Compute SIR. Compute SIR. Apply Channel Assignment algorithm based on SIR. Apply Channel Assignment algorithm based on SIR.

28. 11/09/2007Ph.D. Defense28 Numerical Analysis and Results Initial Approach (based on min AP interference) Initial Approach (based on min AP interference) AP NumberFCA: Equal Power FCA: Power Management AP117 AP281 AP3311 AP4113 Interference (dB)-21.17-22.02 Scenario 1: 4 APs (12, 18, 20, 17 (dBm)) AP NumberFCA: Equal Power FCA: Power Management AP111 AP211 AP387 AP445 AP5112 AP6110 Interference (dB)-19.15-25.49 Scenario2: 6 APS (16, 16, 11, 6, 6, 1 (dBm)) AP3AP2 AP1AP4 4 APs AP1AP4AP5 AP2AP3AP6 6 APs 4% 33%

29. 11/09/2007 * Published at IEEE PIMRC conference Jun'0729 Numerical Analysis and Results Initial Approach (Cont’d) Initial Approach (Cont’d) Scenario 3: 9 APs (4, 12, 20, 16, 20, 16, 17, 8, 19 (dBm)) AP NumberFCA: Equal Power FCA: Power Management AP111 AP241 AP386 AP411 AP51110 AP641 AP711 AP811 AP911 Interference (dB)-17-19.86 9 APs AP7AP8AP9 AP6AP3AP2 AP1AP4AP5 * Published at IEEE ICSPC conference Nov’07 17%

30. 11/09/2007Ph.D. Defense30 Numerical Analysis and Results Second Approach (based on max SIR at users) Second Approach (based on max SIR at users) Two special cases: Two special cases: Many users in the overlapping zone Many users in the overlapping zone Users are not in the overlapping zone Users are not in the overlapping zone

31. 11/09/2007 *Submitted to IEEE WCNC conference Apr'0831 Numerical Analysis and Results AP Number FCA: No Users (minimize interference between APs) FCA: With Users (Maximize SIR at the Users) AP116 AP2811 AP332 AP4111 Avg. SIR (dB)6.51 7.66 AP NumberFCA: No usersFCA: with users AP1112 AP2111 AP386 AP446 AP5118 AP611 Avg. SIR (dB)4.224.47 AP NumberFCA: No usersFCA: With Users AP1116 AP241 AP3811 AP418 AP511 AP644 AP7116 AP818 AP911 Avg. SIR (dB)0.442.86 Scenario 1: 4 APs (12, 18, 20, 17 (dBm)) Scenario2: 6 APS (16, 16, 11, 6, 6, 1 (dBm)) Scenario 3: 9 APs (4, 12, 20, 16, 20, 16, 17, 8, 19 (dBm)) 17%6% 540%

32. 11/09/2007Ph.D. Defense32 Simulation Scenarios (OPNET) 4-AP WLAN 4-AP WLAN 4-AP WLAN Scenario 1 Scenario 2 Scenario 3 Scenario 4 AP1 1116 AP2 26811 AP3 3132 AP4 411 1 Summary of the 4 Scenarios

33. 11/09/2007*Results not yet published33 Simulation Results (OPNET) Same assumptions from the load balancing scenarios apply EXCEPT for the channel assignment. Same assumptions from the load balancing scenarios apply EXCEPT for the channel assignment. Zoomed in ViewOverall Upload Response TimeOverall Throughput

34. 11/09/2007Ph.D. Defense34 Dynamic Model Background Background No such application of a dynamic user behavior model on a full scale dynamic network. No such application of a dynamic user behavior model on a full scale dynamic network. Published work related to user behavior reported the user behavior through monitoring network traffic and behavior for long periods of time (10 months or more). Published work related to user behavior reported the user behavior through monitoring network traffic and behavior for long periods of time (10 months or more). Such a model is significant for future researchers in the WLAN field or industry where load distribution and channel assignment algorithms can be implemented and tested on a dynamic scale. Such a model is significant for future researchers in the WLAN field or industry where load distribution and channel assignment algorithms can be implemented and tested on a dynamic scale.

35. 11/09/2007Ph.D. Defense35 Dynamic Scenario 1 Scenario 1: Varying data rate with time Scenario 1: Varying data rate with time 4 APs and 20 users. 4 APs and 20 users. Data rate of users vary with time according to a normal distribution (  = 4 Mbps,  = 2 Mbps). Data rate of users vary with time according to a normal distribution (  = 4 Mbps,  = 2 Mbps). Data rate is captured every 5 minutes. Data rate is captured every 5 minutes. All users are continuously active. All users are continuously active. All APs and users are stationary. All APs and users are stationary. Default AP transmitted power is 20 dBm. Default AP transmitted power is 20 dBm. Receiver’s threshold is -90 dBm. Receiver’s threshold is -90 dBm. Simulation period is 2 hours. Simulation period is 2 hours.

36. 11/09/2007*Results not yet published36 Numerical Analysis and Results Initial user-AP association Initial CFFinal CF Final transmitted power (dBm) Final FCA AP10.25630.2464161 AP20.06690.2721206 AP30.37520.25021211 AP40.34450.274111  82.49%99.77% Iteration 1 Initial CFFinal CF Final transmitted power (dBm) Final FCA AP10.24540.3023201 AP20.12750.3979166 AP30.72400.396856 AP40.3703 1811  72.94%98.89% Last iteration Final user-AP association

37. 11/09/2007Ph.D. Defense37 Dynamic Scenario 2 Scenario 2: Dynamic User Behavior Scenario 2: Dynamic User Behavior Same assumptions as before apply EXCEPT that the data rate now is fixed over simulation time. Same assumptions as before apply EXCEPT that the data rate now is fixed over simulation time. Users arrive to the WLAN according to a Poisson distribution with an arrival rate of. Users arrive to the WLAN according to a Poisson distribution with an arrival rate of. varies with time. However, in this scenario has a constant value over the simulation period (2 hours). varies with time. However, in this scenario has a constant value over the simulation period (2 hours).

38. 11/09/2007 Ph.D. Defense 38 Dynamic Scenario 2 (Cont’d) Session lengths of each user is characterized by a Bi-Pareto distribution. Session lengths of each user is characterized by a Bi-Pareto distribution. When a user’s session is over, the user is assumed as either no longer active or left the network. When a user’s session is over, the user is assumed as either no longer active or left the network. i.e. the user no longer has a data rate  it does not constitute any load at its AP. i.e. the user no longer has a data rate  it does not constitute any load at its AP.

39. 11/09/2007Ph.D. Defense39 Numerical Analysis and Results = 4 = 4 User NumberArrival times(hrs) Departure Time(hrs) 210.10 220.15 230.70 240.76 251.13 261.42 101.62 271.66 31.93 281.87 292.00 Arrival and Departure time Table 4 APs, 20 Users

40. 11/09/2007Ph.D. Defense40 Numerical Analysis and Results (Cont’d) FCA: Arrive 4 FCA: Arrive 5 FCA: Arrive 6 FCA: Leave 1 Final Tx Power (dBm): Arrive 4 Final Tx Power (dBm: Arrive 5 Final Tx Power (dBm): Arrive 6 Final Tx Power (dBm): Leave 1 AP1111117201518 AP2666611141918 AP311 1251912 AP466111513  98.75%99.14%96.89%99.62% Avg. SIR (dB) 6.466.276.086.05 FCA and Load Balancing results

41. 11/09/2007*Results not yet published41 Numerical Analysis and Results (Cont’d) FCA and Load Balancing results FCA: Arrive 7 FCA: Leave 2 FCA: Arrive 8 FCA: Arrive 9 Final Tx Power (dBm): Arrive 7 Final Tx Power (dBm): Leave 2 Final Tx Power (dBm): Arrive 8 Final Tx Power (dBm): Arrive 9 AP1111120192018 AP2666618171518 AP311 8151615 AP466111018119  99.01%97.69%98.92%99.42% Total SIR (dB) 5.925.945.775.71

42. 11/09/2007Ph.D. Defense42 Numerical Analysis and Results (Cont’d) FCA and Load Balancing results -- Added users -- Removed users -- Existing users

43. 11/09/2007Ph.D. Defense43 Conclusion A new load balancing algorithm based on power management was developed. A new load balancing algorithm based on power management was developed. A new channel assignment algorithm based on maximizing SIR was developed. A new channel assignment algorithm based on maximizing SIR was developed. Results were validated using OPNET simulation to show the effectiveness of the developed algorithms. Results were validated using OPNET simulation to show the effectiveness of the developed algorithms. Dynamic data rate and user behavior were introduced to verify the ability of the developed models to adapt to these dynamic behaviors. Dynamic data rate and user behavior were introduced to verify the ability of the developed models to adapt to these dynamic behaviors.

44. 11/09/2007Ph.D. Defense44 Future Work Extension of the dynamic model to combine both variable data rate and users’ behavior. Extension of the dynamic model to combine both variable data rate and users’ behavior. Application of this work to WiMAX (IEEE 802.16). Application of this work to WiMAX (IEEE 802.16). Integration of smart antenna technology at the AP. Integration of smart antenna technology at the AP. Expand developed work to larger WLANs. Expand developed work to larger WLANs.

45. 11/09/2007Ph.D. Defense45 Special Thanks Ph.D. Advising Committee: Ph.D. Advising Committee: Dr.. Hussain Al-Rizzo (Advisor) Dr.. Hussain Al-Rizzo (Advisor) Dr. Robert Akl Dr. Robert Akl Dr. Yupo Chan Dr. Yupo Chan Dr. Hassan El-Salloukh Dr. Hassan El-Salloukh Dr. Seshadri Mohan Dr. Seshadri Mohan Dr. Haydar Alshukri Dr. Haydar Alshukri Ph.D. Candidates Ph.D. Candidates Rami Adada Rami Adada Rabindra Ghimire Rabindra Ghimire Graduate Student Graduate Student TJ Calvin TJ Calvin Network Administrator Network Administrator Greg Browning OPNET Technical Support OPNET Technical Support LINGO Technical Support LINGO Technical Support