Energy-Efficient Multi-Task Allocation for Antenna Array Empowered Vehicular Fog Computing

With the emergence of compute-intensive and latency-sensitive vehicular applications, vehicular fog computing (VFC) has been proposed for catering to the thriving demands for computing and communication resources close to vehicles. In VFC scenarios where multiple tasks need to be offloaded simultaneously, the data, often coming from multiple sources, must be transmitted at a high data-rate in parallel. An antenna array system, a set of multiple connected antennas which work together as a single antenna, could achieve a significantly higher data-rate than a traditional single antenna. However, data-rate of the antenna array system may decrease due to the presence of interference. On the other hand, an antenna array system consumes more energy than a single antenna, which is antagonistic to vehicles powered by limited electricity. To address these challenges, we propose EAAV, a multi-task allocation strategy that enables multiple tasks to be offloaded concurrently in antenna array empowered VFC. EAAV aims at reducing the transmission power consumption while maintaining a high transmission data-rate, taking into account the mobility of vehicles and communication interference. We transform the multi-task allocation problem into a convex solvable one and evaluate the effectiveness of EAAV based on real-world vehicle trajectories. Compared with the existing task allocation strategy, EAAV improves the average transmission data-rate by up to 8.2% and reduces the average power consumption by up to 38.3%.