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Through offloading the computing tasks of the task nodes (TNs) to the fog nodes (FNs) located at the network edge, the fog network is expected to address the unacceptable processing delay and heavy link burden existed in current cloudbased networks. Unlike most existing researches based on the command-mode offloading and full capability report, this paper develops a general analytical model of the task scheduling among voluntary nodes (VNs) in fog networks, wherein the VNs voluntarily contribute their capabilities for serving their neighboring TNs. A novel Delay-Optimal Task Scheduling (DOTS) algorithm is proposed to obtain the delay-optimal offloading solution according to the reported capabilities of the VNs. Extensive simulations are carried out in a fog network, and the numerical results indicate that the proposed DOTS algorithm can effectively provide the optimal helper nodes (HNs) set, subtask sizes, and TN transmission power to minimize the overall task processing delay. Moreover, compared with the command-mode offloading, the voluntary-mode achieves more balanced offloading and a higher fairness level among the FNs.

Local and customized services are realized with new type computing architecture by utilizing the spare resources distributed on the helper nodes (HNs) throughout the network. The heterogeneity of mobile edge and fog computing networks makes them natural to support multitarget tasks, and efficient task scheduling is always a fundamental and hot issue in multitask multihelper (MTMH) computing networks. Unlike most of the researches concentrating on the optimization of a single or limited service metrics, this article proposes a service framework for multitarget tasks, which is more universal for future 6G networks supporting customized services. The comprehensive quality of service (CQoS) is constructed to indicate the comprehensive objectives of the task nodes (TNs) with multiple targets. By formulating and transforming the CQoS maximal problem into two one-variable form subproblems, an algorithm named scheduling of comprehensive objectives for tasks with multitargets (SCOTT) is proposed. The SCOTT algorithm achieves the optimal offloading service solutions considering service metrics including delay, energy consumption, and economic cost. Extensive numerical simulations are carried out, which indicate that the proposed SCOTT algorithm can effectively achieve the optimal offloading solutions including node selection, task division, and transmission power for TNs with various service targets. Moreover, the universal applicability of the SCOTT algorithm is verified with case studies and numerical results.