Assessing the Impact of Diverse Scheduling Strategies on Digital Library System Performance
- DOI
- 10.2991/978-94-6463-300-9_49How to use a DOI?
- Keywords
- Scheduling Strategies; Digital Library Systems; Performance
- Abstract
With the evolution and maturity of cloud computing and big data technologies, the shift from traditional libraries to digital libraries has emerged as a prevailing trend. To comprehend the current scheduling strategies employed within digital libraries, and to address challenges such as server congestion and the absence of robust scheduling strategies, this study aims to evaluate and compare various scheduling techniques found in digital libraries. This article offers a comprehensive overview of four primary categories of scheduling strategies, along with the essential components of digital library systems. These insights, gleaned from an exhaustive review of existing literature, set the stage for a more in-depth discussion on the application of these scheduling strategies within digital library systems. Subsequently, the study delves into a comparative analysis of the application, advantages, and drawbacks of these four key categories of scheduling strategies in the context of managing virtual resources. The discussion is divided into four segments, each devoted to a particular class of scheduling strategies.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haoqin Shi PY - 2023 DA - 2023/11/27 TI - Assessing the Impact of Diverse Scheduling Strategies on Digital Library System Performance BT - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023) PB - Atlantis Press SP - 485 EP - 491 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-300-9_49 DO - 10.2991/978-94-6463-300-9_49 ID - Shi2023 ER -