TY - GEN

T1 - Improved Algorithms for Online Load Balancing

AU - Liu, Yaxiong

AU - Hatano, Kohei

AU - Takimoto, Eiji

N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - We consider an online load balancing problem and its extensions in the framework of repeated games. On each round, the player chooses a distribution (task allocation) over K servers, and then the environment reveals the load of each server, which determines the computation time of each server for processing the task assigned. After all rounds, the cost of the player is measured by some norm of the cumulative computation-time vector. The cost is the makespan if the norm is L∞ -norm. The goal is to minimize the regret, i.e., minimizing the player’s cost relative to the cost of the best fixed distribution in hindsight. We propose algorithms for general norms and prove their regret bounds. In particular, for L∞ -norm, our regret bound matches the best known bound and the proposed algorithm runs in polynomial time per trial involving linear programming and second order programming, whereas no polynomial time algorithm was previously known to achieve the bound.

AB - We consider an online load balancing problem and its extensions in the framework of repeated games. On each round, the player chooses a distribution (task allocation) over K servers, and then the environment reveals the load of each server, which determines the computation time of each server for processing the task assigned. After all rounds, the cost of the player is measured by some norm of the cumulative computation-time vector. The cost is the makespan if the norm is L∞ -norm. The goal is to minimize the regret, i.e., minimizing the player’s cost relative to the cost of the best fixed distribution in hindsight. We propose algorithms for general norms and prove their regret bounds. In particular, for L∞ -norm, our regret bound matches the best known bound and the proposed algorithm runs in polynomial time per trial involving linear programming and second order programming, whereas no polynomial time algorithm was previously known to achieve the bound.

UR - http://www.scopus.com/inward/record.url?scp=85101503774&partnerID=8YFLogxK

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U2 - 10.1007/978-3-030-67731-2_15

DO - 10.1007/978-3-030-67731-2_15

M3 - Conference contribution

AN - SCOPUS:85101503774

SN - 9783030677305

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 203

EP - 217

BT - SOFSEM 2021

A2 - Bureš, Tomáš

A2 - Dondi, Riccardo

A2 - Gamper, Johann

A2 - Guerrini, Giovanna

A2 - Jurdzinski, Tomasz

A2 - Pahl, Claus

A2 - Sikora, Florian

A2 - Wong, Prudence W.

PB - Springer Science and Business Media Deutschland GmbH

T2 - 47th International Conference on Current Trends in Theory and Practice of Computer Science, SOFSEM 2021

Y2 - 25 January 2021 through 29 January 2021

ER -