@article { IoT2023,
	title = {Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform},
	journal = {Internet of Things; Engineering Cyber Physical Human Systems},
	year = {2023},
	publisher = {Elsevier},
	abstract = {Mobile devices are becoming ubiquitous in our daily lives, but they have limited computational capacity. Thanks to the advancement in the network infrastructure, task offloading from resource-constrained devices to the near edge and the cloud becomes possible and advantageous. Complete task offloading is now possible to almost limitless computing resources of public cloud platforms. Generally, the edge computing resources support latency-sensitive applications with limited computing resources, while the cloud supports latency-tolerant applications. This paper proposes one lightweight task-scheduling framework from cloud service provider perspective, for applications using both cloud and edge platforms. Here, the challenge is using edge and cloud resources efficiently when necessary. Such decisions have to be made quickly, with a small management overhead. Our framework aims at solving two research questions. They are: i) How to distribute tasks to the edge resource pools and multi-clouds? ii) How to manage these resource pools effectively with low overheads? To answer these two questions, we examine the performance of our proposed framework based on Reliable Server Pooling (RSerPool). We have shown via simulations that RSerPool, with the correct usage and configuration of pool member selection policies, can accomplish the cloud/edge setup resource selection task with a small overhead.},
	keywords = {Cloud computing, Edge Computing, Reliable Server Pooling (RSerPool), Resource Pools, Task Scheduling},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
