TODG: Distributed Task Offloading With Delay Guarantees for Edge Computing

Edge computing has been an efficient way to provide prompt and near-data services for resource-and-delay sensitive IoT applications via computation offloading. Effective offloading strategies need comprehensively cope with several major issues, including 1) the allocation of dynamic communication computational resources, 2) delay constraints heterogeneous tasks, 3) requirements computationally inexpensive distributed algorithms. However, most existing works mainly focus on part these which would not suffice achieve expected performance in complex practical scenarios. To tackle this challenge, paper, we systematically study a problem constraints, where tasks require continually set edge servers limiting number stochastic channels. The task is formulated as delay-constrained long-term optimization under unknown prior statistical knowledge. solve problem, first technical path transform decompose it into slot-level sub-problems. Then, devise online algorithm, namely TODG, efficiently allocate resources schedule tasks. Further, present comprehensive analysis TODG terms optimality gap, worst-case delay, impact system parameters. Extensive simulation results demonstrate effectiveness efficiency TODG.