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Incentive-Compatible Opportunistic Routing for Wireless Networks Fan Wu, Tingting Chen, Sheng Zhong (SUNY Buffalo) Li Erran Li Li Erran Li (Bell Labs) Yang Richard Yang Yang Richard Yang (Yale University) Fan Wu Speaker: Fan Wu

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Motivation User-contributed wireless mesh networks –Low cost –Unpredictable and lossy wireless links From

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Motivation (cont’) Opportunistic routing emerged to improve throughput, e.g., –ExOR (Biswas and Morris [2005]) –MORE (Chachulski et. al. [2007]) SRD LLP = 0.4 LLP: Link Loss Probability LLP = 0.8 ENT: Expected Number of Transmissions ENT = 1.18 LLP = 0.4 ENT = 1.47 p1p1 p2p2 p1p1 p2p2 p 1 +p 2 p1p1 p2p2

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Motivation (cont’) Selfish behavior may reduce performance –Free-rider problem –Adverse selection problem SRD LLP = 0.1 ↓ LLP: Link Loss Probability LLP = 0.8 ENT: Expected Number of Transmissions ENT = 0.78 ↓ LLP = 0.4 ENT = 1.47

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Motivation (cont’) Existing incentive mechanisms are mainly based on shortest path routing Need to design incentive-compatible routing protocols so that each user node participates in opportunistic routing honestly

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Objective Develop incentive compatible techniques that can be integrated with a wide class of opportunistic routing protocols A basic opportunistic routing protocol: –collects link states and then –computes a forwarding behavior profile for user nodes

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Basic Opportunistic Routing Protocol Source Node, S –Divides traffic into batches of packets –Keeps sending coded packets in current batch –Moves to next batch if acknowledged Intermediate Node, i –Broadcasts a coded packet if needed –Targets expected number of transmissions z i : ε i,j : loss probability on link (i, j) Destination Node, D –Decodes received packets –Sends acknowledgments

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Issues Issue 1: Motivating Honest Reporting Issue 2: Motivating Honest Measuring

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Issue: Motivating Honest Reporting Ideal scenario: Each node i reports the loss probabilities of its outgoing links Reality: Without proper incentive, node i may not report its link loss probabilities honestly

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Techniques to Motivate Honest Reporting We design a routing protocol, such that reporting loss probabilities truthfully is the best strategy of each node Techniques: We influence the strategies of the players by introducing –an auxiliary transmission and –a carefully designed payment formula

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Motivating Honest Reporting: Auxiliary Transmission For each packet that a node i should forward, it is required to send an auxiliary traffic of size z* i,j to each node j V p α is a very small constant ε’ i,j is the reported loss probability on link (i,j)

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Motivating Honest Reporting: Payment Formula L is the packet length –covers the cost of packet transmissions –covers the cost of auxiliary transmissions (We assume that transmitting a packet of size 1 has one unit of cost.)

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Why Auxiliary Transmission and the Payment Formula? Utility: Get maximized when

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ACK How does the protocol work? S A D B ε’ A,D, ε’ A,B ε’ B,D, ε’ B,A z’ A, z* A,D, z* A,B z’ B, z* B,D, z* B,A ACK pApA pBpB AUX

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Motivating Honest Reporting: Analysis –Theorem: It is a strictly dominant strategy equilibrium for all player nodes to truthfully report loss probabilities. Strictly Dominant Strategy Equilibrium: The equilibrium strategy is strictly better than any other strategy for each node regardless of other nodes’ behaviors.

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Two Steps Step 1: Motivating Honest Reporting Step 2: Motivating Honest Measuring

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Issue: Cheating in Measurements Practical scenario: A node needs the cooperation (feedback) of its neighbors to measure link loss probabilities Dishonest feedback may allow one node to cheat its neighbors in order to raise its own utility

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Techniques to Achieve Truthful Measurements We design an enhanced routing protocol, such that truthfully measuring the loss probabilities is to the best interest of each node Techniques: We influence the strategies of the players by carefully designing –measurement (test) signals and –a payment formula (Auxiliary transmission is the same as before.)

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Measurement Signaling –Each node i sends n t measurement signals –Format of measurement signal: k S,i is a secret key shared by S and i MAC is a cryptographic Message Authentication Code function –Each node forwards measurement signals using traditional routing protocol –If n i,j measurement signals are received, then

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Payment Covering Measurements Payment Formula: –covers the cost of packet transmissions –covers the cost of auxiliary transmissions –prevents dropping measurement signals

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TEST_1 TEST_2 TEST_n BA … How does the enhanced protocol work? S A D B z’ A, z* A,D, z* A,B z’ B, z* B,D, z* B,A ACK pApA pBpB AUX TEST_1 TEST_2 TEST_n DA … TEST_1 TEST_2 TEST_n DB … AUX TEST_1 TEST_2 TEST_n AB … TEST_1 TEST_2 TEST_n AD … TEST_1 TEST_2 TEST_n BD …

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Motivating Truthful Measurements: Analysis –Theorem: There is a strict Nash equilibrium for all player nodes to behave honestly in sending test signals and forwarding the received test signals. –Theorem: The above equilibrium is the only strict Nash equilibrium in the system. Strict Nash Equilibrium: Unilaterally deviating from the equilibrium strategy will hurt a player’s utility.

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Evaluation Setup Real implementation and tests on the ORBIT testbed 25 nodes b ad hoc mode Trans. power 20 dBm Bit-rate 11Mbps MORE batch size 32 Packet size 1500 bytes Loss prob. 24%~100% Session length 30 s α=0.1 β=0.05

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Evaluation Setup Node Behavior: –Honest behavior: Each node follows our protocol faithfully –Cheating behavior: Misreporting link loss probabilities in the simple extension; Sending incorrect number of measurement signals and Dropping others’ measurement signals in the enhanced extension

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Cheating Behavior and Node Utility Simple extension Utilities obtained by node 18 Enhanced extension Utilities obtained by node 11 Utilities obtained by honest reporting and cheating randomly

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Cheating Behavior and Node Utility Utilities obtained by applying various strategies Simple extensionEnhanced extension

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Impacts on End-to-End Throughput Average throughput as a function of the number of hops on the path Simple extension Up to 33.2% (58.0%) gain when 20% (40%) cheating Enhanced extension Up to 13.7% (23.4%) gain when 20% (40%) cheating

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Miscellaneous Overhead: –Average auxiliary transmissions: KB –Average data transmitted: 3.93 MB –Ratio: 0.66% Auxiliary payment: –Ratio between auxiliary payment and total payment –Simple extension: 0.23% –Enhanced extension: 1.20%

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Conclusion We study incentives in opportunistic routing and provide first solutions. We present a simple and practical protocol to guarantees that it is a strict dominant strategy for each user node to behave honestly. We also design an enhanced protocol to prevent cheating in measuring loss probabilities. We implement and evaluate our protocols on the ORBIT lab. The experimental results show that our protocols can bring the system throughput achieved by opportunistic routing protocols back to the high level.

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Thank you!

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