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SODA
2001
ACM

Approximate majorization and fair online load balancing

13 years 5 months ago
Approximate majorization and fair online load balancing
This paper relates the notion of fairness in online routing and load balancing to vector majorization as developed by Hardy, Littlewood, and Polya 9]. We de ne -supermajorization as an approximate form of vector majorization, and show that this de nition generalizes and strengthens the pre x measure proposed by Kleinberg, Rabani and Tardos 11] as well as the popular notion of max-min fairness. The paper revisits the problem of online load-balancing for unrelated 1-1 machines from the viewpoint of fairness. We prove that a greedy approach is O(logn)-supermajorized by all other allocations, where n is the number of jobs. This means the greedy approach is globally O(logn)-fair. This may be constrasted with polynomial lower bounds presented in 7] for fair online routing. We also de ne a machine-centric view of fairness using the related concept of submajorization. We prove that the greedy online algorithm is globally O(logm)-balanced, where m is the number of machines.
Ashish Goel, Adam Meyerson, Serge A. Plotkin
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where SODA
Authors Ashish Goel, Adam Meyerson, Serge A. Plotkin
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