Joint Function Configuration and Multislot Offloading in Solar-Powered Serverless Edge Computing

In this paper, we address the novel problem of jointly considering dynamic function configuration, function download latency, multi-slot task offloading, and energy harvesting in order to process the maximum number of tasks. To this end, we formulate a mixed integer linear program (MILP) that optimizes (i) task offloading of servers, (ii) function configuration, (iii) function scheduling, (iv) function download decision, (v) energy usage, (vi) channel allocation. It provides a theoretical optimum, but leverages non-causal information and becomes computationally intractable in large scale networks. To address this challenge, we propose a fully distributed protocol called Distributed Task Offloading with Energy Harvesting (D-TOEH), where each server establishes a function importance ranking to activate functions required by more tasks. Our simulation results show that, on average, the performance of D-TOEH attains 71.36% of the theoretical optimum while ensuring low polynomial time complexity.