January 2006 doc.: IEEE 802.11-06/11-06-0364-00-000s March 2006 EDCA Parameters Selection to Optimally Provide QoS in IEEE 802.11s Mesh WLANs Date: 2006-03-07 Authors: Notice: This document has been prepared to assist IEEE 802.11. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor grants a free, irrevocable license to the IEEE to incorporate material contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE’s name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE’s sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that this contribution may be made public by IEEE 802.11. Patent Policy and Procedures: The contributor is familiar with the IEEE 802 Patent Policy and Procedures <http:// ieee802.org/guides/bylaws/sb-bylaws.pdf>, including the statement "IEEE standards may include the known use of patent(s), including patent applications, provided the IEEE receives assurance from the patent holder or applicant with respect to patents essential for compliance with both mandatory and optional portions of the standard." Early disclosure to the Working Group of patent information that might be relevant to the standard is essential to reduce the possibility for delays in the development process and increase the likelihood that the draft publication will be approved for publication. Please notify the Chair <stuart.kerry@philips.com> as early as possible, in written or electronic form, if patented technology (or technology under patent application) might be incorporated into a draft standard being developed within the IEEE 802.11 Working Group. If you have questions, contact the IEEE Patent Committee Administrator at <patcom@ieee.org>. Chunyu Hu, UIUC Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Challenges in IEEE 802.11s Mesh Networks March 2006 Challenges in IEEE 802.11s Mesh Networks Challenges Lack of central coordinators – Each node can be a coordinator Multi-hop environments For Absolute QoS Guarantees Need to determine the optimal route and perform a hop-by-hop reservation For Prioritized QoS Need to maximize throughput and maintain pre-specified throughput ratios between different flows or classes, need to compute optimal CW for each class Optimal CWj depends (1 or multi)-hop neighboring information: such as number of nodes in each class and their traffic characteristics Chunyu Hu, UIUC

MAC layer issues in 802.11s Mesh Networks March 2006 MAC layer issues in 802.11s Mesh Networks EDCA will be the basis of IEEE 802.11s MAC1 EDCA will be used to provide prioritized QoS Nodes (say i,j) forwarding their traffic to a particular node, (say x) will have to receive the EDCA parameters from node x If the forwarding node (x) is allowed to set parameters to individual flows then it can provide absolute QoS for a particular flow Enable congestion control1 Simple hop by hop congestion control enabled at each Mesh Point (MP) Need to curtail a flow if it has violated its QoS agreements Because the forwarding node has reduced available channel bandwidth, it may ask all nodes that forward traffic to it to reduce their rates. (By form of signaling newer EDCA parameters) 1DCN: IEEE802.11-06/0329r0: Joint SEE-Mesh/Wi-Mesh Proposal to 802.11 TGs Overview Chunyu Hu, UIUC

Example WLAN Mesh Assume a simple clustering structure January 2006 doc.: IEEE 802.11-06/11-06-0364-00-000s March 2006 Example WLAN Mesh Assume a simple clustering structure Mesh Portals (MPs) are at level-0 Level-i MP nodes coordinate level-(i+1) MP nodes A level-i MP node estimates the number of flows in each class by communicating with its parent and sister nodes, and by monitoring its children nodes The level-i MP node computes the optimal CW/AIFS for each traffic class and broadcasts them to its children nodes Level-(i+1) MP nodes use the designated CW/AIFS to access the channel MP1 MP2 MP21 MP222 MP211 MP212 Now let us understand the performance of IEEE 802.11e EDCA …… Chunyu Hu, UIUC Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Overview of EDCA: Enhanced Distributed Control Access March 2006 Overview of EDCA: Enhanced Distributed Control Access 802.11 DCF enhanced with QoS Figure 1. Four access categories with different QoS parameters Table 1. Default EDCA Parameters aCWmin = 32, aCWmax = 1024. AIFS = SIFS + AIFSN*aSlotTime Chunyu Hu, UIUC

Key parameters in EDCA Contention window size (CW) March 2006 Key parameters in EDCA Contention window size (CW) Determine the probability of gaining the channel access Arbitrary inter-frame space (AIFS) Determines the duration of occupying the channel Transmission opportunity limit (TXOP) Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

The system in view of the channel January 2006 doc.: IEEE 802.11-06/11-06-0364-00-000s March 2006 The system in view of the channel Figure 3. Following every busy period, the slots can be divided into contention zones. aj = AIFSNj + 1. AIFS = SIFS + AIFSN * aSlotTime a1 = 3, a2 = 5, a3 = 8 3 5 8 1 Contention zone j: Consecutive slots in which only the first j classes are eligible to access the channel Numbering the slot from the first slot after a busy period + SIFS, the j-th contention zone starts from the aj-th idle slot and ends at the (aj+1-1)-th idle slot. Chunyu Hu, UIUC Chunyu Hu, UIUC

Describe the channel state transition March 2006 Describe the channel state transition Success states Collision states Idle states Figure 4. The discrete Markov chain that describes the channel state transition Assume attempt probability of each class, j, are known at this step. The stable probabilities can be readily derived. Details (see the Infocom2006 paper at http://lion.cs.uiuc.edu/~chunyuhu.) Chunyu Hu, UIUC

Other elements in the model March 2006 Other elements in the model Assumptions: Saturation condition: every node is back-logged Every node has the same view of the channel state An iterative algorithm to obtain average contention window size, and attempt probabilities j Given [CWMIN(j), CWMAX(j)] and Lj Derive the performance, e.g., the throughput Expected slot length Throughput of each class Packet payload Success probability of class j Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Simulation Setup Tools: PHY/MAC parameters: Traffic: March 2006 Simulation Setup Tools: Simulator: ns-2, extended with EDCA Analytical results: use Matlab PHY/MAC parameters: Data rate 200 Mbps (all throughput results are normalized to it) Slot time: 8 sec SIFS: 10 sec Retry times limit: 7 Traffic: All classes have the same number of nodes All nodes transmit packets to a sink node CBR (Constant-Bit-Rate), rate large enough to backlog every node Packet size is 1024 bytes Chunyu Hu, UIUC

Impact of contention window size, CW March 2006 Impact of contention window size, CW The temporary increase (will eventually decrease) is caused by the non-uniform access to the post-busy slot. Figure 5-1. Three classes with the same AIFS: CW1, 2, 3 = [8, 16], [16, 32], [32, 64] Chunyu Hu, UIUC

March 2006 Impact of AIFS Figure 5-2. Two classes with the same CW: AIFSN1, 2 = 2, 3 Chunyu Hu, UIUC

Impact of CW and AIFS combined March 2006 Impact of CW and AIFS combined Figure 5-3. Four classes: CW1, 2, 3, 4 = [8, 16], [16, 32], [32, 1024], [32, 1024], AIFSN1, 2, 3, 4 = 2, 2, 3, 7. (Default EDCA parameters) Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

March 2006 Observation 1 Higher priority traffic with smaller AIFS value can easily grab most of the bandwidth and starve other traffic. Figure 6-1. Two classes with the same CW but different AIFS. Left: AIFSN1 = 2, AIFSN2 = 3. Right: AIFSN1 = 2, AIFSN2 = 5. Chunyu Hu, UIUC

Figure 6-2. Three classes: CW1, 2, 3 = [8, 16], [16, 32], [32, 64]. March 2006 Observation 2 Bandwidth allocation fails to stay stable – it varies as the system load (the number of nodes) varies. ratio Figure 6-2. Three classes: CW1, 2, 3 = [8, 16], [16, 32], [32, 64]. Left: throughputs. Right: throughput ratios of class 2/1, and class 3/1. Chunyu Hu, UIUC

Optimal operating points March 2006 Observation 3 Bandwidth is under-utilized – the system is not operating at optimal condition (a problem known in 802.11 DCF). Optimal operating points Figure 6-3. Existence of optimal operating points that can maximize the throughput. Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Suggestion: March 2006 Observation 1 Higher priority traffic with smaller AIFS value can easily grab most of the bandwidth and starve other traffic. Suggestion: Small AIFS has to be carefully used to avoid burst contention Use by real-time traffic only for admission and reservation Real-time traffic, once admitted and made a reservation, access the channel using reservation-based access (e.g. poll-based) Normal contention-based access use the same AIFS Chunyu Hu, UIUC

Leverage our theoretical model to achieve March 2006 Observation 2 Bandwidth allocation fails to stay stable – it varies as the system load (the number of nodes) varies. Observation 3 Bandwidth is under-utilized – the system is not operating at optimal condition (a problem known in 802.11 DCF). Leverage our theoretical model to achieve Constant (in the statistical sense) weighted bandwidth allocation, and Maximize the bandwidth utilization Chunyu Hu, UIUC

Theoretically suggested CWs March 2006 Theoretically suggested CWs Theorem 1: For M classes traffic with the same AIFS value, to achieve proportional bandwidth allocation: rj, which is defined as the ratio of the throughput of class j and that of class 1, and maximum bandwidth utilization, the CW of each class shall be set as follows: where and TD’ is the duration of a successful transmission in the unit of slots. r1  1. Chunyu Hu, UIUC

Numerical and simulation results March 2006 Numerical and simulation results Figure 8. The throughput ratio among different traffic classes before (left) and after (right) optimization based on the theoretical model Chunyu Hu, UIUC

Simulation results March 2006 Figure 10. The total throughput and the throughput attained by each class in the presence of two groups of real-time streams and two classes of best-effort traffic. Left: pre-set bandwidth allocation ratio r3/2 = 0.5 Right: pre-set bandwidth allocation ratio r3/2 = 0.25 Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

Experiment setup Device and driver Experiment scenarios January 2006 doc.: IEEE 802.11-06/11-06-0364-00-000s March 2006 Experiment setup Device and driver WLAN devices with the Atheros chipset (e.g. Netgear WG511T) Basic chipset – most of the MAC functionality is handled in the driver Linux-based MADWifi (Multiband Atheros driver for WiFi) driver Implement the enhanced EDCA in the Hardware Access Layer (HAL) module HAL is similar to firmware and provides an interface to set some parameters, such as CW Experiment scenarios AP estimates number of stations in each class, computes the optimal CW for each class, and broadcast these information in beacon messages. One AP and two classes, one station in each class Pre-specify bandwidth allocation ratio The hardware access layer module operates between the hardware and driver to manage much of the chip-specific operations and to enforce the required FCC regulations. Similar to firmware. AP Chunyu Hu, UIUC Chunyu Hu, UIUC

Experimental results March 2006 Figure 11. Throughputs attained by two traffic classes with on-off traffic. The pre-set ratio is r1/2 = 4. Left: Throughputs (Mbps) Right: Throughput ratio. Chunyu Hu, UIUC

Outline Challenges and Overview of IEEE 802.11s Mesh WLAN March 2006 Outline Challenges and Overview of IEEE 802.11s Mesh WLAN Overview of EDCA Analytical Model of EDCA Simulation Setup and Results Observations How to Handle Each Observation? Experimental Setup and Results Conclusions Chunyu Hu, UIUC

March 2006 Conclusions Have analytically studied the impact of CW and AIFS in EDCA and how to apply it to IEEE 802.11s WLAN Insights obtained Tuning AIFS (small value) has to be cautiously used, so as not to starve best-effort traffic CW has to be tuned dynamically in response to varying load Can now apply these insights to provide per flow QoS or Prioritized QoS and effect congestion control in IEEE 802.11s MESH WLAN. Chunyu Hu, UIUC