On the Optimal Trade-Off of Delay and Energy Consumption in 3C-Enabled F-RAN

In order to improve the flexibility and resilience of network service provision under constrained resources, a joint scheduling of communication-computation-caching (3C) is investigated. Focusing on the application of adaptive bit-rate (ABR) content streaming, a 3C-enabled fog radio access network (F-RAN) is established in the first place. Within the proposed architecture of 3C-enabled F-RAN for ABR, the sequential arrivals and processing of users’ content requests are modeled as a multi-class processor queue. On this basis, the average delay and energy consumption in downloading a requested content are respectively analyzed and obtained in closed-form expressions. For optimizing these two performance metrics separately, alternating direction method of multipliers-based algorithms are proposed by efficiently utilizing the available 3C resources. Since these two metrics cannot be optimized simultaneously, in order to characterize the optimal performance trade-off between them, an evolutionary multitasking-based constrained multi-objective optimization-based algorithm is proposed to solve the Pareto frontier. The proposed algorithm is more robust to population size and converges faster as compared to the state-of-the-art methods. Simulation results demonstrate the obtained Pareto frontier between delay and energy consumption, illustrating an inherent performance trade-off between them. With a coordinated allocation of 3C, customized services can be provided while avoiding unnecessary waste of resources.