Congestion Control in Multi-hop Wireless Mesh Networks Ihsan Ayyub Qazi

Background: Congestion Control What is congestion? – A network state where the arrival rate exceeds the service rate Throughput starts decreasing (due to packet losses) Delay increases fast (queues build up) Why does congestion occur? – No admission control Where does congestion control take? – At the end hosts – congestion inferred from end-system observed loss and delay

Goals of Congestion Control Avoid congestion – Avoid packet losses, keep delays low Efficient use of resources – Given some demand, resource must be utilizable Fair use of resources – Allocate resources according to a fairness criteria – Max-Min fairness allocation is max-min fair if no rates can be increased without decreasing an already smaller rate

Transmission Control Protocol (TCP) Only W packets may be outstanding Rule for adjusting W  If an ACK is received: W ← W+1/W  If a packet is lost:W ← W/2

Understanding Congestion Control in Multi-hop Wireless Mesh Networks Sumit Rangwala, Apoorva Jindal, Ki-Young Jang, Konstantinos Psounis and Ramesh Govindan (MobiCom’08) Acknowledgement: following slides taken from Sumit Rangwala, USC.

Mesh Networks Static multi-hop mesh networks have been proposed as an alternative to wired connectivity User’s satisfaction hinges on transport performance – TCP’s performance on mesh networks is known to be poor Starvation Is poor transport performance inherent to multi-hop mesh networks? Can a correctly designed transport help make mesh networks a viable alternative? 6

TCP’s Performance TCP only signals flows traversing the congested link – Link centric view of congestion Fails to account for neighborhood congestion 7 TCP Optimal (Max Min) What mechanisms can help us achieve near-optimal rates?

WCPCap WCP Approach AIMD Based Design Neighborhood-centric Transport 8 Explicit Rate Notification

Neighborhood of a Link Neighbors (overhearing) 10 Neighborhood of a link – All incoming and outgoing links of Sender Receiver One hop neighbors of the sender One hop neighbors of the receiver Link → sender receiver pair Prohibits channel capture Prohibits channel capture at the sender or causes collision at the receiver Ensuing ACK prohibits channel capture at the sender or causes collision at the receiver

WCP: AIMD Based Design When a link is congested, signal all flows traversing the neighborhood of a link to reduce their rate by half, i.e., r f = r f / 2 React to congestion after RTT neighborhood Multiplicative Decrease Key Insight: Congestion is signaled to all flows traversing neighborhood of a congested link 10

WCP During no congestion increase a flow’s rate as r f = r f + α Every RTT neighborhood Additive Increase Key Insight: Rate adaptation is clocked at the largest flow RTT in a neighborhood RTT neighborhood : Largest flow RTT within the neighborhood 11

Simulations: Stack Topology WCP achieves near optimal performance – Through congestion sharing in the neighborhood Simulation setup –Qualnet –802.11b MAC with default parameters –TCP SACK –Auto rate adaptation is off

WCPCap WCP Approach AIMD Based Design Neighborhood-centric Transport 13 Explicit Rate Notification

WCPCap: Explicit Rate Feedback Estimate residual capacity in a neighborhood – Need to know the achievable rate region for scheduled mesh networks Using only local information 14 Challenge: Is a given set of rates achievable in a neighborhood?

Combine, incorporating link dependencies, individual probabilities to find net collision and idle probabilities of the link Combine, incorporating local link dependencies, individual probabilities to find net collision and idle probabilities for the link Calculating Achievable Rates Decompose the neighborhood topology of a link into canonical two-link topologies Find collision and idle time probability of the link in every two-link topology Compute expected packet service time for a link from collision and idle probability of the link Check feasibility, i.e., for each link, Packet arrival rate × E[service time of a packet] ≤ U, 0 ≤ U ≤ 1 15 Requires global information Using only local information Jindal et. al., “The Achievable Rate Region of Scheduled Multi-hop Networks”.

WCPCap: Explicit Rate Feedback Every epoch – Find, by binary search, the largest increment or smallest decrement, δ, such that the new rates are achievable yet fair – Increase/decrease rate of each flow by δ U=1 (100% utilization) would yield large delays, we target U=0.7 16

Simulations: Stack Topology WCPCap slightly better than WCP – Yields smaller queue and thus smaller delays – Not as good as optimal as we target 70% utilization Simulation setup –Qualnet –802.11b MAC with default parameters –TCP SACK –Auto rate adaptation is off TCP Optimal WCPCap WCP

Simulations: Diamond Topology WCP does not achieve max-min rates – Rates are dependent on the number of congested neighborhood and the degree of congestion WCPCap achieves max-min rates

Experimental Setup Mini-PCs running Click and Linux – ICOP eBox b wireless cards running the madwifi driver Omni directional antennas – some antennas covered with aluminum foils to reduce transmission range 19

Experimental Results: Stack Topology SimulationsExperiments For this topology, WCP’s simulation and experimental results are nearly identical 20

Experimental Results: Arbitrary Topology 14 nodes and five flows TCP starves different flows during different runs WCP consistently gives fair rates 21

WXCP: Explicit Congestion Control for Wireless Multi-hop Networks Yang Su and Thomas Gross (IWQoS’05)

Motivation In wireless networks, physical capacity is not fixed – Varies with the number of contending nodes and the traffic load in the neighborhood CC Protocols (such as XCP) that rely on link capacity estimate for computing feedback tend to overestimate capacity – Gives rise to unfairness and fluctuating rates

Contribution Proposes an extension to XCP for wireless networks – Estimates how much capacity a flow has for fair access by locally monitoring channels conditions Proposes three metrics for measuring the state of resource usage and the level of congestion at a node – Available bandwidth – Interface queue length – Average link layer retransmission

Congestion Metrics Available bandwidth – If estimation is made periodically, channel idle time represents network capacity still available during the estimation period =time used by station itself+physical carrier sense time+virtual carrier sense time

Congestion Metrics Interface queue length – When input rate > output rate  queue builds up Average link layer retransmission

Performance

Packet drop rate and Fairness

Grid Topology

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