Analysis of Dynamic Resource Allocation in Digital Education Ecosystems

ABSTRACT

The use of technology enhanced learning in education institutions has been developing at a rapid pace. Higher education administration affirms the value of digitization in learning platforms, especially in view of the response to the COVID-19 pandemic. The conventional education system is not consistent with the changing demands of modern education concepts, which are the driving factors towards formation and development of the digital educational ecosystem. To digitally transform education systems within a cross organizational environment, educational institutions should be interconnected, and the learners are able to access the learning modules from anywhere in the world. The effective allocation of learning modules to the students is of crucial importance due to the scarceness of such resources. The main objective of this paper is to identify the methods for assigning digital learning modules from a set of existing solutions. Facilitated by optimal resource allocation, the digital ecosystem can provision learning instances via virtual machines or containers and allocate it based on demand. Through the optimal resource allocation, the overall cost and power consumption shall be decreased and the availability of the learning service shall be increased. In this paper, literature research of different scheduling and allocation policies are discussed under varying statistical processes, priority, and performance metrics to increase efficiency and reduce operating cost of servers with no allocated task. © 2022 IEEE.