Optimal Association Strategy of Multi-gateway Wireless Sensor Networks Against Smart Jammers

TL;DR

This paper introduces an analytical game-theoretic model for multi-gateway wireless sensor networks to optimize gateway association and mitigate jamming attacks, demonstrating significant throughput improvements with multiple gateways.

Contribution

It presents a novel Stackelberg game-based model for gateway selection in sensor networks under jamming, including equilibrium analysis and performance evaluation.

Findings

Throughput increases by 26% with two gateways and 60% with four gateways under jamming.

The model effectively captures network performance variations with different gateway configurations.

Proves conditions for Nash equilibrium in the context of sensor network and jammer interactions.

Abstract

Engineers have numerous low-power wireless sensor devices in the current network setup for the Internet of Things, such as ZigBee, LoRaWAN, ANT, or Bluetooth. These low-power wireless sensors are the best candidates to transfer and collect data. But they are all vulnerable to the physical jamming attack since it is not costly for the attackers to run low power jammer sources in these networks. Having multiple gateways and providing alternative connections to sensors would help these networks to mitigate successful jamming. In this paper, we propose an analytical model to solve the problem of gateway selection and association based on a Stackelberg game, where the jammer is the follower. We first formulate the payoffs of both sensor network and attacker and then establish and prove the conditions leading to NASH equilibrium. With numerical investigation, we also present how our model can capture the performance of sensor networks under jamming with a varying number of gateways. Our results show that compared to the single gateway scenario, the network's throughput will improve by 26% and 60% when we deploy two and four gateways in the presence of a single jammer.