Dynamic resource allocation on Vehicular edge computing and communication

Abstract

The improvement of modern communication technology has made the Internet of Vehicles (IoV) advance by leaps and bounds, and promotes the progress of many technologies, such as mobile sensing, vehicular edge computing, sensor networks, satellite positioning, data analysis, etc. Vehicular edge computing (VEC) is an innovative computing paradigm which can provide flexible and reliable computation services for intelligent and connected vehicles. An optimized problem is formulated to minimize the total task offloading time delay by making a tradeoff between vehicle mobility and task nature. To tackle the optimization problem, we proposed the Delay-sensitive half-Determined atomic Search algorithm, called DeshDaS, in which we regard each intelligent vehicle as an atom and strategy as electron and consider electron transition process. Experimental results validate the effectiveness and superior of our algorithm compared with several existed offloading strategy, and the larger average amount of data waiting to be processed, the more significant our advantage is.