Qingxiang Liu

TL;DR: A system model and dynamic schedules of data/control-constrained computing tasks are investigated, including the execution time and energy consumption for mobile devices, and NSGA-III (non-dominated sorting genetic algorithm III) is employed to address the multi-objective optimization problem of task offloading in cloud-edge computing.

TL;DR: A mobile crowdsourcing framework based on blockchain is designed first to preserve the privacy of the participants and keep the integrity of the service request and provision, and then density-based spatial clustering of applications with noise and improved dynamic programming are adopted to cluster the requestors and generate service strategies, respectively.

TL;DR: An IoT-oriented Data Placement method with privacy preservation, named IDP, is designed in this paper and designed to achieve high resource usage, energy saving and efficient data access, and meanwhile realize privacy preservation of the IoT data.

TL;DR: A blockchain‐based computation offloading method, named BCO, which is designed to degrade the data loss possibility by integrating blockchain and EC, and takes advantage of Simple Additive Weighting and Multiple Criteria Decision Making to identify the optimal offloading strategy.

TL;DR: A heuristic VM scheduling method is designed through VM placement and dynamic VM scheduling by leveraging the VM live migration technique to realize the load balancing for the computing nodes in the fog-cloud environment.