Abstract: Edge computing has been envisioned as an effective solution to enhance the computing capabilities for resource-constrained mobile devices.It allows users to satisfy the resource requirement by offloading heavy computing tasks to the edge cloud.However,it still needs to commit to solving the issues of energy consumption and reliability.This paper firstly proposes an energy-aware collaborative task execution scheduling model,which combines computing offloading model and fault-tolerant model to reduce energy consumption while improving reliability of edge computing within time constraints of tasks.Then,an energy-aware fault-tolerant collaborative task execution scheduling algorithm including collaborative task execution,initial scheduling and online scheduling is proposed to improve reliability while reducing energy consumption.The collaborative task execution is to determine the execution decision of tasks by partial critical path analysis and one-climb policy.The initial scheduling is to determine the fault-tolerant strategy from replication and resubmission for tasks executed on the edge cloud,ensuring the tasks processing successfully.The online scheduling is to adjust the fault-tolerant strategy in real time when a fault occurs.Finally,through extensive simulation experiments with the three different representative task topologies,the performance difference under three different scenarios in terms of the task completion rate and the energy consumption ratio are evaluated.Results show that the proposed method is more reliable than collaborative task execution and more energy-aware than local execution in terms of the change of the deadline,the data transmission rate,and the fault tolerance rate.

Key words: Computing offloading, Edge computing, Fault-tolerant, Replication, Resubmission