Network Selection and Computation Offloading in Non-Terrestrial Network Edge Computing Environments for Vehicular Applications

The Edge Computing (EC) paradigm and the Internet of Things (IoT) have transformed the conventional vehicular network (VN) into a highly reliable, intelligent, and complex networking system serving users with heterogeneous services. However, the traditional terrestrial network-based EC facilities, usually referred to as Vehicular Edge Computing (VEC), enabled through the Road Side Units (RSU) deployments, have limited resources, higher deployment costs, limited coverage, and can rapidly become a bottleneck for the VNs performance. On the other hand, various Non-terrestrial Networking (NTN) platforms from air and space networks have gained a lot of attention in 5G and beyond studies and are expected to play a key role in the upcoming days. Integration of NTN-based EC facilities into the current VEC system can be useful for serving vehicular users with different service types. In this work, we first design a multi-EC enabled vehicular networking platform for serving vehicular users (VUs) with a heterogeneous set of services. We model the various latency and energy requirements for processing the VUs task requests through partial computation offloading operations. We further aim at minimizing the overall latency and energy requirements for processing the VUs data by selecting the proper ENs and the offloading amounts over a multi-EC enabled VN. The problem is modeled as a constrained optimization problem and an evolutionary search-based metaheuristic approach is used to solve it. The results are compared with various benchmark methods for showing the performance gain.