Balancing QoS and power consumption in programmable 5G infrastructures

The advent of fifth generation is promising to push far more intelligence than today to the network boundary, hence boosting novel computing models based on fog/edge paradigms. The need for proximity in computation, coupled with various forms of mobility, will be responsible for dynamic shifting of workload within the system, with large fluctuations in resource usage. This eventually turns into poor energy efficiency of the whole infrastructure. However, improving efficiency usually deteriorates quality of service, hence the dilemma about how to balance these two contrasting aspects. In this paper, we propose a framework that leverages the increasing programmability of ICT infrastructures to pursue a linear relationship between power consumption and workload, while safeguarding quality of service. Our approach is based on workload consolidation and extensions to existing cloud management software. We collected both real measurements from an experimental testbed and performance analysis from simulations to evaluate the consolidation strategy in more complex environments. User mobility and the need for small latency and close proximity are expected to result in large fluctuations in workload and utilization at the network edge, evantually leading to large energy inefficiency. Boosting the usage of power‐saving mechanisms and balancing efficiency with QoS is the only viable road for sustainable and cost‐effective 5G infrastructures.