Performance Analysis of Grouping Strategy for Dense IEEE Networks

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Performance Analysis of Grouping Strategy for Dense IEEE 802.

1 Performance Analysis of Grouping Strategy for Dense IEEE Networks Lei Zheng *, Lin Cai *, Jianping Pan *, and Minming Ni *+ * University of Victoria, Victoria, BC, Canada + Beijing Jiaotong University, Beijing, China Dec. 10, 2013

2 Outline Motivations IEEE ah: RAW-based Media Access Method Performance Model and Analysis Performance Evaluation Future Work 2

3 The key issue: communication efficiency MAC efficiency Motivations Packet transmission (without collision) TXOP CW (variable) Actual data up to 64 subframes Max A-MPDU size ~ 1MB DIFS RTS CTS A-MPDU BA A-MPDU BA Packet transmission pattern with collision Overhead (OH) Actual data OH Collision Actual data OH [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13,

4 The key issue: communication efficiency MAC efficiency Motivations MAC efficiency = MAC throughput PHY rate Packet transmission (without collision) TXOP CW (variable) Actual data up to 64 subframes Max A-MPDU size ~ 1MB DIFS RTS CTS A-MPDU BA A-MPDU BA Packet transmission pattern with collision Overhead (OH) Actual data OH Collision Actual data OH [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13,

5 The key issue: communication efficiency MAC efficiency Motivations MAC efficiency = MAC throughput PHY rate Packet transmission (without collision) The PHY data rate can be up to 6 Gbps (IEEE ac) TXOP CW (variable) Actual data up to 64 subframes Max A-MPDU size ~ 1MB DIFS RTS CTS A-MPDU BA A-MPDU BA Packet transmission pattern with collision Overhead (OH) Actual data OH Collision Actual data OH [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13,

6 The key issue: communication efficiency MAC efficiency MAC efficiency = Motivations MAC throughput PHY rate Packet transmission (without collision) TXOP Challenge: How to imove the MAC efficiency? The PHY data rate can be up to 6 Gbps (IEEE ac) CW (variable) Actual data up to 64 subframes Max A-MPDU size ~ 1MB DIFS RTS CTS A-MPDU BA A-MPDU BA Packet transmission pattern with collision Overhead (OH) Actual data OH Collision Actual data OH [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13,

7 Motivations The key issue: communication efficiency MAC efficiency Several options to imove the MAC efficiency longer TXOP, fewer idle slots (back off), fewer collisions Challenge: How to imove the MAC efficiency? 3

8 Motivations The key issue: communication efficiency MAC efficiency Several options to imove the MAC efficiency longer TXOP, fewer idle slots (back off), fewer collisions The networks are becoming denser e.g., wireless office, shopping mall, airport waiting area/lounge, stadium, lecture hall Challenge: How to imove the MAC efficiency? 3

9 Motivations The key issue: communication efficiency MAC efficiency Several options to imove the MAC efficiency longer TXOP, fewer idle slots (back off), fewer collisions The networks are becoming denser e.g., wireless office, shopping mall, airport waiting area/lounge, stadium, lecture hall Challenge: How to imove the MAC efficiency in dense networks? 3

10 Motivations The key issue: communication efficiency MAC efficiency Several options to imove the MAC efficiency longer TXOP, fewer idle slots (back off), fewer collisions The networks are becoming denser e.g., wireless office, shopping mall, airport waiting area/lounge, stadium, lecture hall In dense networks, it has been observed that The collision obability as the no. of STAs The idle intervals between TXOP as the no. of STAs Challenge: How to imove the MAC efficiency in dense networks? [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13, 2013 [1] 3

11 Motivations The key issue: communication efficiency MAC efficiency Several options to imove the MAC efficiency longer TXOP, fewer idle slots (back off), fewer collisions The networks are becoming denser e.g., wireless office, shopping mall, airport waiting area/lounge, stadium, lecture hall In dense networks, it has been observed that The collision obability as the no. of STAs The idle intervals between TXOP as the no. of STAs Challenge: How to imove the How to reduce the collisions MAC efficiency in dense networks? in dense networks? [1] IEEE /0505r0, MAC Efficiency Analysis for HEW SG, May 13, 2013 [1] 3

12 B eacon B eacon IEEE ah: RAW-based Media Access Method Restricted Access Window (RAW) T im e Structure of RAW A Restricted Access Window (RAW) is further divided in RAW slots. How to know the RAW slot assignment STA wakes up at TBTT and it listens to a Beacon frame that indicates the slot duration for each Restricted Access Window (RAW) Slot duration for each RAW may be different STA determines its channel access slot assigned by AP 4

13 IEEE ah: RAW-based Media Access Method Restricted Access Window (RAW) How to access the RAW STA may sleep before its channel access slot. STA shall start to access the channel at the slot boundary of its channel access slot based on EDCA. AP indicates a cross boundary option applied in each RAW: If it is set to FALSE, a TXOP or transmission within a RAW slot shall not extend across a slot boundary RAW AP STA-a STA-b Doze State Beacon Active State RAW Slot 1 RAW Slot TXOP Doze State Active State TXOP RAW Slot 3 When cross boundary is set to FALSE When cross boundary is set to TRUE 5

14 IEEE ah: RAW-based Media Access Method Restricted Access Window (RAW) How to access the RAW STA may sleep before its channel access slot. STA shall start to access the channel at the slot boundary of its channel access slot based on EDCA. AP indicates a cross boundary option applied in each RAW: If it is set to FALSE, a TXOP or transmission within a RAW slot shall not extend across a slot boundary RAW AP Beacon RAW Slot 1 RAW Slot 2 RAW Slot 3 When cross boundary is set to FALSE STA-a Doze State Active State TXOP Focusing: the FALSE cross boundary option 5

15 Performance Model and Analysis System model Topology: one-hop network without hidden terminal Traffic model: saturated traffic, identical packet size Transmission model: otocol model Objective: RAW-based media access method with FALSE cross boundary option (termed it as Group-Synch DCF, GSDCF) T f : superframe ~ RAW T c,k : CAP (channel access period) ~ RAW slot T a : access time T h : holding time T g : guard time Ø : duration of a TXOP 6

Performance Model and Analysis System model Topology: one-hop network without hidden terminal Traffic model: saturated traffic, identical packet size Transmission model: otocol model Objective:

16 Performance Model and Analysis System model Topology: one-hop network without hidden terminal Traffic model: saturated traffic, identical packet size Transmission model: otocol model Objective: RAW-based media access method with FALSE cross boundary option (termed it as Group-Synch DCF, GSDCF) T f : superframe ~ RAW T c,k : CAP (channel access period) ~ RAW slot T a : access time T h : holding time T g : guard time Ø : duration of a TXOP Interest: The impact of the RAW slot handover on throughput. 6

17 Performance Model and Analysis The impact of the RAW slot handover on throughput It was found that the throughput fluctuates with the duration of CAPs, and such a phenomena can t be tracked by evious models. 7

18 Performance Model and Analysis Analytical model Previously, Bianchi s Markov chain model Mean value analysis [3] [2] [2] G. Bianchi, Performance analysis of the IEEE distributed coordination function, IEEE JSAC, vol. 18, no. 3, pp , [3] Y. C. Tay and K. C. Chua, A capacity analysis for the IEEE MAC otocol, Wirel. Netw., vol. 7, no. 2, pp , Mar

19 Performance Model and Analysis Analytical model Proposed 9

20 Performance Model and Analysis Analytical model Proposed Fig. 1 The PMF of idle intervals between transactions (Apoximated by exponential distribution) 9

Performance Evaluation Simulation settings [5,6] Grouping scheme: assuming all STAs uniformly assigned to K groups (K CAPs), named as uni-gsdcf [5] IEEE 802.

21 Performance Evaluation Simulation settings [5,6] Grouping scheme: assuming all STAs uniformly assigned to K groups (K CAPs), named as uni-gsdcf [5] IEEE ah Task Group, 11/1137r14 specification framework for TGah. [Online]. available: update.htm [6] Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 8: IEEE Wireless Network Management, IEEE Std v, Sep

22 Performance Evaluation Model validation Fig. 2 Expected number of transactions in a CAP Fig. 3 Normalized throughput (normalized to the channel data rate) 11

23 Performance Evaluation Exploring optimal grouping configurations Fig. 3 The optimized throughput using 2 groups, N=20, superframe duration 30 ms and 100 ms uni-gsdcf: the CAP is allocated to groups opt-gsdcf: in oportion to the groups size an optimal combination of group sizes and CAP sizes given K groups; Opt*-GSDCF: based on opt-gsdcf, further tune the superframe size a little bit. 12

24 Performance Evaluation Exploring optimal grouping configurations Gain >50%! Fig. 3 The optimized throughput Guidelines: using 2 groups, N=20, superframe 1. Grouping duration can 30 ms help and imove 100 ms the throughput significantly in dense uni-gsdcf: the CAP is allocated to groups networks; opt-gsdcf: in oportion to the groups size an optimal combination of group sizes and CAP sizes given K groups; Opt*-GSDCF: based on opt-gsdcf, further tune the superframe size a little bit.

25 Performance Evaluation Exploring optimal grouping configurations Gain >50%! Fig. 3 The optimized throughput Guidelines: using 2 groups, N=20, superframe 1. Grouping duration can 30 ms help and imove 100 ms the throughput significantly in dense uni-gsdcf: the CAP is allocated to groups networks; in oportion to the groups size 2. Group sizes should be as close as possible; opt-gsdcf: an optimal combination of group sizes and CAP sizes given K groups; Opt*-GSDCF: based on opt-gsdcf, further tune the superframe size a little bit.

Performance Evaluation Exploring optimal grouping configurations Gain >50%! Fig. 3 The optimized throughput Guidelines: using 2 groups, N=20, superframe 1.

26 Performance Evaluation Exploring optimal grouping configurations Gain >50%! Fig. 3 The optimized throughput Guidelines: using 2 groups, N=20, superframe 1. Grouping duration can 30 ms help and imove 100 ms the throughput significantly in dense uni-gsdcf: the CAP is allocated to groups networks; in oportion to the groups size 2. Group sizes should be as close as possible; opt-gsdcf: 3. A large group number does not mean high throughput; an optimal combination of group sizes and CAP sizes given K groups; Opt*-GSDCF: based on opt-gsdcf, further tune the superframe size a little bit.

27 Performance Evaluation Exploring optimal grouping configurations Gain >50%! Fig. 3 The optimized throughput Guidelines: using 2 groups, N=20, superframe 1. Grouping duration can 30 ms help and imove 100 ms the throughput significantly in dense uni-gsdcf: the CAP is allocated to groups networks; in oportion to the groups size 2. Group sizes should be as close as possible; opt-gsdcf: 3. A large group number does not mean high given throughput; K groups; 4. The super-frame size, CAP sizes, group Opt*-GSDCF: sizes based and on opt-gsdcf, group number should be tuned simultaneously to achieve optimal further efficiency. tune the superframe size a little bit. an optimal combination of group sizes and CAP sizes

28 Conclusions We have oposed a novel analytical framework for IEEE ah RAW-based media access method with FALSE cross boundary option. It has been demonstrated that It is omising in alleviating the channel contention in a dense IEEE network (50% or more throughput gain with 256 STAs). It may experience throughput loss due to RAW slot handover. The grouping configuration, e.g., group size, the RAW slot durations, should be set carefully to fully exploit the advantage of the RAWbased media access method. 13

29 Future Work The RAW-based media access method with TRUE cross boundary option The grouping schemes and their impact Centralized vs. decentralized grouping scheme Model and performance analysis Unsaturated traffic Dynamic networks: hybrid packet sizes, multiple data rates, etc.. 14

30 Thanks for your attention! & We d like to hear your comments! zhengl@ece.uvic.ca 15

Performance Analysis of Grouping Strategy for Dense IEEE Networks

Performance Analysis of Grouping Strategy for Dense IEEE 802.11 Networks Lei Zheng, Lin Cai, Jianping Pan, and Minming Ni University of Victoria, Victoria, BC, Canada Beijing Jiaotong University, Beijing,