Cost and Delay-Aware Service Replication for Scalable Mobile Edge Computing

Mobile edge computing (MEC) has emanated as a propitious computing paradigm that can foster delay-sensitive and/or data-intensive applications. However, it can be challenging to maintain a scalable MEC service when computational resources are overloaded. In this article, we propose the service replication between multiple service providers (SRMSPs) scheme. SRMSP is the first scheme that fosters service scalability in a cost-efficient manner, while considering the stringent QoS requirements of real-time applications involving groups of users. SRMSP enables SRMSPs to minimize the average response delay and the operational cost incurred by service providers, while satisfying the delay requirements of all user groups. We formulate the resource allocation problem as an integer linear program (ILP) and derive an analytical solution using the Karush-Kuhn-Tucker (KKT) conditions and Lagrangian analysis. In addition, we propose the SRMSP-distributed allocation (SRMSP-DA) scheme to provide a time-efficient solution in distributed scenarios. In SRMSP-DA, we use a game-theoretic strategy that formulates the resource allocation problem as a potential game. Extensive simulations show that SRMSP renders a 50% operational cost reduction compared to a baseline scheme that does not consider the operational cost. In addition, SRMSP-DA exhibits a relatively marginal difference of up to 20% and 4% in terms of the total operational cost and average response delay, respectively, compared to the optimal solution provided by SRMSP.