Job scheduling with adaptable computing levels for edge computing

Abstract

Edge computing is an emerging technology that can help huge number of devices be connected and processed with low latency. However, the performance of edge servers is far less powerful than cloud servers. When dealing with a large number of job requests from user devices, traditional job scheduling methods are not efficient enough. In this paper, we propose a new job scheduling model by considering adaptable jobs that can be executed with different computing levels and accordingly different resource requirements. We design a new job scheduling algorithm based on such an adaptable job model. The algorithm can choose an appropriate level for each job according to resource availability. Compared with existing works, our design can achieve better tradeoff between resource utilization and quality of experience. To the best of our knowledge, this is the first paper that considers adaptable job computing levels.