Optimal Pricing for Service Caching and Task Offloading in Edge Computing

Abstract

Motivated by the emergence of function-as-a-service (FaaS) as a programming abstraction for edge computing, we consider the problem of caching and pricing applications for edge computation offloading. We model the problem as a multiple-follower Stackelberg game, where the operator is the leader and decides what applications to cache and how much to charge for their use, while the wireless devices (WDs) are the followers and decide whether or not to offload their computations. We show that the WDs' interaction can be modeled as a player-specific congestion game and show the existence and computability of equilibria. We then show that the equilibrium price of the operator can be computed in polynomial time for any cache placement, and propose a greedy algorithm for computing the applications to be cached. We use extensive simulations to show that the proposed heuristic performs close to optimal at negligible computational overhead.