Joint Management of Communication, Computing, and Storage Resources for Low Latency Vehicular Edge Computing
Mostafa Kishani, Zdeněk Bečvář · IEEE Transactions on Intelligent Transportation Systems · 2025
Low-latency Vehicular Edge Computing (VEC) applications require an efficient VEC resource allocation considering all components contributing to application latency, i.e., computation, communication, and storage. While the optimization of communication and computation resources is broadly addressed in literature, storage, a significant source of latency in the computing stack, is often ignored in existing works. Thus, in this paper, we optimize the communication and computation resources together with the storage resources to minimize the latency of VEC applications. The problem of jointly minimizing communication, computation, and storage latency under practical constraints is NP-hard. Hence, we employ dual decomposition and Lagrangian relaxation to achieve a computationally viable solution for the joint communication, computing, and storage resource allocation to VEC applications. To this end, we define a dual problem of the assignment of VEC applications to base stations. This problem corresponds to the perfect matching problem in a weighted bipartite graph and optimally solvable by algorithms with polynomial computation complexity. Then, as the solution to the dual problem may violate some constraints of the main resource allocation problem, we find a feasible solution to the main resource allocation problem using Lagrangian relaxation. We show that the joint optimization of all three aspects, i.e., communication, computation, and storage, reduces the overall offloading latency up to 60% compared to state-of-the-art works.