Abstract
It is the need of an era to store and process big data and its applications. To process these applications, it is inevitable to use heterogeneous distributed computing systems (HeDCS). The heterogeneous distributed systems facilitate scalability, an essential characteristic for big data processing. However, to implement the scalable model, it is essential to handle performance, efficiency, optimal resource utilization and several other key constraints. Scheduling algorithms play a vital role in achieving better performance and high throughput in heterogeneous distributed computing systems. Hence, selection of a proper scheduling algorithm, for the specific application, becomes a critical task. Selection of an appropriate scheduling algorithm in heterogeneous distributed computing systems require the consideration of various parameters like scheduling type, multi-core processors, and heterogeneity. The paper discusses broadly the hierarchical classification of scheduling algorithms implemented in heterogeneous distributed computing systems and presents a comparative study of these algorithms, thus providing an insight into the significance of various parameters that play a role in the selection of a scheduling algorithm.
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Padole, M., Shah, A. (2018). Comparative Study of Scheduling Algorithms in Heterogeneous Distributed Computing Systems. In: Choudhary, R., Mandal, J., Bhattacharyya, D. (eds) Advanced Computing and Communication Technologies. Advances in Intelligent Systems and Computing, vol 562. Springer, Singapore. https://doi.org/10.1007/978-981-10-4603-2_12
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DOI: https://doi.org/10.1007/978-981-10-4603-2_12
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