Using dual approximation algorithms for scheduling problems theoretical and practical results
Journal of the ACM (JACM)
A lower bound for randomized on-line scheduling algorithms
Information Processing Letters
A lower bound for randomized on-line multiprocessor scheduling
Information Processing Letters
Load balancing for response time
Journal of Algorithms
Developments from a June 1996 seminar on Online algorithms: the state of the art
Developments from a June 1996 seminar on Online algorithms: the state of the art
Improved Bounds for the Online Scheduling Problem
SIAM Journal on Computing
A robust APTAS for the classical bin packing problem
Mathematical Programming: Series A and B
Online Scheduling with Bounded Migration
Mathematics of Operations Research
A polynomial-time approximation scheme for maximizing the minimum machine completion time
Operations Research Letters
A truthful constant approximation for maximizing the minimum load on related machines
WINE'10 Proceedings of the 6th international conference on Internet and network economics
On-line machine covering on two machines with local migration
Computers & Mathematics with Applications
Robust algorithms for preemptive scheduling
ESA'11 Proceedings of the 19th European conference on Algorithms
The power of deferral: maintaining a constant-competitive steiner tree online
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
A robust AFPTAS for online bin packing with polynomial migration,
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
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Minimizing the makespan or maximizing the minimum machine load are two of the most important and fundamental parallel machine scheduling problems. In an online scenario, jobs are consecutively added and/or deleted and the goal is to always maintain a (close to) optimal assignment of jobs to machines. The reassignment of a job induces a cost proportional to its size and the total cost for reassigning jobs must preferably be bounded by a constant r times the total size of added or deleted jobs. Our main result is that, for any ε 0, one can always maintain a (1 + ε)-competitive solution for some constant reassignment factor r(ε). For the minimum makespan problem this is the first improvement of the (2+ε)-competitive algorithm with constant reassignment factor published in 1996 by Andrews, Goemans, and Zhang.