A Multi-server Approach for Large Scale Collaborative Game-Based Learning

  • Yunhua Deng
  • Zhe Huang
Conference paper

DOI: 10.1007/978-3-319-09635-3_9

Volume 8613 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Deng Y., Huang Z. (2014) A Multi-server Approach for Large Scale Collaborative Game-Based Learning. In: Popescu E., Lau R.W.H., Pata K., Leung H., Laanpere M. (eds) Advances in Web-Based Learning – ICWL 2014. ICWL 2014. Lecture Notes in Computer Science, vol 8613. Springer, Cham

Abstract

E-learning through online games, where users play collaboratively to gain knowledge, has great potential to significantly change the way we learn. As the number of participants is no longer limited by the classroom, the learning process could potentially involve tens of thousands of learners. However, hosting massive users playing in a shared game world is nontrivial, as the underlying servers may get overloaded by the constantly changing workload due to user activity. In this work, we adapt a multi-server approach with dynamic load balancing to enable large scale collaborative game-based learning. Through simulation, we thoroughly evaluate its performance and identify the optimal settings of the key load balancing parameters under different scenarios. Results imply that the multi-server approach can support tens of thousands of users learning together, through combining the power of multiple servers each of which only can handle hundreds of users.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yunhua Deng
    • 1
  • Zhe Huang
    • 1
  1. 1.City University of Hong KongKowloonHong Kong, China