Dynamic Interplay Between Service Caching and Code Offloading in Mobile-Edge-Cloud Networks

Service caching has been emerging as a key technology that can overcome the hardware limitations of mobile devices by leasing resources from mobile edge computing (MEC) servers. This technology is inherently different from content caching where caching performance can be maximized by caching the most popular contents since most of the services require workload processing from CPU/GPU in servers. Thereby caching the most popular services on the MEC server may not be the best choice. Besides, when the service caching system is designed together with code offloading policy, the problem becomes more difficult because two control parameters are tightly intertwined with each other. In this paper, we formulate an average cost minimization problem of mobile devices constrained by service queue stability in a three-layer (mobile/MEC/cloud) network architecture. We apply a statistic-based dynamic optimization framework to derive an online-fashioned interTWined Interplay between Storage and Transmission, namely TWIST algorithm that jointly makes decisions of service caching, CPU/GPU clock frequency of mobile devices, and code offloading. Next, via theoretical analysis, we show the trade-off relationships between average cost of mobile devices and service delay. Finally, extensive simulations demonstrate that TWIST can save up to 51% of cost for the same delay 2.41sec. compared to the existing algorithms.