  Augmented Reality (AR) and Virtual Reality (VR) systems involve
computationally intensive image processing algorithms that can burden
end-devices with limited resources, leading to poor performance in providing
low latency services. Edge-to-cloud computing overcomes the limitations of
end-devices by offloading their computations to nearby edge devices or remote
cloud servers. Although this proves to be sufficient for many applications,
optimal placement of latency sensitive AR/VR services in edge-to-cloud
infrastructures (to provide desirable service response times and reliability)
remain a formidable challenging. To address this challenge, this paper develops
a Multi-Objective Genetic Algorithm (MOGA) to optimize the placement of
AR/VR-based services in multi-tier edge-to-cloud environments. The primary
objective of the proposed MOGA is to minimize the response time of all running
services, while maximizing the reliability of the underlying system from both
software and hardware perspectives. To evaluate its performance, we
mathematically modeled all components and developed a tailor-made simulator to
assess its effectiveness on various scales. MOGA was compared with several
heuristics to prove that intuitive solutions, which are usually assumed
sufficient, are not efficient enough for the stated problem. The experimental
results indicated that MOGA can significantly reduce the response time of
deployed services by an average of 67\% on different scales, compared to other
heuristic methods. MOGA also ensures reliability of the 97\% infrastructure
(hardware) and 95\% services (software).
