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Channel Contention with a Large Number of Devices

Channel Contention with a Large Number of Devices. Date: 2011-07-14. Authors:. Abstract.

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Channel Contention with a Large Number of Devices

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  1. Channel Contention with a Large Number of Devices Date: 2011-07-14 Authors: Edward Reuss, SK Communications

  2. Abstract • Certain use cases for IEEE 802.11 networks involve a large number of devices conveying time-sensitive information through a single AP. Many of these involve frequent transmission of relatively short packets, less than 200 bytes. In these scenarios the time on the medium to transmit the actual data is very short, but because there are so many devices the contention windows must be very long to minimize the probability of a collision. This effect limits the maximum number of devices that can participate in these applications. This presentation introduces the reasons that cause this problem and proposes some possible solutions. Edward Reuss, SK Communications

  3. Channel Contention with a Large Number of Devices • Several applications require support for a large number of devices communicating time-sensitive information, such as telephony or sensor streams, through a single AP. • Most of these use cases involve frequently transmitting a series of relatively short data packets (~200 bytes or less). • Enterprise Wireless VoIP • “Internet of Things” (IoT) • SmartGrid • Process Control (Manufacturing, Industrial systems, etc.) • Automotive (Engine sensors, Impact warnings, etc.) • ?? Edward Reuss, SK Communications

  4. Example: Enterprise Wireless VoIP • Assume: • Either: • Duplex G.711 PCM audio @ 8 kSamples/sec. • or Duplex G.722 ADPCM audio @ 16 kSamples/sec. • 20 msec. packet intervals = 160 bytes of audio data per packet, uplink and downlink • UDP/IP Packets: 86 header bytes total • SNAP/LLC: 8 bytes, UDP header: 8 bytes, IP header: 20 bytes • MAC Security (AES): 16 bytes, MAC frame header & CRC: 34 bytes • IEEE 802.11a PHY: • Symbol Interval: 4 μsec, PHY header: 16 μsec, PLCP header: 4 μsec. Edward Reuss, SK Communications

  5. Example: Enterprise Wireless VoIP #2 • Calculate the length of a single audio data packet + the Ack packet + DIFS + SIFS, in microseconds. • Therefore the maximum theoretical call capacity for duplex data packets, Ack packets, DIFS & SIFS is: Edward Reuss, SK Communications

  6. IEEE 802.11 Collision Avoidance • Contention Window • New Packets: Randomly assigned to the range [0,CWmin]. • Retransmitted Packets: Randomly assigned to a range that exponentially increases from [0,CWmin] to [0, CWmax]. • Assuming no collisions & no retransmissions • For k devices attempting to transmit a packet on the same Access Category, the average contention window delay is: Edward Reuss, SK Communications

  7. Effect of CA on the VoIP Example • Add tCWavg to each audio data transmission • Assumes 20 devices and CWmin = 127. Times are in microseconds. • This overhead remains tolerable, although the average length of the contention window is approaching the length of the entire packet + Ack sequence. Edward Reuss, SK Communications

  8. Probability of a Collision • Pigeonhole Principle: • If k pigeons are placed randomly into m pigeonholes (m ≥ k), the probability of 2 or more pigeons in one hole are: • Basis for the “Birthday Paradox” • How many randomly chosen people do you need in a room for there to be a better than even chance that at least two of them have the same birthday? Answer: 23 people • The paradox is that this is a surprisingly small number for 365 days in a year. • This is the source of the problem with IEEE 802.11 CA for many devices transmitting rapid sequences of short packets. Edward Reuss, SK Communications

  9. Impact of Collisions - Cascade • Every time a collision occurs, at least two packets must be retransmitted. • At the same time another device may have a packet ready to transmit. • Therefore, for the next contention window: k’ = k + 1 If CWmin = CWmax = 255, there is no room for the exponential backoff for the retransmitted packets, so the probability continues to rise. • This causes the probability of a second collision to increase, resulting in a cascade of packet collisions and retransmissions. Edward Reuss, SK Communications

  10. Future Trends • Amendments IEEE 802.11n and 802.11ac exacerbate this problem further by increasing the relative overhead due to the packet headers and the contention window with respect to the actual user data symbols. • IEEE 802.11a may use as few as 10 symbols (40 μsec.) for the VoIP example. • IEEE 802.11ac can fit an entire VoIP data packet into a single symbol at the higher modulation indices. • The utilization efficiency of the medium falls as the contention window and packet header overheads dominate the medium. Edward Reuss, SK Communications

  11. Impact on Short Packet Applications • These amendments have increased the effective throughput for long packets from a single stream by about 40 times, from about 25 Mbps for 802.11a to over 1000 Mbps for 802.11ac. • But the contention window remains unchanged from the original definition in IEEE 802.11-1997 and the Time_Slot of 9 μsec, as defined in 802.11a. • This limits the utility of IEEE 802.11 for short packet applications. Edward Reuss, SK Communications

  12. Solution 1: – Fractional Time Slots • Add an optional operating mode that recognizes fractional time slots “FTS”. • FTS = TS / 4 = 9 μsec / 4 = 2.25 μsec. • Or possibly: • FTS = TS / 8 = 9 μsec / 8 = 1.125 μsec. • This is a cheap solution, but it may be impractical to implement. • This is only a partial solution, but it may be adequate to make the use cases feasible. Edward Reuss, SK Communications

  13. Solution 2: Dynamic Contention Window • Modify the contention window dynamically according to the load requirements. • Adapts to high load conditions when required. • Can choose between various strategies. • Cooperative or non-cooperative • Cooperative: All nodes share their load requirements with all other nodes. • Non-cooperative requires each node to listen to the traffic, collisions, etc, to infer the network load requirements. • Heterogeneous or homogeneous • Homogeneous uses the same strategy at all nodes. • Heterogeneous uses different strategies for differentiated access categories. • Reference [5] uses a game theoretic strategy amongst non-cooperative nodes. • Must guard against cheaters. Edward Reuss, SK Communications

  14. Solutions – Contention-less Strategies • Removes the contention window entirely. • See reference [6]. • Theoretically removes all collisions. (Famous last words) • Normally cooperative (but not required) • Every node broadcasts, or group-casts, their load requirements to all of the other nodes. • This overhead is much smaller than the overhead from the contention windows and the collisions. • All nodes use an identical strategy to calculate the transmission schedule for every node in the group. (Homogeneous strategy) • Each node knows when it is their turn to transmit their packet(s) according to the calculated schedule. Edward Reuss, SK Communications

  15. Contention-less Strategy in IEEE 802.11 • AP sends “CTS-to-Self” to set the NAV, defining the contention-less interval according to the dynamic load requirements for each interval. • Each device senses the contention-less interval, and starts transmitting at their calculated point in the schedule. • Similar to the old CFP, except more flexible. • The load announcements can be piggy-backed onto other existing traffic, such as sounding packets. Edward Reuss, SK Communications

  16. Straw Poll #1 • Do you think the overhead from contentions and collisions may be significant for at least some of the use cases presented? • Agree: • Disagree: • Abstain: Edward Reuss, SK Communications

  17. Straw Poll #2 • Assuming the results of Straw Poll #1 are affirmative, do you agree that the IEEE 802.11 WG should form a study group to pursue this problem? • Agree: • Disagree: • Abstain: Edward Reuss, SK Communications

  18. References • IEEE 802.11-1997 • Amendment IEEE 802.11a-2003 • Amendment IEEE 802.11n • Draft Amendment IEEE 802.11ac • “Contention Control: A Game-Theoretic Approach”, Chen, Low & Doyle, 46th IEEE Conference on Decision and Control, 2007. • “Many-to-many communication for mobile ad hoc networks”, Moraes, Sadjadpour & Garcia-Luna-Aceves, IEEE Transactions on Wireless Communications, Vol. 8 Issue 5, May 2009. Edward Reuss, SK Communications

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