Latency Minimization for Mobile Edge Computing Networks

The proliferation of data-intensive mobile applications is causing latency to become an issue in mobile edge computing (MEC) systems. In this work, we propose a novel methodology that optimizes communication, computation, and caching configurations in MEC to minimize the mean latency experienced by mobile devices. Transmission and computation processes are modeled using M/G/1 queues to account for service rates and warm-up times. Our caching scheme includes time variables for each file at each edge server in determining when to discard files from storage. We theoretically analyze the latency experienced by mobile devices due to communication, computation, and caching, showing how MEC system latency depends on the offloading decisions of mobile devices, bandwidth and CPU resources, and expiration times of files in the storage of edge servers. Our method for solving the latency minimization problem consists of two main components: iNner cOnVex Approximation (NOVA) to deal with non-convexity in the optimization, and an online algorithm for preventing cache storage violations as new tasks arrive and are serviced by the MEC system. Simulation results show that our algorithm outperforms several baselines in minimizing latency, and verify the benefit of including different resource allocation variables in our optimization.

Automated summary

In this work, a novel methodology is proposed to optimize communication, computation, and caching configurations in mobile edge computing (MEC) systems, aiming at minimizing the mean latency of mobile devices. The transmission and computation processes are modeled using M/G/1 queues, considering service rates and warm-up times. The caching scheme includes time variables for each file at each edge server to determine when to discard files from storage. Theoretical analysis is conducted to examine the impact of communication, computation, and caching on the latency experienced by mobile devices in MEC systems, incorporating offloading decisions, resource allocation, and expiration times of files.