Combinatorial Auction-enabled Dependency-Aware Offloading Strategy in Mobile Edge Computing

Mobile Edge Computing (MEC) enables computation offloading from resource-constrained mobile devices to edge servers in close vicinity, effectively promoting the user experience on emerging interactive multimedia applications such as virtual/augmented reality, mobile gaming, and mobile video editing. However, most contemporary MEC offloading research disregards the interdependencies between partitioned subtasks of application. Also, few studies focused on application topologies have neglected to design effective incentives to encourage edge servers to provide offloading services. In this paper, we propose a dependency-aware offloading algorithm based on a multi-round truthful combinatorial reverse auction (MTCRA) to address the social welfare maximization problem in the paradigm of MEC. Building on the topology of directed acyclic graphs (DAGs) modeled from applications, we discuss the complementarity and substitutability of subtasks in the context of combinatorial auction. Theoretical analysis shows that the presented auction mechanism achieves computing efficiency while maintaining desirable economic features like truthfulness, individual rationality, and budget balance. Simulation results demonstrate that the proposed algorithm achieves high social welfare regarding reduced execution time and good economic benefits for MEC servers.