TY - GEN
T1 - Online load balancing of temporary tasks
AU - Azar, Yossi
AU - Kalyanasundaram, Bala
AU - Plotkin, Serge
AU - Pruhs, Kirk R.
AU - Waarts, Orli
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1993.
PY - 1993
Y1 - 1993
N2 - We consider non-preemptive online load balancing problem under the assumption that tasks have limited duration in time. Each task has to be assigned immediately upon arrival to one of the machines, increasing the load on this machine for the duration of the task. The goal is to minimize the maximum load. Azar, Broder and Karlin studied the unknown duration case where for each task there is a subset of machines capable of executing it; the increase in load due to assignment of the task to one of these machines depends only on the task and not on the machine. For this case, they showed an O(n2/3)-competitive algorithm and an O(√n) lower bound, where n is the number of the machines. We close the gap by showing an O(√n)-competitive algorithm. We also consider the related machines case with unknown task duration. Here, a task can be executed by any machine and the increase in load depends on the speed of the machine and the weight of the task. For this case we show a 20-competitive algorithm and a lower bound of 3-o(1). Trying to overcome the O(√n) lower bound for the case of unknown task duration, we study a variant of the load balancing problem for tasks with known duration. For this case we show an O(log nT)-competitive algorithm, where T is the ratio of the maximum to minimum duration.
AB - We consider non-preemptive online load balancing problem under the assumption that tasks have limited duration in time. Each task has to be assigned immediately upon arrival to one of the machines, increasing the load on this machine for the duration of the task. The goal is to minimize the maximum load. Azar, Broder and Karlin studied the unknown duration case where for each task there is a subset of machines capable of executing it; the increase in load due to assignment of the task to one of these machines depends only on the task and not on the machine. For this case, they showed an O(n2/3)-competitive algorithm and an O(√n) lower bound, where n is the number of the machines. We close the gap by showing an O(√n)-competitive algorithm. We also consider the related machines case with unknown task duration. Here, a task can be executed by any machine and the increase in load depends on the speed of the machine and the weight of the task. For this case we show a 20-competitive algorithm and a lower bound of 3-o(1). Trying to overcome the O(√n) lower bound for the case of unknown task duration, we study a variant of the load balancing problem for tasks with known duration. For this case we show an O(log nT)-competitive algorithm, where T is the ratio of the maximum to minimum duration.
UR - https://www.scopus.com/pages/publications/84947791860
U2 - 10.1007/3-540-57155-8_241
DO - 10.1007/3-540-57155-8_241
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AN - SCOPUS:84947791860
SN - 9783540571551
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 119
EP - 130
BT - Algorithms and Data Structures - 3rd Workshop, WADS 1993, Proceedings
A2 - Dehne, Frank
A2 - Sack, Jorg-Rudiger
A2 - Santoro, Nicola
A2 - Whitesides, Sue
PB - Springer Verlag
T2 - 3rd Workshop on Algorithms and Data Structures, WADS 1993
Y2 - 11 August 1993 through 13 August 1993
ER -