Design of Task Distribution and Scheduling Strategies for Data Processingin the Internet of Things

To adapt to the characteristics of IoT tasks arriving online (i.e., the arrival pattern and time of tasks cannot be pre-dicted), delay sensitivity, and limited processing unit resources, to ensure the completion of tasks with low latency and to ensure the efficient and stable operation of the IoT platform, this paper studies the problem of online task distribution and scheduling in the unit manager of a data-driven Internet of Things (IoT) architecture. The problem is modeled and an efficient online task distribution and scheduling algorithm is proposed, named OnSche. We have validated the performance of the OnSche algorithm using real datasets and conducted a thorough verification. The experimental results show that under different parameter changes, OnSche is consistently superior to the baseline methods.