Distributed Fair Scheduling in a Wireless LAN Nitin Vaidya, Texas A&M University Victor Bahl, Microsoft Research Seema Gupta, now with Cisco MobiCom 2000

Distributed Scheduling : What & Why

Wireless medium is a broadcast medium Medium Access Control Wireless medium is a broadcast medium Transmissions by multiple nodes can interfere Need medium access control (MAC) Many proposals Centralized Distributed

Centralized Protocols Base station coordinates access to the wireless channel Node 1 Node 2 Base Station Node 3 Node n

Distributed Protocols All nodes have identical responsibilities Node 1 Node 2 Wireless LAN Node 3 Node n

Disadvantages of Centralized Approach If a node cannot talk to the base station, it cannot transmit to any other nodes Base station needs to keep track of state of other nodes Hard to use failure-prone nodes as coordinators in centralized protocols

Fairness

Fairness Packets to be transmitted belong to several flows Each flow is assigned a weight Bandwidth assigned to each backlogged flow is proportional to its weight

Fairness Three flows with weights 2, 1, 1 Backlogged flows: Allocated bandwidth Backlogged flows:

Many centralized fair queueing protocols exist WFQ, WF2Q, SCFQ, SFQ, … Scheduler needs to know state of all flows Flow 1 Flow 2 Flow n Output link

Distributed Fair Scheduling

Fully distributed fair scheduling protocol Our Objectives Fully distributed fair scheduling protocol All nodes have identical responsibilities Nodes do not need to be aware of each other’s state Maintain compatibility / resemblance with an existing standard specifically, IEEE 802.11 Distributed Coordination Function

IEEE 802.11 Distributed Coordination Function (DCF) Proposed Approach Combination of IEEE 802.11 Distributed Coordination Function (DCF) Carrier sense / collision avoidance A centralized fair queueing protocol

Basic Carrier Sense Approach A node wishing to transmit waits until channel is sensed as idle, and then transmits If two nodes are waiting to transmit, they will collide Collision avoidance mechanism needed to avoid this

IEEE 802.11 Distributed Coordination Function Collision avoidance mechanism: When transmitting a packet, choose a backoff interval in the range [0,cw] cw is contention window Count down the backoff interval when medium is idle When backoff interval reaches 0, transmit 0 cw

802.11 DCF Example B1 = 25 B2 = 20 B1 = 5 B2 = 15 data wait data wait B1 and B2 are backoff intervals at nodes 1 and 2 cw = 31

Self-Clocked Fair Queueing (SCFQ) [Golestani] A centralized fair scheduling protocol But more amenable for a distributed implementation than many others The steps involved in deriving proposed distributed protocol starting from SCFQ are given in the paper virtual time, start/finish tags implementation does not need virtual time or tags

Distributed Fair Scheduling (DFS) Node with smallest “length/weight” should transmit first Caveat: This is a somewhat imprecise statement. DFS (implicitly) compares so-called virtual finish tags, which are a function of length/weight See paper for details on the finish tags Backoff intervals used as a way to distributedly determine whose “length/weight” is smaller

Distributed Fair Scheduling (DFS) Choose backoff interval = packet length / weight packet length = 5 weight = 1/3 backoff interval = 5 / (1/3) = 15 slots

Distributed Fair Scheduling (DFS) Collision ! data wait data wait Packet length = 15 Weight of node 1 = 1 ====> B1 = 15 / 1 = 15 Weight of node 2 = 3 ====> B2 = 15 / 3 = 5

Collisions occur when two nodes count down to 0 simultaneously In centralized fair queueing, ties can be broken without causing “collisions” To reduce the possibility of collisions: Backoff interval = Scaling_Factor * length / weight * random number with mean 1

Backoff Interval Initial formula: Length / weight = 15 / 1 = 15 Scaling_factor * length / weight * random number = 4 * 15 / 1 * [0.9,1.1] = [54,66] 0 15

Backoff Interval 802.11 Proposed DFS

Collisions Resolution Collision occurs when two nodes count down to 0 simultaneously Counting to 0 implies that it is a given node’s “turn” to transmit To reduce “priority” reversals, a small backoff interval is chosen after the first collision Backoff interval increased exponentially on further collisions

Impact of Small Weights Backoff interval: Scaling_factor * length / weight * random number Backoff intervals can become large when weights are small Large backoff intervals may degrade performance (time wasted in counting down)

Impact of Small Weights Recall: Backoff intervals are being used to compare “length/weight” Intuition: Any non-decreasing function of lenghth/weight may be used to obtain backoff intervals

Scaling_factor * length / weight * random number Alternative Mappings Chosen backoff interval Linear mapping SQRT EXP Scaling_factor * length / weight * random number

Alternative Mappings Advantage Disadvantage smaller backoff intervals less time wasted in counting down when weights of all backlogged flows are small Disadvantage backoff intervals that are different on a linear scale may become identical on the compressed scale possibility for greater number of collisions

Performance Evaluation Using modified ns-2 simulator: 2 Mbps channel Number of nodes = N Number of flows = N/2 Odd-numbered nodes are destinations, even-numbered nodes are sources Unless otherwise specified: flow weight = 1 / number of flows backlogged flows with packet size 584 bytes (including UDP/IP headers) Scaling_Factor = 0.02

Fairness measured as a function of Fairness Index Fairness measured as a function of (throughput T / weight f) for each flow f over an interval of time Unless specified, the interval is 6 seconds

Throughput / Weight Variation Across Flows (with 16 Flows) 802.11 Flatter curve is fairer DFS Throughput / Weight Flow destination identifier

Throughput - Fairness Trade-Off 802.11 Aggregate throughput (all flows combined) Number of flows

Throughput - Fairness Trade-Off index 802.11 Number of flows

Scaled 802.11 Fairness of 802.11 can be improved by using larger backoff intervals Is DFS fairer simply because it uses large backoff intervals ? Scaled 802.11 = 802.11 which uses backoff interval range comparable with DFS

Number of packets transmitted by a flow Short-Term Fairness Narrow distribution is fairer DFS is fairer DFS Frequency Scaled 802.11 802.11 Number of packets transmitted by a flow (over 0.04 second windows)

Fairness versus Sampling Interval Size (24 flows) DFS Scaled 802.11 Fairness index 802.11 Interval Size

Alternative Mappings for Backoff Intervals See additional data in the paper EXP and SQRT improve throughput compared to LINEAR mapping when all backlogged flows have low weights but not too impressively If at least one backlogged flow has a high weight, not much benefit

Conclusions (supporting arguments for some conclusions not presented in the talk: please see the paper) DFS improves fairness compared to 802.11 and Scaled 802.11 Alternative mappings somewhat beneficial No distributed fair scheduling protocol may accurately emulate work-conserving centralized protocols (unless clocks are synchronized)

Possible to handle multiple flows per node Conclusions Possible to augment DFS with other techniques to improve fairness in presence of transmission errors see Seema Gupta’s M.S. thesis No performance cost even if weight assigned to a flow is changed on a per-packet basis Execution complexity of centralized protocols would increase Possible to handle multiple flows per node

Other Potential Applications of DFS Wired LANs Wireless multi-hop networks see our 1999 Microsoft Research technical report for some initial ideas

Issues for Further Work DFS is only the first step towards practical fairness: How to choose parameters such as Scaling_Factor ? Failure to choose reasonable values can degrade throughput or short-term fairness How to choose flow weights ? Let upper layer specify dynamically, or Static assignment based on static criteria Ad hoc network-related issues

Thank you! www.cs.tamu.edu/faculty/vaidya

Thank you! www.cs.tamu.edu/faculty/vaidya

Impact of Packet Size Flow throughput Three flows 802.11 with different packet sizes 802.11 584 328 200 Packet size (bytes)

Impact of Scaling Factor (six flows with weights 1/2,1/4,1/8,1/16,1/32,1/32) DFS Fairness index Scaling Factor

Impact of Scaling Factor (six flows with weights 1/2,1/4,1/8,1/16,1/32,1/32) Aggregate throughput DFS Scaling factor

Related Past Work Centralized fair queueing on wired links [Bennett,Demers,Parekh] Centralized fair queueing in wireless environments, taking location-dependent errors into account [Bharghavan,Ramanathan,Zhang] Distributed Real-time scheduling [Sobrinho] Distributed Priority-based scheduling

How to choose these adaptively ? Backoff Interval Scaling factor Small number : May result in more collisions Large number: Larger overhead Random number range Small range will cause more collisions between synchronized nodes How to choose these adaptively ? This paper punts the issue But heuristic solutions are easy to define Heuristics yet to be evaluated