Cooperative Data Sharing for Mobile Cloudlets Under Heterogeneous Environments

As accessing remote cloud via cellular network is costly due to the lower bandwidth, higher wide area network (WAN) latency, and higher energy consumption, mobile cloudlet that formed by several edge mobile devices has become an emerging computing paradigm and attracted increasing attention recently. Being different from the existing studies that mainly focus on the issue of computation offloading among the peers, this paper investigates the problem of cooperative data sharing among peers to overcome the data dissymmetry, especially with the presence of dynamic network context. First, a publish/subscribe-based data sharing model is designed to cope with the unpredictable communication condition. Then, the data transmission scheduling within cooperative mobile devices is formulated as a utility maximization optimization considering the limited channel capacity, heterogeneous quality of experience (QoE) requirements, and incentive mechanism for participation. To encourage cooperation among mobile devices, a data downloading/uploading queuing mechanism is elegantly designed. Furthermore, an online algorithm without predicting the future information on request arrivals and network changes is developed to simultaneously optimize data transmission and communication interface selection in the long run. Theoretical analysis shows that the proposed algorithm is able to obtain a utility arbitrarily close to the offline optimum and guarantee the delay bound. Simulations demonstrate the effectiveness and the superiority of the proposed algorithm over some existing typical strategies.