A Context-Oriented Framework and Decision Algorithms for Computation Offloading in Vehicular Edge Computing

Some increasingly popular vehicular applications have critical time requirements. As vehicles still do not have enough computation power, they cannot satisfy these demands satisfactorily. One option to deal with this problem is to enable vehicles to transfer computational tasks to cooperating devices through the offloading technique. However, performing this technique in vehicular scenarios is challenging due to the fast movement of network nodes and the frequent disconnections. Thus, we propose a context-oriented framework and decision algorithms to reduce the execution time of vehicular applications reliably through computation offloading in vehicular edge computing systems. Experimental results show that our solutions can significantly improve the execution time of vehicular applications.