Nowadays, many enterprises provide cloud services based on their own Hadoop clusters. Because the resources of\na Hadoop cluster are limited, the Hadoop cluster must select some specific tasks to allocate limited resources in\norder to get the maximal profit. In this paper, we study the maximal profit problem for a given candidate task set.\nWe describe the candidate task set with a valid sequence and propose a sequence-based scheduling strategy. In\norder to improve the efficiency of finding a valid sequence, we design some pruning strategies and give the\ncorresponding scheduling algorithm. Finally, we propose a timeout handling algorithm when some task runs\ntimeout. Experiments show that the total profit of the proposed algorithm is very close to the ideal maxima and is\nobviously bigger than related scheduling algorithms under different experimental settings.
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