How to Balance the Load Online When Jobs and Machines Are Both Selfish?
Wenqian Wang, Chenyang Xu, Yuhao Zhang

TL;DR
This paper introduces the first online truthful mechanism for load balancing with both selfish jobs and machines, achieving an $O( ext{log } m)$ competitive ratio and extending to $ ext{ell}_q$ norm variants.
Contribution
It presents the first non-trivial two-sided truthful online load balancing mechanism for related machines with competitive guarantees.
Findings
Achieves $O( ext{log } m)$ competitive ratio for two-sided truthful online load balancing.
Extends mechanism to $ ext{ell}_q$ norm load balancing with competitive ratio $ ilde{O}(m^{rac{1}{q}(1-rac{1}{q})})$.
First mechanism to be truthful for both selfish jobs and machines in an online setting.
Abstract
In this paper, we study the classic optimization problem of Related Machine Online Load Balancing under the conditions of selfish machines and selfish jobs. We have related machines with varying speeds and jobs arriving online with different sizes. Our objective is to design an online truthful algorithm that minimizes the makespan while ensuring that jobs and machines report their true sizes and speeds. Previous studies in the online scenario have primarily focused on selfish jobs, beginning with the work of Aspnes et al. (JACM 1997). An -competitive online mechanism for selfish jobs was discovered by Feldman, Fiat, and Roytman (EC 2017). For selfish machines, truthful mechanisms have only been explored in offline settings, starting with Archer and Tardos (FOCS 2001). The best-known results are two PTAS mechanisms by Christodoulou and Kov\'{a}cs (SICOMP 2013) and Epstein…
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Taxonomy
TopicsScheduling and Optimization Algorithms
