On Attack-Resilient Service Placement and Availability in Edge-enabled IoV Networks

TL;DR

This paper proposes a deep reinforcement learning framework for attack-resilient service placement in edge-enabled IoV networks, enhancing resilience and availability amidst dynamic traffic and potential attacks.

Contribution

It introduces a novel DRL-based approach with ILP models for optimal, attack-resilient service placement and recovery in IoV networks, addressing traffic variability and resource constraints.

Findings

DRL framework effectively adapts to dynamic IoV traffic.

Proposed models improve service availability during attacks.

Numerical experiments validate approach's efficiency and resilience.

Abstract

Achieving network resilience in terms of attack tolerance and service availability is critically important for Internet of Vehicles (IoV) networks where vehicles require assistance in sensitive and safety-critical applications like driving. It is particularly challenging in time-varying conditions of IoV traffic. In this paper, we study an attack-resilient optimal service placement problem to ensure disruption-free service availability to the users in edge-enabled IoV network. Our work aims to improve the user experience while minimizing the delay and simultaneously considering efficient utilization of limited edge resources. First, an optimal service placement is performed while considering traffic dynamicity and meeting the service requirements with the use of a deep reinforcement learning (DRL) framework. Next, an optimal secondary mapping and service recovery placements are performed to account for the attacks/failures at the edge. The use of DRL framework helps to adapt to dynamically varying IoV traffic and service demands. In this work, we develop three ILP models and use them in the DRL-based framework to provide attack-resilient service placement and ensure service availability with efficient network performance. Extensive numerical experiments are performed to demonstrate the effectiveness of the proposed approach.