Age of Information Analysis for Task Offloading in an Energy Harvesting Status Update System

This paper considers a computation-intensive status update system with energy harvesting technology. The status update packets can be processed locally or partially offloaded to a mobile edge computing server. Using the stochastic hybrid system approach, we analyze the moment generating function of the age of information (AoI) for three different disciplines (preemption, discarding, and blocking) under zero-wait policy. The numerical results show that the preemption discipline gives the best performance while the discarding discipline is the worst. The results demonstrate the importance of obtaining higher AoI moments and facilitate choosing an offloading ratio that satisfies a given average AoI constraint.