ProbeCast: MANET Admission Control via Probing Soon Y. Oh, Gustavo Marfia, and Mario Gerla Dept. of Computer Science, UCLA Los Angeles, CA 90095, USA {soonoh, gmarfia,

Introduction  Multicast “inelastic” streams  Inelastic flow - the rate cannot be elastically controlled (unlike TCP)  Real time flows: situation awareness dissemination; surveillance data/video, etc  Important in tactical/emergency MANETs  Traditional resource reservation ineffective in MANETs  Bookkeeping is very cumbersome in multicast (as number of destinations increases);  Also, mobility requires continuous re-adjustments  Without reservations:  Flow allocation can be “unfair”  possible capture  Network may get congested 2

3 Unfairness Example (unicast)  3 parallel inelastic flows; 500Kbps each  Interference between Flow 1 and 2 and Flow 2 and 3

Goal & Contribution  Achieving reliable QoS support of inelastic flows (e.g., video and audio stream)  ProbeCast:  Enable Call Admission Control and fair allocation of inelastic flows in MANETs without requiring prior resource reservation 4

ProbeCast: key insights  Insight #1: Resource Probing  No a priori resource allocation  Rather “probe” for resources to see if available  Insight #2: Pruning via Back-pressure  Back-pressure (“prune”) toward the source when resource is unavailable  Re-route or reject the inelastic flow  Insight #3: Neighborhood Proportional Drop (NPROD)  Local rate balancing using proportional dropping  Enforces fair channel sharing  “fair back-pressure” 5

ProbeCast: Example 6 Proportional Drop Backpressure (Pruning)

ProbeCast: Probing  Assumptions:  End-to-End FEC – e.g. erasure coding – always ON  Each flow has packet drop threshold (say, 20%), beyond which the flow must be back-pressured  Probing  Each node measures own packet drop rate  It broadcasts to one hop neighbors own drop rate via piggybacking on data packets 7

8  The node estimates packet drop probability DP F for each flow F  It broadcasts to one hop neighbors the DP F value

ProbeCast: N-PROD  Neighborhood Proportional Drop (N-PROD)  Distributed fairness scheme  First introduced and evaluated in FairCast (MSWIM 2008)  Overhearing neighbors’ drop probabilities  Enforcing proportional drop among flows competing in the same contention domain  Forced drop from the queue  After transient, nodes in the same contention domain converge to fair share of the channel 9

ProbeCast: Pruning  Pruning  Flow Drop based on Threshold  Threshold is traffic class and flow age dependent;  Drop Threshold stamped in packet header  Typically, incoming flow has lower threshold than incumbent  When drop rate is > threshold, a flow is backpressured  BckPr signal piggybacked on data packets whenever possible  Upstream node in turn will backpressure when all “children” have sent BckPr signal  Source action (upon receiving backpressure signal):  Re-route if there is alternate route;  Otherwise reject the flow 10

ProbeCast Example (A)Three flows in the same contention domain. Bar graphs shows packet delivery ratios (B)Flow 3 starts transmitting and other flows’ rate decreases (N-PROD). (C)Since Flow 3 drop rate exceeds the threshold, it is backpressured. 11

Simulation  Simulation setup  Qualnet simulations  Radio range 376m; 2Mbps capacity; b  512B packets; 50KB queue in each node  Topologies  Three parallel flows  30 nodes uniformly distributed in a 1000x1000m field  Experiments  N-PROD: to show proportional fairness  ProbeCast: to show proper rejection 12

Three Parallel Flow Topology S2 R3 R2 S3 F3 F2 R1F1 S1 Flow 3 Flow 2 Flow 1 Source Forwarder Receiver  F1, F2, and F3 are within the same contention domain  No interference between sources and forwarders  No interference between forwarders and receivers  Staggered Transmission starts: 1s, 10s, 20s 13

Three Even Parallel Flows  Uniform nominal rate = 500Kpbs  Flows 2 has higher packet drop rate without N-PROD  N-PROD restores fairness 14

Three Even Parallel Flows (cont)  Uniform nominal rate = 500Kpbs  Aggregated throughput of the three flows  Fairness comes at the cost of degraded total throughput 15

Three Uneven Parallel Flows  Flow1 = 800Kbps, Flow2 = 400Kbps, and Flow3=200Kbps  Without N-PROD, Flow 1 and 3 capture the channel  With N-PROD proportional drop yields 8:4:2 ratio 16

Three Uneven Parallel Flows (cont)  Aggregated throughput of 3 flows  Flow1 = 800Kbps, Flow2 = 400Kbps, and Flow3=200Kbps  Proportional fairness again comes at the cost of degraded total throughput 17

Two Flows in Random Topology  30 nodes in 1000 by 1000 meter  Flow 1: 200Kbps video stream, 9 members  Flow 2: 40Kbps audio stream, 3 members 18 Session 2 Session 1 Session 2

Two Flows in Random Topology  Session 1 captures channel in ODMRP so session 2 starves  N-PROD achieves fairness  All members in session 1 and 2 receive more than 50% packets  Drop Threshold = 50% 19

Three Flows in Random Topology  Three multicast sessions, each session has 1 source and 3 members  30 nodes in 1000 by 1000 meter  Data transmission starts Session1 T=1s, Session2 T=10s, and Session3 T=20s  500Kbps traffic; drop threshold = 50% 20 Session 1 Session 2 Session 3

Three Flows in Random Topology (cont)  Three multicast sessions compete within the same collision domain  Session 2 is rejected (it came after Session 1 - initially lower threshold) 21

Conclusion  N-PROD achieves proportional bandwidth share in the same contention domain  ProbeCast uses probing and backpressure to accept feasible flows and reject unfeasible ones.  Probecast can also handle inelastic unicast (a special case of multicast) 22