We consider geographically distributed data centers forming a collectively managed cloud computing system, hosting multiple Service Oriented Architecture (SOA) based context aware applications, each subject to Service Level Agreements (SLA). The Service Level Agreements for each context aware application require the response time of a certain percentile of the input requests to be less than a specified value for a profit to be charged by the cloud provider. We present a novel approach of data-oriented dynamic service-request allocation with gi-FIFO scheduling, in each of the geographically distributed data centers, to globally increase the profit charged by the cloud computing system. Our evaluation shows that our dynamic scheme far outperforms the commonly deployed static allocation with either First in First Out (FIFO) or Weighted Round Robin (WRR) scheduling.
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Boloor et al. (2010) studied this question.
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