Game-based distributed pricing and task offloading in multi-cloud and multi-edge environments

Abstract Enabling cloud–edge collaboration to Internet of Things (IoT) systems can better satisfy the application requirements of mobile devices (MDs). In the environments where cloud service providers (CSPs) and edge service providers (ESPs) coexist, it is critical to design a mechanism for the competitive IoT markets to maximize the revenues of CSPs and ESPs and optimize the quality of experience (QoE) of MDs. This area is less considered by the existing works. To this end, we propose a distributed pricing and task offloading mechanism for multi-cloud and multi-edge IoT environments. We introduce a multi-leader multi-follower two-tier Stackelberg game to model the interaction between service provides and MDs. We further design two distributed algorithms, namely, an iterative proximal offloading algorithm (IPOA) and an iterative Stackelberg game pricing algorithm (ISPA). The former solves the follower non-cooperative game among MDs and the latter uses backward induction to deal with the price competition among service providers. Experimental results show that IPOA can markedly reduce the disutility of MDs compared with other traditional task offloading schemes, and the price of anarchy (PoA) is always less than 2. Besides, the results also demonstrate that ISPA is reliable in improving the revenue of service providers while guaranteeing the QoE of MDs.