Edgeconomics: Price Competition and Selfish Computation Offloading in Multi-Server Edge Computing Networks

As edge computing provides crucial support for delay-sensitive and computation-intensive applications, many business entities deploy their own edge servers to compete for users, which forms multi-server edge computing networks. However, no prior work studies the competition among heterogeneous edge servers and how the competition affects users’ selfish computation offloading behaviors in such a network from an economic perspective. In this paper, we model the interactions between edge servers and users as a two-stage game. In Stage I, edge servers with heterogeneous marginal costs set their service prices to compete for users, and in Stage II, each user selfishly offloads its task to one of the edge servers or the remote cloud. Analyzing the equilibrium of the two-stage game is challenging due to edge servers’ heterogeneity and the congestion effect caused by resource sharing among users. We first prove that in Stage II, users’ selfish computation offloading game is a potential game and admits a unique Nash equilibrium (NE), for which we derive the explicit expression. We then analyze edge servers’ price competition game in Stage I and characterize the conditions for the uniqueness of the NE. We show that at equilibrium, users only choose low-priced edge servers, and hence edge servers with low marginal costs can win the price competition, which reflects the improvement of economic efficiency in competitive markets. Moreover, it is surprising that the equilibrium prices do not monotonically increase with the task execution delay. This is because a long execution delay gives a chance to edge servers with high marginal costs to win the competition, which results in more fierce competition among edge servers.