Energy-optimal resource scheduling and computation offloading in small cell networks
Abstract
This paper provides a joint optimization framework of radio resource scheduling and computation offloading in small cell LTE based networks. We consider that mobile users are served by nearby small cell base stations which can be endowed with some computational capabilities. The objective is to minimize the average energy consumption at the user terminal to run its mobile applications, either locally or remotely, while satisfying average delay constraints tolerated by these applications. For this problem, we investigate offline dynamic programming approaches and we devise two solutions: deterministic and randomized, to find the optimal radio scheduling-offloading policy. We show that the dynamic offline strategies are able of achieving optimal energy efficiency at the mobile terminals. Indeed, they can adapt the processing decisions between: local processing, offloading, and staying idle, by exploiting their knowledge on the channel conditions and the application properties.
Keywords
Balloons
Energy efficiency
Energy utilization
Mobile telecommunication systems
Scheduling
Wireless telecommunication systems
Application properties
Channel conditions
Computation offloading
Computational capability
Joint optimization
Mobile applications
Resource-scheduling
Small cell Networks
Dynamic programming