Serverless computing has become increasingly popular recently due to its cost efficiency and flexibility.However,running serverless computing functions in the cloud can incur high end-to-end service latency and operat...Serverless computing has become increasingly popular recently due to its cost efficiency and flexibility.However,running serverless computing functions in the cloud can incur high end-to-end service latency and operational costs.Running them on edge servers may significantly reduce service latency but is limited by computing power and memory availability.Given the limitations of cloud and edge environments for performing serverless com-puting,this paper proposes a joint function warm-up and request routing scheme to perform serverless computing functions on edge and cloud collaboratively.The key idea of the new scheme is to maximize the hit ratio of server-less computing requests,thereby reducing the cold-start latency that dominates the overall serving latency.This scheme explicitly considers allocating server memory and operation budget for executing concurrent requests during the scheduling.The proposed scheme has been evaluated through extensive simulations.Its effectiveness has been proved by comparison with the upper-bound results.展开更多
文摘Serverless computing has become increasingly popular recently due to its cost efficiency and flexibility.However,running serverless computing functions in the cloud can incur high end-to-end service latency and operational costs.Running them on edge servers may significantly reduce service latency but is limited by computing power and memory availability.Given the limitations of cloud and edge environments for performing serverless com-puting,this paper proposes a joint function warm-up and request routing scheme to perform serverless computing functions on edge and cloud collaboratively.The key idea of the new scheme is to maximize the hit ratio of server-less computing requests,thereby reducing the cold-start latency that dominates the overall serving latency.This scheme explicitly considers allocating server memory and operation budget for executing concurrent requests during the scheduling.The proposed scheme has been evaluated through extensive simulations.Its effectiveness has been proved by comparison with the upper-bound results.
