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Online List Scheduling for Makespan Minimization: A Review of the State-of-the-art Results, Research Challenges, and Open Problems

Publication Type : Journal Article

Publisher : ACM

Source : ACM SIGACT News, vol. 53, no. 2, pp. 84-105, 2022.

Url : https://dl.acm.org/doi/10.1145/3544979.3544993

Campus : Coimbatore

School : School of Computing

Year : 2022

Abstract : In the modern interactive computing era, computational problems such as scheduling, rout- ing, sequencing, and resource management are online in nature. In the online framework, at the outset, an algorithm receives and processes inputs one by one in order without the knowledge of future inputs, unlike in an offline framework, where an algorithm knows the entire input sequence at the beginning. The design of mathematical models and efficient al- gorithms for the online framework constitutes a challenging and competitive area of research in Theoretical Computer Science. The researchers have considered competitive analysis as a well-de ned and standard method to measure the performance of online algorithms.

Cite this Research Publication : Debasis Dwibedy and Rakesh Mohanty. Online List Scheduling for Makespan Minimization: A Review of the State-of-the-art Results, Research Challenges, and Open Problems. ACM SIGACT News, vol. 53, no. 2, pp. 84-105, 2022.

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